Cancer immunotherapy represents a transformative approach to cancer treatment, paving the way for personalized and precision medicine strategies. Despite the significant advances in immunotherapy, the treatment response rate remains a major clinical challenge. The stratification of patients into responders and nonresponders is paramount for immunotherapy treatment response, which reduces the likelihood of treatment challenges, expenses, and potentially severe adverse effects in cases where patients are not likely to respond. Therefore, in the present study, we optimized a mass spectrometry-based analytical assay deploying data-independent acquisition analysis (DIA) to simultaneously detect a panel of six well-known immune checkpoint proteins. Further, the optimized assay was analytically validated to assess the technical performance, and preliminary clinical feasibility testing was conducted using the clinical samples of immune cells from oral cancer patients. Altogether, we tested the method for the detection of the candidate proteins in samples from 20 oral cancer patients and healthy individuals. A proof-of-concept method using DIA-MS was optimized with a shorter turnaround time, facilitating a multiplexed detection and quantitation of protein targets within the panel. This DIA-MS method could be applied to detect potential immune checkpoint proteins without additional enrichment techniques. Furthermore, this optimized method can be used in clinical settings to guide appropriate drug selection based on the abundance of target protein(s) in each patient. The assay may also be adapted for other cancer types using the same multiprotein panel, or expanded in the future to include additional proteins validated as potential immunotherapeutic targets.
Aravind et al. (Mon,) studied this question.