Baseline profile of intrinsic cytokines predicting prognosis of chronic hepatitis B patients responding to HBV therapeutic vaccinations

Objective To explore relevant biomarkers in chronic HBV (CHB) infected individuals, and whether their presence can be related to the prognosis of CHB (i.e., used as a prediction tool) and used as inclusion and exclusion criteria in clinical trials. Methods Thirty-four (34) cytokines and chemokines were analyzed in the baseline plasma of 130 chronic HBV infected patients and were matched with the clinical outcomes of these patients regarding to their responses to anti-HBV treatment by a mathematic model based on the Boolean method. A retrospective analysis was implemented to establish the prediction model, and a perspective analysis was performed to verify the prediction efficacy. Results Through analyzing 34 cytokines and chemokines in the baseline plasma of 130 chronic HBV infected patients by Boolean methods, we generated a predicting model successfully capable of screening out therapy non-responded patients. In this prediction model, six cytokines, including IL-8, IL-10, IL-17, IL-1RA, IFN-α, IL-18, defined as expressed or not-expressed, contributed to 21 possibilities, every of which predicts a clinical outcome. The model was verified in a separate chronic HBV infected population database, which included 76 patients, with 100% responders and 50% who are not responded to the immunotherapy identified. Conclusions The prediction model can be used to screen CHB patients as the inclusion incorporated into HBV clinical design and practice. By screening out inappropriate participants in clinical trials, therapy response rate may rise and lead to a more homogeneous responding population. For Boolean method which requires continuous iteration, more accurate prediction models will be established with more homogeneous data. This is very helpful for revealing the reason why certain CHB individuals can be functionally cured and others were not. The method may also have great potential and possible applications for other immunotherapies in the future. What is already known about the subject? 1. Chronic hepatitis B virus (CHB) infection can be controlled while rarely cured, or functionally cured. The exact reason why certain CHB individuals can be functionally cured and others were not, regarding to different treatment strategies, remains unclear. 2. Lack of relevant immunological biomarkers are often to blame clinical failures in immunotherapeutic treatments, particularly for the hepatitis B virus (HBV) therapeutic vaccination, since such trials use virological parameters as inclusion and exclusion criteria of patients, but seldom more relevant immunological biomarkers. What are the new findings? 1. Using patterns of cytokines, instead of single cytokines, to present CHB individuals’ immune status can help discovering the prognosis of their responses or not response to HBV therapeutic vaccination. 2. By utilizing the model, we predicted 10 patients out of 10 who were sensitive to the anti-HBV immunotherapy and 33 out of 66 who were not, in a distinct CHB population, and verified the predicting efficacy. How might it impact on clinical practice in the foreseeable future? 1. Immune status, presented by different patterns of cytokines/chemokines, might be used as an in/exclusion criteria in clinical trials to select a more appropriate treatment for CHB individuals. 2. By screening out inappropriate participants in clinical trials, therapy response rate may rise and lead to a more homogeneous responding population. For Boolean method which requires continuous iteration, more accurate prediction models will be established with such more homogeneous data. This is very helpful for revealing the reason why certain CHB individuals can be responsive to the treatments and toward the functionally cured and others could not. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was partly supported by the National Major Science and Technology Research Projects for the Control and Prevention of Major Infectious Diseases in China (2017ZX10202202, 2017ZX10202203007, 2013ZX10002001) to Drs. JM Zhang, HY Jia, LD Yang, and B.Wang, and the National Natural Science Foundation of China (81871640, 82172255) and Shanghai Municipal Science and Technology Major Project to B. Wang. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee/IRB of Huashan hospital, Fudan University gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors.