Figure 7.

Dynamic profiling of immune features to predict response to immunotherapy

(A) Schematic of sample collection for lung cancer patients with anti-PD-1 therapy alone or chemotherapy and anti-PD-1 combination therapy.

(B) IL expression difference (IL_Δ) at cycle 2 of anti-PD-1 therapy is significantly higher in responders (n = 11) than non-responders (n = 11). p value was determined by paired Mann-Whitney-Wilcoxon test. The boxes indicate the median ±1 quartile, with the whiskers extending from the hinge to the smallest or largest value within 1.5× IQR from the box boundaries.

(C–H) Immune activation (IS_Δ) can accurately predict the patient response to anti-PD-1 therapy in patient cohort 1 (C–E) and cohort 2 (F–H). (C and F) Patients with immune activation (IS_Δ > 0) after ICB are more likely to respond to anti-PD-1 treatment. p value was determined by Fisher's test. (D and G) Patients with immune activation (IS_Δ > 0) demonstrate significantly better PFS. p value was determined by log rank test. (E and H) Tumor size decreases significantly in patients with immune activation (IS_Δ > 0) based on CT image.

(I–N) Schematic of immune features in patients (I and J) with benefit or (K and L) without benefit from ICB treatment at (I and K) pre-treatment and (J and L) on-treatment. (M) The activation of immune checkpoints and immune cell abundance in tumor microenvironment can predict immunotherapy benefit after 1–4 weeks of ICB therapy. (N) The activation of ILs in patient plasma at cycle 2 can predict immune benefit of ICB therapy (4–6 weeks).