Dynamic Exosome Analysis to Predict Response to the Combination of SABR and Immunotherapy in Oligoprogressive Disease

PURPOSE/OBJECTIVE(S)

Up to 80% of metastatic patients face resistance to immune checkpoint inhibitors (ICI). Combined SABR and ICI (I-SABR) can unleash antitumor immune cascades to overcome resistance and improve response with minimal toxicity. This synergy is particularly interesting in the oligoprogressive setting to extend the clinical benefit (CB) of ICI. However, there are no current biomarkers for patient selection. We hypothesize that differential expression of exosomal RNA in liquid biopsy may predict response to I-SABR.

MATERIALS/METHODS

Ongoing prospective multicenter study in two cohorts. Cohort A consists of metastatic patients in oligoprogression to ICI (1-5 extracranial sites) but maintaining the same ICI due to CB and who receive concomitant SABR (35 Gy in 5 fractions, fx) to oligoprogressive sites. Cohort B is a comparative group of oligometastatic patients receiving only SABR in ablative doses. Blood samples are extracted before SABR (T1), after the first (T2) and last (T3) fx, two months post-SABR (T4) and at further progression (TP). Response is evaluated by iRECIST and defined by the objective response rate (ORR) in all lesions (in and out-of-field)- complete and partial responses. For exosome analysis, we perform RNA isolation and small RNA sequencing from plasma. We use Cutadapt, Bowtie and featureCounts to quantify the number of reads of miRNA, small nuclear RNA (snRNA) and small nucleolar RNA (snoRNA). Pairwise differences in expression in responders and non-responders are examined by DESeq2 differential expression analysis. Differentially expressed transcripts are consulted in Ingenuity Pathway Analysis (IPA).

RESULTS

Of 22 patients recruited, we present preliminary results of the first 10 (8 from cohort A and 2 from B) that had undergone re-evaluation after SABR. Most frequent cancer types were lung (60%) and renal cell (20%). Seventy percent were polymetastatic (>5 lesions) and 90% had a single progressing site. Pembrolizumab (40%) and Nivolumab (30%) were the most frequent ICI. Most lesions for SABR were lung (45%). With a median follow-up of 7.1 months (95% CI, 3.7-10.6) ORR at two months was 60% (6 partial responses, 1 stable disease and 3 progressions). Median progression-free survival was 10.3 months (95% CI, 3.7-not reached) and median overall survival was not reached. Seven patients in cohort A were available for small RNA analysis. We identified 3 miRNA, 24 snRNA and 9 snoRNA that were significantly differentially expressed at T1. Hsa-miR-493, marker of tumor progression, was upregulated in non-responders. RN7SK inhibits LAS1L (a known inductor of metastasis in lung cancer) and was upregulated in responders. SNORD71, which is inhibited by ILF3 (promotor of progression), was also upregulated in responders.

CONCLUSION

I-SABR is an effective approach for extending CB of ICI in oligoprogressive patients. Exosomal RNA expression analysis in liquid biopsy is a novel and non-invasive technique that may predict response to this combination and aid in patient selection.

Abstract 1044: Cell-free DNA concentration as a prognostic biomarker in patients with non-small cell lung cancer under immunotherapy treatment

The irruption of the immunotherapy for the treatment of non-small cell lung cancer (NSCLC) based on Immune Checkpoint Inhibitors (ICI) PD-1 and PD-L1 inhibitors is considered a treatment revolution. However, only a small percentage of patients benefit with ICI treatment over the long term, and precise biomarkers that can recognize these individuals before or early during treatment have so far eluded. PD-L1 expression and tumor mutational burden (TMB) are the most well studied biomarkers for predicting response to PD- (L)1 blockade-based ICI prior to treatment. TMB is still being clinically assessed whereas PD-L1 has several drawbacks for prediction of persistent benefit. Our aim is to evaluate the basal state and dynamic changes of cell-free DNA (cfDNA) concentration to predict and monitor response in NSCLC patients starting ICI. A total of 248 cfDNA concentration measurements were performed from 87 NSCLC patients. The quantification was done before the start of the treatment, at the second ICI cycle, after 6 and 12 months in treatment, and at progression if it was within the first 12 months. Quality and quantity of the cfDNA was assessed using Qubit High Sensitivity and Bioanalyzer 2100. We first explored the association with response of the basal cell-free DNA concentration using Mann-Whitney-Wilcoxon test. The longitudinal analysis between different time points was tested with Wilcoxon signed-rank tests. Response was ascertained using RECIST parameters at 3, 6, and 12 months. We evaluated the utility of the cfDNA concentration as a prognostic factor using Mantel-Cox test. The response association results indicate that early and long-term response is associated with lower levels of basal cfDNA (p<0.002, 3 months; p<0.001, 6 months; p<0.05, 12 months). The longitudinal analysis could also detect a decrease in cfDNA from the second cycle to the month 6 of treatment in responders (p<0.05), and an increase in non-responders (p<0.05). To identify a prognostic concentration threshold, statistical stratification of cfDNA levels based on the selected maximum rank method of cfDNA levels was used to group them into low and high concentration. Patients with high basal cfDNA concentrations showed both worse FPS (log-rank 3.4x10-03, Medians: Low 12.57 [8.36 - 18.46] High 5.50 [3.03 - 10.06]) and OS (log-rank 3.2x10-05, Medians: Low 21.26 [15.33 - 33.96] High 5.45 [3.10 - 15.66]). With these results, we provide proof-of-principle that specifically detecting tumor cfDNA by PCR or NGS methods would not be necessary to predict the long-term clinical benefit to ICI in NSCLC patients. Moreover, concentration cut-offs can be defined to categorize the patients in potential responders and non-responders before the start of the treatment. This would constitute a cost-effective and easily implementable prognostic tool that could be particularly useful for avoiding loss of treatment windows of opportunities.

Citation Format: Isabel Barragan, Elisabeth Perez-Ruiz, Juan Luis Onieva, Maria Garrido-Ramos, Beatriz Martinez-Galvez, Jaime Dubbelman, Emilio Alba, Juan Zafra, Manuel Cobo, Javier Oliver, Antonio Rueda-Dominguez. Cell-free DNA concentration as a prognostic biomarker in patients with non-small cell lung cancer under immunotherapy treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1044.