An international phase II trial and immune profiling of SBRT and atezolizumab in advanced pretreated colorectal cancer

Abstract

Background: Immuno-radiotherapy may improve outcomes for patients with advanced solid tumors, although optimized combination modalities remain unclear. Here, we report the colorectal (CRC) cohort analysis from the SABR-PDL1 trial that evaluated the PD-L1 inhibitor atezolizumab in combination with stereotactic body radiation therapy (SBRT) in advanced cancer patients.

Methods: Eligible patients received atezolizumab 1200 mg every 3 weeks until progression or unmanageable toxicity, together with ablative SBRT delivered concurrently with the 2nd cycle (recommended dose of 45 Gy in 3 fractions, adapted upon normal tissue tolerance constraint). SBRT was delivered to at least one tumor site, with at least one additional measurable lesion being kept from the radiation field. The primary efficacy endpoint was one-year progression-free survival (PFS) rate from the start of atezolizumab. Sequential tumor biopsies were collected for deep multi-feature immune profiling.

Results: Sixty pretreated (median of 2 prior lines) advanced CRC patients (38 men [63%]; median age, 59 years [range, 20-81 years]; 77% with liver metastases) were enrolled in five centers (France: n = 4, Spain: n = 1) from 11/2016 to 04/2019. All but one (98%) received atezolizumab and 54/60 (90%) received SBRT. The most frequently irradiated site was lung (n = 30/54; 56.3%). Treatment-related G3 (no G4-5) toxicity was observed in 3 (5%) patients. Median OS and PFS were respectively 8.4 [95%CI:5.9-11.6] and 1.4 months [95%CI:1.2-2.6], including five (9%) patients with PFS > 1 year (median time to progression: 19.2 months, including 2/5 MMR-proficient). Best overall responses consisted of stable disease (n = 38; 64%), partial (n = 3; 5%) and complete response (n = 1; 2%). Immune-centric multiplex IHC and RNAseq showed that SBRT redirected immune cells towards tumor lesions, even in the case of radio-induced lymphopenia. Baseline tumor PD-L1 and IRF1 nuclear expression (both in CD3 + T cells and in CD68 + cells) were higher in responding patients. Upregulation of genes that encode for proteins known to increase T and B cell trafficking to tumors (CCL19, CXCL9), migration (MACF1) and tumor cell killing (GZMB) correlated with responses.

Conclusions: This study provides new data on the feasibility, efficacy, and immune context of tumors that may help identifying advanced CRC patients most likely to respond to immuno-radiotherapy.

Trial registration: EudraCT N°: 2015-005464-42; Clinicaltrial.gov number: NCT02992912.

Fig. 1

CONSORT Diagram

Fig. 2

Clinical outcomes. A-B Kaplan Meyer describing progression-free (A) and overall survival (B) in the intention-to-treat population. C Best change from baseline in size of target lesions in evaluable patients

Fig. 3

Biopsies immune profiles and lymphocyte count. A-B (Top panels). Absolute lymphocyte blood counts from baseline evaluation to the fifth cycle of atezolizumab (D84) in patients who experienced stable disease, partial response or complete response as best tumor response according to RECIST 1.1 (SD/PR/CR) (A) and in patients who rapidly progressed (PD) (B). Red arrows indicate SABR delivery during the course of treatment. The three periods of tumor biopsies are also indicated. Yellow and red stars refer respectively to MSI-high patients and elite responders (PFS > 1 year). (Bottom panels). Immunograms detailing the immune composition of the immune infiltrate as assessed by multiplex IHC in FFPE tumor biopsy samples collected at the indicated timepoints in patients with SD/PR/CR (A) an in patients who progressed (B). Each absolute cell density is ranged from 0 to 10.000 cells/mm2. C-F Multiplex IHC. Images at 20X of two liver samples with a high level (C) and a low level (D) of immune infiltration; (E); Comparison of tumor immune infiltration according to disease control rate (defined as lack of disease progression) in baseline biopsies by different IHC markers; (F) Scatter dot plot showing the sum of densities of immune infiltrating cells assessed by multiplex IHC in tumor samples and calcutated as follows: (macrophages density + CD3 + cells density + CD68 + density + CD20 + density). Mean with SD are represented. ns > 0.05; 0.05 ≤ * < 0.01; 0.01 ≤ ** < 0.001; 0.001 ≤ *** < 0.0001; 0.0001 ≤ ****. HES: Haematoxylin–Eosin-Saffran; d: DAB brown; p: purple; y: yellow; g: green

Fig. 4

RNAseq immune cell differences in patient biopsies. A-B CIBESORTx characterization of the immune infiltrate obtained from RNAseq analyses performed on fresh frozen tumor samples in patients with stable disease, partial or complete response (SD/PR/CR) (A) and in patients who progressed (PD) (B), according to the treatment timepoint (baseline, week 3 and week 7). For each analyzed tumor sample, a bar chart depicts the absolute score of each immune subpopulation and is accompagned with a circular representation that indicates the relative fraction of granulocytes, monocytes/macrophages and lymphocytes within the sample, as indicated. Yellow and red stars refer respectivelly to MSI-high patients and elite responders (> 1 year). C-E. Scatter dot plots comparating the total CIBESORTx score found in patients with SD/PR/CR versus patients who progressed in tumor samples collected at baseline (C), at week 3 (D) and at week 7 (E). Mean with SD are represented. ns > 0.05; 0.01 ≤ ** < 0.001

Fig. 5

Coding gene RNA expression. A Heatmap showing an unsupervised hierarchical clustering (Euclidean distances) of the differences in immune gene expressions between before and after (week 3) treatment with atezolizumab. The clustering was made on log2-transformed TPM values of 536 immune-related genes extracted from the LM22 dataset after pre-processing, in patients for whom both baseline and week 3 RNAseq data were available. Pink refers to higher expression at baseline (reduction of expression at week 3) and green refers to lower expression at baseline (increased expression at week 3) B-C. Differential expression analyses of top-differentiated genes among the 536 immune-related genes when comparing only elite responders (> 1 year) with the others (B) and patients who rapidly progressed with the others (C). CCL19, BHLHE41, CXCL9, MS4A6A, GZMB, DGKA, BIRC3, PDK1, MACF1 and SLAMF1 expressions are commonly found of good prognosis