The crucial role of predicting brain metastases development in non-small cell lung cancer patients

A Comparison Between First-, Second- and Third-Generation Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in Patients with Non-Small-Cell Lung Cancer and Brain Metastases

Patients with non-small-cell lung cancer (NSCLC), harboring Epidermal Growth Factor Receptor (EGFR) mutations, are more susceptible to brain metastases (BM). Comparisons of the efficacy of different-generation EGFR-tyrosine kinase inhibitors (TKI) on BMs from NSCLC are currently limited. We identified studies comparing different EGFR-TKIs for NSCLC through Pubmed literature search and selected those with neurological outcome data. By two retrospective analyses, Erlotinib showed longer neurological time-to-progression (30 months vs. 15.8 months, P = 0.024) and reduced the risk of central nervous system (CNS) progression (Hazard Ratio (HR) 0.25; 95% CI, 0.08–0.81; P = 0.021) compared to Gefitinib. In a phase 2b randomized trial, 16% of patients with BMs had a similar Progression Free Survival (PFS) (HR 0.76, 95% CI 0.41–1.44) or Overall Survival (OS) (HR 1.16, 95% CI 0.61–2.21) with Afatinib versus Gefitinib; a lower risk of developing subsequent BMs with Afatinib than Gefitinib (HR 0.49; 95% CI 0.34–0.71; P < 0.001) was reported by a retrospective study. A randomized phase 3 trial proved that patients with BMs treated with Osimertinib had longer PFS (HR 0.47, 95% CI 0.30–0.74) and OS (HR 0.79, 95% CI 0.61–1.01) than with Gefitinib, and lower incidence of CNS progression (6% vs. 15%, respectively). Although there is limited evidence, differences in CNS activity may exist between EGFR-TKIs.

The effect of combining Endostar with radiotherapy on blood vessels, tumor-associated macrophages, and T cells in brain metastases of Lewis lung cancer

Background

Combining Endostar (ES) with radiotherapy (RT) has shown a promising therapeutic effect on non-small cell lung carcinoma with brain metastases (BMs) in clinical practice. However, the specific mechanism is not yet fully understood. The present study aimed to investigate the effects of ES on blood vessels, tumor-associated macrophages (TAMs), and T cells in a tumor microenvironment treated with RT.

Methods

BM models were established by stereotactic and intracarotid injection of luciferase-Lewis lung cancer (LLC) cells into female C57BL mice. The animals were randomly divided into 4 groups: normal saline (NS), ES, RT, and ES plus radiotherapy (ES + RT) groups. Tumor size was determined with the IVIS imaging system. Tumor specimens were stained with CD34 and α-SMA to investigate tumor vascular changes. The proportions of TAMs, CD4⁺ T cells, and CD8⁺ T cells in tumor tissues were determined by flow cytometry and immunofluorescence. The expressions of hypoxia-inducible factor 1α (HIF-1α) and CXCR4 were deduced using western blotting and immunohistochemistry (IHC).

Results

ES + RT significantly suppressed tumor growth compared to the other 3 groups. RT decreased M1 and increased M2 in microglial cells and bone marrow-derived macrophages (BMDMs) relative to NS, while ES had the opposite effect. The ratio of CD8⁺T/CD4⁺T was increased in the ES + RT group compared to the other 3 groups. Tumor vascular maturity (α-SMA⁺/CD34⁺) was increased while HIF-1α was significantly suppressed in the ES + RT group. CXCR4 expression, which is involved in TAM recruitment, increased following RT, whereas, ES attenuated its expression.

Conclusions

Our findings suggest that ES can promote the normalization of tumor blood vessels and increase the anti-tumor immune-related immune cells infiltrating the tumor following RT treatment.

The Promise of Digital Biopsy for the Prediction of Tumor Molecular Features and Clinical Outcomes Associated With Immunotherapy

Immunotherapy by immune checkpoint inhibitors has emerged as an effective treatment for a slight proportion of patients with aggressive tumors. Currently, some molecular determinants, such as the expression of the programmed cell death ligand-1 (PD-L1) or the tumor mutational burden (TMB) have been used in the clinical practice as predictive biomarkers, although they fail in consistency, applicability, or reliability to precisely identify the responding patients mainly because of their spatial intratumoral heterogeneity. Therefore, new biomarkers for early prediction of patient response to immunotherapy, that could integrate several approaches, are eagerly sought. Novel methods of quantitative image analysis (such as radiomics or pathomics) might offer a comprehensive approach providing spatial and temporal information from macroscopic imaging features potentially predictive of underlying molecular drivers, tumor-immune microenvironment, tumor-related prognosis, and clinical outcome (in terms of response or toxicity) following immunotherapy. Preliminary results from radiomics and pathomics analysis have demonstrated their ability to correlate image features with PD-L1 tumor expression, high CD3 cell infiltration or CD8 cell expression, or to produce an image signature concordant with gene expression. Furthermore, the predictive power of radiomics and pathomics can be improved by combining information from other modalities, such as blood values or molecular features, leading to increase the accuracy of these models. Thus, “digital biopsy,” which could be defined by non-invasive and non-consuming digital techniques provided by radiomics and pathomics, may have the potential to allow for personalized approach for cancer patients treated with immunotherapy.