Dataset Information

Bayesian Networks to Support Decision-Making for Immune-Checkpoint Blockade in Recurrent/Metastatic (R/M) Head and Neck Squamous Cell Carcinoma (HNSCC).

ABSTRACT: New diagnostic methods and novel therapeutic agents spawn additional and heterogeneous information, leading to an increasingly complex decision-making process for optimal treatment of cancer. A great amount of information is collected in organ-specific multidisciplinary tumor boards (MDTBs). By considering the patient's tumor properties, molecular pathological test results, and comorbidities, the MDTB has to consent an evidence-based treatment decision. Immunotherapies are increasingly important in today's cancer treatment, resulting in detailed information that influences the decision-making process. Clinical decision support systems can facilitate a better understanding via processing of multiple datasets of oncological cases and molecular genetic information, potentially fostering transparency and comprehensibility of available information, eventually leading to an optimum treatment decision for the individual patient. We constructed a digital patient model based on Bayesian networks to combine the relevant patient-specific and molecular data with depended probabilities derived from pertinent studies and clinical guidelines to calculate treatment decisions in head and neck squamous cell carcinoma (HNSCC). In a validation analysis, the model can provide guidance within the growing subject of immunotherapy in HNSCC and, based on its ability to calculate reliable probabilities, facilitates estimation of suitable therapy options. We compared actual treatment decisions of 25 patients with the calculated recommendations of our model and found significant concordance (Cohen's κ = 0.505, p = 0.009) and 84% accuracy.

SUBMITTER: Huehn M

PROVIDER: S-EPMC8657168 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The success of immune checkpoint receptor blockade has brought exciting promises for the treatment of head and neck squamous cell carcinoma (HNSCC). While patients who respond to checkpoint inhibitors tend to develop a durable response, <15% of patients with HNSCC respond to immune checkpoint inhibitors, underscoring the critical need to alleviate cancer resistance to immunotherapy. Major advances have been made to elucidate the intrinsic and adaptive resistance mechanisms to immunotherapy. Central genomic events in HNSCC have been found to possess previously unknown roles in suppressing immune sensing. Such inhibitory function affects both the innate and adaptive arms of tumor-specific immunity. While checkpoint blockade effectively reinvigorates adaptive T-cell responses, additional targeting of the oncogenic inhibitors of innate immune sensing likely informs a novel and potent strategy for immune priming. This review discusses the recent advances on the identification of key HNSCC oncogenes that impair antitumor immunity and emerging immune-priming approaches that sensitize poorly immunogenic HNSCCs to checkpoint blockade. These approaches include but are not limited to cancer vaccine systems utilizing novel type I interferon agonists as immune adjuvants, radiation, DNA damage-inducing agents, and metabolic reprogramming. The goal of these multipronged approaches is to expand tumor-specific effector T-cells, break checkpoint receptor-mediated tolerance, and metabolically support sustained T-cell activation. The translation of therapeutics that reverses oncogenic inhibition of immune sensing requires thorough characterization of the HNSCC regulators of innate immune sensors, development of additional immunocompetent HNSCC mouse models, as well as engineering of more robust immune adjuvant delivery systems. Built on the success of checkpoint blockade, validation of novel immune-priming approaches holds key promises to expand the pool of responders to immunotherapy.

Dataset Information

Bayesian Networks to Support Decision-Making for Immune-Checkpoint Blockade in Recurrent/Metastatic (R/M) Head and Neck Squamous Cell Carcinoma (HNSCC).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets