Background Diagnosing seronegative rheumatoid arthritis (RA) can be challenging due to complex diagnostic criteria. We sought to discover diagnostic biomarkers for seronegative RA cases by studying metabolomic and lipidomic changes in RA patient serum. Methods We performed comprehensive metabolomic and lipidomic profiling in serum of 225 RA patients and 100 normal controls. These samples were divided into a discovery set (n = 243) and a validation set (n = 82). A machine-learning-based multivariate classification model was constructed using distinctive metabolites and lipids signals. Results Twenty-six metabolites and lipids were identified from the discovery cohort to construct a RA diagnosis model. The model was subsequently tested on a validation set and achieved accuracy of 90.2%, with sensitivity of 89.7% and specificity of 90.6%. Both seropositive and seronegative patients were identified using this model. A co-occurrence network using serum omics profiles was built and parsed into six modules, showing significant association between the inflammation and immune activity markers and aberrant metabolism of energy metabolism, lipids metabolism and amino acid metabolism. Acyl carnitines (20:3), aspartyl-phenylalanine, pipecolic acid, phosphatidylethanolamine PE (18:1) and lysophosphatidylethanolamine LPE (20:3) were positively correlated with the RA disease activity, while histidine and phosphatidic acid PA (28:0) were negatively correlated with the RA disease activity. Conclusions A panel of 26 serum markers were selected from omics profiles to build a machine-learning-based prediction model that could aid in diagnosing seronegative RA patients. Potential markers were also identified in stratifying RA cases based on disease activity.

Background: Trastuzumab and pertuzumab are anti-HER2 antibodies that bind to two different epitopes of HER2. Although pertuzumab itself did not exhibit substantial clinical benefit as monotherapy, it was approved to be used in combination with trastuzumab because of its ability to enhance the clinical efficacy of trastuzumab. Currently, the combination of trastuzumab and pertuzumab is being used as first-line treatment for HER2-positive metastatic breast cancer. However, while the combination of trastuzumab and pertuzumab has been effective, there is still opportunity for greater effectiveness by identifying anti-HER2 mAbs that will be better synergistic partners of trastuzumab, allowing for better efficacy and/or broader indications. Methods: A SynAb࣪ Platform was used to identify BSI-001, an anti-HER2 mAb, through trastuzumab-based synergistic functional screening. A competitive ELISA was used to perform epitope binning of the anti-HER2 antibodies. BSI-001 was further characterized in combination with trastuzumab for its bioactivity in vitro, including inhibition of cell proliferation and antigen-mediated internalization of HER2 positive cell lines. The synergistic effect of BSI-001 with trastuzumab was also evaluated in trastuzumab-resistant cell lines. Multiple animal models were then employed to investigate the synergistic antitumor activity of the combination in vivo. Results: BSI-001 is the best functional partner of trastuzumab identified through the SynAb࣪ platform. BSI-001 binds to a unique epitope, distinct from the binding epitopes of trastuzumab and pertuzumab. It exhibits superior bioactivity and efficacy in vitro and in vivo when combined with trastuzumab. The combination of BSI-001 and trastuzumab inhibits HER2-positive cancer cell growth more potently than that of trastuzumab and pertuzumab. The combination of BSI-001 with trastuzumab also shows inhibition of cell growth of the trastuzumab-resistant cell line BT-474 Clone 5, whereas the combination of pertuzumab and trastuzumab did not. In addition, BSI-001 is able to synergize with trastuzumab to promote antigen-antibody internalization. In animal models, BSI-001 demonstrates superior synergistic antitumor activity when combined with trastuzumab as compared to pertuzumab. Summary: The combination of BSI-001 and trastuzumab showed significantly better in vitro and in vivo activity than the combination of trastuzumab and pertuzumab. In addition, because of the activity of the BSI-001/trastuzumab combination in a trastuzumab-resistant cancer cell line, there is the potential for this combination to be used to treat patients with trastuzumab-resistant cancer or patients who experienced relapse following trastuzumab and pertuzumab treatment. Citation Format: Shukai Xia, Zeyu Peng, Xiaoyu Ding, Wanjian Gu, Yujie Zhong, Jinyu Liu, Hongyan Li, Xiaoyao Hao, Xiaodong F. Liu, Mark Z. Ma, Lan Luo, Chunni Zhang, Mingjiu Chen. BSI-001, a novel anti-HER2 antibody exhibiting potent synergistic efficacy with trastuzumab [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5290.

Background: To observe the correlation between Lp-PLA2, Hcy, CRP, Lp(a), AT-III, and TEG parameters and carotid atherosclerosis with combined hypertension and cerebral infarction and evaluate their value in risk determination.Methods: Patients with primary hypertension were selected as subjects and divided into 2 groups based on cerebral infarction: simple hypertension group and hypertension combined with cerebral infarction group. The differences of Lp-PLA2, Hcy, CRP, Lp(a), AT-Ⅲ, and TEG were compared. Spearson correlation and multivariate logistic regression model were used to analyze the correlation. A ROC curve was used to analyse the value of a single item and their combination for the determination of carotid AS risk.Results: The levels of single item and CIMT in the hypertension combined with cerebral infarction group were higher, and the values of R, EPL, and LY30 were lower than corresponding indicators in the simple hypertension group. Furthermore, it was found that Lp-PLA2 and Hcy were risk factors. The AUC for Hcy and Lp-PLA2 for the determination the carotid AS risk were larger. Conclusions: The increase or decrease of Lp-PLA2, Hcy, and TEG were important factors influencing the development of carotid AS with combined hypertension and cerebral infarction. The levels of Lp-PLA2, Hcy, and TEG with combined hypertension and cerebral infarction were significantly different from those with simple hypertension and could be used as independent predictive factors for determining carotid AS risk.