Immunotherapy has fundamentally changed the landscape of cancer treatment. However, only a subset of patients respond to immunotherapy, and a significant portion experience immune-related adverse events (irAEs). In addition, the predictive ability of current biomarkers such as programmed death-ligand 1 (PD-L1) remains unreliable and establishing better potential candidate markers is of great importance in selecting patients who would benefit from immunotherapy. Here, we focus on the role of serum-based proteomic tests in predicting the response and toxicity of immunotherapy. Serum proteomic signatures refer to unique patterns of proteins which are associated with immune response in patients with cancer. These protein signatures are derived from patient serum samples based on mass spectrometry and act as biomarkers to predict response to immunotherapy. Using machine learning algorithms, serum proteomic tests were developed through training data sets from advanced non-small cell lung cancer (Host Immune Classifier, Primary Immune Response) and malignant melanoma patients (PerspectIV test). The tests effectively stratified patients into groups with good and poor treatment outcomes independent of PD-L1 expression. Here, we review current evidence in the published literature on three liquid biopsy tests that use biomarkers derived from proteomics and machine learning for use in immuno-oncology. We discuss how these tests may inform patient prognosis as well as guide treatment decisions and predict irAE of immunotherapy. Thus, mass spectrometry-based serum proteomics signatures play an important role in predicting clinical outcomes and toxicity.

As the use of immune checkpoint inhibitors (ICIs) in treating a variety of cancer types has increased in recent years, so too have the number of reports on patients acquiring resistance to these therapies. Overcoming acquired resistance to immunotherapy remains an important need in the field of immuno-oncology. Herein, we present a case that suggests sequential administration of combination immunotherapy may be beneficial to advanced cervical cancer patients exhibiting acquired resistance to mono-immunotherapy. The patient’s tumor is microsatellite instability-high (MSI-H), which is an important biomarker in predicting ICI response. Results from recent interim prospective studies using combination immunotherapy (eg, nivolumab and ipilimumab) with anti-PD-1 plus anti-CTLA-4 inhibitor following progression on anti-PD-1 inhibitors (eg, nivolumab) have shown anti-tumor activity in patients with advanced melanoma and metastatic urothelial carcinoma. We also introduce retrospective studies and case reports/case series of dual checkpoint inhibition with anti-PD-1 inhibitor plus anti-CTLA-4 inhibitor after progression on prior anti-PD/PD-L1 monotherapy. To date, there has been no prospective study on the use of combined anti-PD-1 and anti-CTLA-4 therapy at the time of progression on anti-PD-1 therapy in patients with MSI-H tumors or advanced cervical cancer. In this report, we provide evidence that supports future investigations into such treatments.

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Cushing’s syndrome (CS), secondary to paraneoplastic syndrome, is more commonly seen in small cell lung cancer but never before reported in epidermal growth factor receptor-mutated adenocarcinoma of the lung. Here, we present a case of a patient whose symptoms of hypokalemia, hypertension, and progressive abnormal glucose levels led to further workup that revealed adrenocorticotropic hormone-dependent hypercortisolism. Her cortisol levels dropped after 1 month of osilodrostat treatment, while lung cancer was treated with osimertinib. The use of osilodrostat in paraneoplastic CS has been previously reported in only 3 patients.