Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy.

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.

CEA-CD3 bispecific antibody cibisatamab with or without atezolizumab in patients with CEA-positive solid tumours: results of two multi-institutional Phase 1 trials.

Cibisatamab is a bispecific antibody-based construct targeting carcinoembryonic antigen (CEA) on tumour cells and CD3 epsilon chain as a T-cell engager. Here we evaluated cibisatamab for advanced CEA-positive solid tumours in two open-label Phase 1 dose-escalation and -expansion studies: as a single agent with or without obinutuzumab in S1 (NCT02324257) and with atezolizumab in S2 (NCT02650713). Primary endpoints were safety, dose finding, and pharmacokinetics in S1; safety and dose finding in S2. Secondary endpoints were anti-tumour activity (including overall response rate, ORR) and pharmacodynamics in S1; anti-tumour activity, pharmacodynamics and pharmacokinetics in S2. S1 and S2 enrolled a total of 149 and 228 patients, respectively. Grade ≥3 cibisatamab-related adverse events occurred in 36% of S1 and 49% of S2 patients. The ORR was 4% in S1 and 7% in S2. In S2, patients with microsatellite stable colorectal carcinoma (MSS-CRC) given flat doses of cibisatamab and atezolizumab demonstrated an ORR of 14%. In S1 and S2, 40% and 52% of patients, respectively, developed persistent anti-drug antibodies (ADAs). ADA appearance could be mitigated by obinutuzumab-pretreatment, with 8% of patients having persistent ADAs. Overall, cibisatamab warrants further exploration in immunotherapy combination strategies for MSS-CRC.

Immune heterogeneity in small-cell lung cancer and vulnerability to immune checkpoint blockade.

Atezolizumab (anti-PD-L1), combined with carboplatin and etoposide (CE), is now a standard of care for extensive-stage small-cell lung cancer (ES-SCLC). A clearer understanding of therapeutically relevant SCLC subsets could identify rational combination strategies and improve outcomes. We conduct transcriptomic analyses and non-negative matrix factorization on 271 pre-treatment patient tumor samples from IMpower133 and identify four subsets with general concordance to previously reported SCLC subtypes (SCLC-A, -N, -P, and -I). Deeper investigation into the immune heterogeneity uncovers two subsets with differing neuroendocrine (NE) versus non-neuroendocrine (non-NE) phenotypes, demonstrating immune cell infiltration hallmarks. The NE tumors with low tumor-associated macrophage (TAM) but high T-effector signals demonstrate longer overall survival with PD-L1 blockade and CE versus CE alone than non-NE tumors with high TAM and high T-effector signal. Our study offers a clinically relevant approach to discriminate SCLC patients likely benefitting most from immunotherapies and highlights the complex mechanisms underlying immunotherapy responses.