Cancer immunology and immunotherapy: immune profiling for data-driven patient selection and therapeutic guidance

The immune system can both restrain and fuel cancer, depending on disease stage and the tumor’s micro-environment. Over the past decade, this insight has led to immune checkpoint inhibitors (ICIs)—treatments that can deliver long-lasting benefits in several aggressive cancers. Yet because responses vary and costs are high, clinicians need better tools to match the right treatment to the right patient. This thesis shows how immune features in tissue and proteins measured from blood samples can guide those choices could be applied to improve cancer screening.

In HER2-positive advanced breast cancer, tumors rich in cytotoxic T cells and tumor-associated macrophages were linked with longer survival and longer trastuzumab-free intervals, suggesting that the “immune context” of the tumor helps predict who does well and who can safely pause therapy.

Across multiple cancer types treated with anti-PD-(L)1, limiting ICI duration to six months or less did not meaningfully worsen overall survival. Many patients achieved long treatment-free periods after shorter courses—an important signal that some can receive less therapy without losing benefit.

Blood-based proteomics further highlighted two proteins—ARG1 and ADGRG1—whose levels were associated with response to ICIs and with overall survival in advanced solid tumors. In a pilot lung-cancer screening cohort, participants with positive low-dose CT (LDCT) findings showed a distinct blood-protein signature, with 17 proteins differing from LDCT-negative participants. This points to a practical way to combine imaging with a simple blood test to enhance cancer screening.

Together, these results support a data-driven approach that integrates tissue immunology with circulating biomarkers. Such biomarker-guided care could personalize treatment, reduce overtreatment, and help health systems use resources more efficiently.