Dynamic evaluation of blood immune cells predictive of response to immune checkpoint inhibitors in NSCLC by multicolor spectrum flow cytometry.

Introduction: Immune checkpoint inhibitors (ICIs) only benefit a subset of cancer patients, underlining the need for predictive biomarkers for patient selection. Given the limitations of tumor tissue availability, flow cytometry of peripheral blood mononuclear cells (PBMCs) is considered a noninvasive method for immune monitoring. This study explores the use of spectrum flow cytometry, which allows a more comprehensive analysis of a greater number of markers using fewer immune cells, to identify potential blood immune biomarkers and monitor ICI treatment in non-small-cell lung cancer (NSCLC) patients. Methods: PBMCs were collected from 14 non-small-cell lung cancer (NSCLC) patients before and after ICI treatment and 4 healthy human donors. Using spectrum flow cytometry, 24 immune cell markers were simultaneously monitored using only 1 million PBMCs. The results were also compared with those from clinical flow cytometry and bulk RNA sequencing analysis. Results: Our findings showed that the measurement of CD4+ and CD8+ T cells by spectrum flow cytometry matched well with those by clinical flow cytometry (Pearson R ranging from 0.75 to 0.95) and bulk RNA sequencing analysis (R=0.80, P=1.3 x 10-4). A lower frequency of CD4+ central memory cells before treatment was associated with a longer median progression-free survival (PFS) [Not reached (NR) vs. 5 months; hazard ratio (HR)=8.1, 95% confidence interval (CI) 1.5-42, P=0.01]. A higher frequency of CD4-CD8- double-negative (DN) T cells was associated with a longer PFS (NR vs. 4.45 months; HR=11.1, 95% CI 2.2-55.0, P=0.003). ICIs significantly changed the frequency of cytotoxic CD8+PD1+ T cells, DN T cells, CD16+CD56dim and CD16+CD56- natural killer (NK) cells, and CD14+HLDRhigh and CD11c+HLADR + monocytes. Of these immune cell subtypes, an increase in the frequency of CD16+CD56dim NK cells and CD14+HLADRhigh monocytes after treatment compared to before treatment were associated with a longer PFS (NR vs. 5 months, HR=5.4, 95% CI 1.1-25.7, P=0.03; 7.8 vs. 3.8 months, HR=5.7, 95% CI 169 1.0-31.7, P=0.04), respectively. Conclusion: Our preliminary findings suggest that the use of multicolor spectrum flow cytometry helps identify potential blood immune biomarkers for ICI treatment, which warrants further validation.

High integrin α3 expression is associated with poor prognosis in patients with non-small cell lung cancer.

BACKGROUND: We previously showed that α3ß1 integrin is a novel cancer biomarker and drug target in non-small cell lung cancer (NSCLC). This study characterized the integrin α3 (ITGA3) expression on patient specimens. METHODS: Tissue microarrays (TMAs) were prepared from archival tissue blocks containing 161 patients, which included 91 adenocarcinoma (LUAD), 46 squamous carcinomas (LUSC), and 24 other histology types. TMA sections were stained and scored for ITGA3 expression by immunohistochemistry (IHC). Kaplan-Meier curves and log-rank tests were used to compare overall survival (OS) between IHC score groups. Propensity-score-weighted Kaplan-Meier curves and weighted Cox models were used to adjust for covariate imbalance between IHC score groups. Logistic regression was used to determine ITGA3 transcriptome expression in NSCLC in The Cancer Genome Atlas (TCGA). RESULTS: ITGA3 IHC expression (1+ to 3+) was detected in 107/161 (66.5%) of the NSCLC samples, and was associated with poor prognosis at the edge of significance (HR =1.30, 95% CI: 0.99-1.71, P=0.056), but significant (P<0.05) in subgroups of female patients, smokers and tumors with grade I and II differentiation using propensity-score-weighted survival analysis after adjusting for confounders. Multivariate survival analysis based on multiple imputation for missing variables showed ITGA3 expression, old age and metastasis were associated with poor prognosis (P<0.05). ITGA3 IHC expression was associated with poor prognosis in LUSC (HR =2.27, P<0.05) but not in LUAD (HR =1.49, P=0.16). Median ITGA3 expression was significantly higher in LUAD than LUSC (P<0.0001) in the TCGA transcriptome datasets. Using a higher cutoff than LUSC (70.6 vs. 19.5 FPKM), high ITGA3 RNA expression was also associated with poor prognosis in LUAD (P=0.023). ITGA3 interacted with key genes regulating epithelial to mesenchymal transition, angiogenesis, invasion and metastasis in both LUAD and LUSC. CONCLUSIONS: High ITGA3 IHC expression was associated with poor prognosis in NSCLC patients. Further study is warranted for targeting α3ß1 integrin in NSCLC.