Precision immunointerception of EGFR-driven tumorigenesis for lung cancer prevention

Shared neoantigens for cancer immunotherapy

Exploration of neoantigens holds the potential to be productive in immuno-oncotherapy. Among tumor-specific antigens, neoantigens result from genetic instability that gives rise to non-synonymous somatic mutations, highly specific to tumor cells. In addition to point mutations, gene rearrangements, indels leading to frameshifts, chromosomal translocations or inversions that may lead to fusion proteins, alternative mRNA splicing, and integration of genetic material of oncogenic viruses into the host genome provide consistent sources of neoantigens that are absent in healthy tissues. Out of these alterations, 2%-3% may generate T cell neoepitopes, possibly detectable by TCRs. Neoantigens are absent in healthy tissues and are thus at low risk of triggering autoimmunity. In addition, the host lymphocytes have not been rendered tolerant toward them and it is possible to induce immune responses against them. Here, we overview the two categories of neoantigens, i.e., private and shared, and their use in immuno-oncotherapy in selected pre-clinical and clinical studies. The vast majority of commonly occurring tumor-specific mutations are cancer causing and are permanently expressed by all malignant tumor cells, preventing the latter from escaping vaccine-induced anti-neoantigen immunity. The use of public neoantigens combined with efficient vaccine platforms can provide non-personalized "off-the-shelf" therapeutic vaccine candidates for broad-spectrum immunotherapy purposes.

PD-L2 drives resistance to EGFR-TKIs: dynamic changes of the tumor immune environment and targeted therapy

There is a lack of effective treatments to overcome resistance to EGFR-TKIs in EGFR mutant tumors. A deeper understanding of resistance mechanisms can provide insights into reducing or eliminating resistance, and can potentially deliver targeted treatment measures to overcome resistance. Here, we identified that the dynamic changes of the tumor immune environment were important extrinsic factors driving tumor resistance to EGFR-TKIs in EGFR mutant cell lines and syngeneic tumor-bearing mice. Our results demonstrate that the acquired resistance to EGFR-TKIs is accompanied by aberrant expression of PD-L2, leading a dynamic shift from an initially favorable tumor immune environment to an immunosuppressive phenotype. PD-L2 expression significantly affected EGFR mutant cell apoptosis that depended on the proportion and function of CD8+ T cells in the tumor immune environment. Combined with single-cell sequencing and experimental results, we demonstrated that PD-L2 specifically inhibited the proliferation of CD8+ T cells and the secretion of granzyme B and perforin, leading to reduced apoptosis mediated by CD8+ T cells and enhanced immune escape of tumor cells, which drives EGFR-TKIs resistance. Importantly, we have identified a potent natural small-molecule inhibitor of PD-L2, zinc undecylenate. In vitro, it selectively and potently blocks the PD-L2/PD-1 interaction. In vivo, it abolishes the suppressive effect of the PD-L2-overexpressing tumor immune microenvironment by blocking PD-L2/PD-1 signaling. Moreover, the combination of zinc undecylenate and EGFR-TKIs can synergistically reverse tumor resistance, which is dependent on CD8+ T cells mediating apoptosis. Our study uncovers the PD-L2/PD-1 signaling pathway as a driving factor to mediate EGFR-TKIs resistance, and identifies a new naturally-derived agent to reverse EGFR-TKIs resistance.

AutoPepVax, a Novel Machine-Learning-Based Program for Vaccine Design: Application to a Pan-Cancer Vaccine Targeting EGFR Missense Mutations

The current epitope selection methods for peptide vaccines often rely on epitope binding affinity predictions, prompting the need for the development of more sophisticated in silico methods to determine immunologically relevant epitopes. Here, we developed AutoPepVax to expedite and improve the in silico epitope selection for peptide vaccine design. AutoPepVax is a novel program that automatically identifies non-toxic and non-allergenic epitopes capable of inducing tumor-infiltrating lymphocytes by considering various epitope characteristics. AutoPepVax employs random forest classification and linear regression machine-learning-based models, which are trained with datasets derived from tumor samples. AutoPepVax, along with documentation on how to run the program, is freely available on GitHub. We used AutoPepVax to design a pan-cancer peptide vaccine targeting epidermal growth factor receptor (EGFR) missense mutations commonly found in lung adenocarcinoma (LUAD), colorectal adenocarcinoma (CRAD), glioblastoma multiforme (GBM), and head and neck squamous cell carcinoma (HNSCC). These mutations have been previously targeted in clinical trials for EGFR-specific peptide vaccines in GBM and LUAD, and they show promise but lack demonstrated clinical efficacy. Using AutoPepVax, our analysis of 96 EGFR mutations identified 368 potential MHC-I-restricted epitope-HLA pairs from 49,113 candidates and 430 potential MHC-II-restricted pairs from 168,669 candidates. Notably, 19 mutations presented viable epitopes for MHC I and II restrictions. To evaluate the potential impact of a pan-cancer vaccine composed of these epitopes, we used our program, PCOptim, to curate a minimal list of epitopes with optimal population coverage. The world population coverage of our list ranged from 81.8% to 98.5% for MHC Class II and Class I epitopes, respectively. From our list of epitopes, we constructed 3D epitope-MHC models for six MHC-I-restricted and four MHC-II-restricted epitopes, demonstrating their epitope binding potential and interaction with T-cell receptors. AutoPepVax's comprehensive approach to in silico epitope selection addresses vaccine safety, efficacy, and broad applicability. Future studies aim to validate the AutoPepVax-designed vaccines with murine tumor models that harbor the studied mutations.

DCLK1 Drives EGFR-TKI-Acquired Resistance in Lung Adenocarcinoma by Remodeling the Epithelial-Mesenchymal Transition Status

OBJECTIVE

Epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) is a first-line treatment for lung adenocarcinoma with EGFR-sensitive mutations, but acquired resistance to EGFR-TKIs remains a problem in clinical practice. The development of epithelial-mesenchymal transition (EMT) is a critical mechanism that induces acquired resistance to TKIs. Reversing acquired resistance to EGFR-TKIs through targeting the key molecules driving EMT provides an alternative choice for patients. We, therefore, aimed to explore the role of doublecortin-like kinase 1 (DCLK1) as an EMT driver gene in the acquired resistance of lung adenocarcinoma to EGFR-TKIs.

METHODS

The IC₅₀ of Gefitinib or Osimertinib in PC9/HCC827 cells was measured using a cell counting kit-8 (CCK8) assay. The expression levels of EMT-related genes in PC9 and HCC827 cells were detected using RT-PCR and Western blot. Cell migration and invasion abilities were assessed via a transwell assay. For the in vivo experiments, PC9 cells were subcutaneously injected into BALB/c nude mice to form tumors. Upon harvesting, tumor tissues were retained for RT-PCR, Western blot, and polychromatic fluorescence staining to detect biomarker changes in the EMT process.

RESULTS

Gefitinib-resistant PC9 (PC9/GR) and Osimertinib-resistant HCC827 (HCC827/OR) cells showed remarkable activation of EMT and enhanced migration and invasion abilities compared to TKI-sensitive cells. In addition, DCLK1 expression was markedly increased in EGFR-TKI-resistant lung adenocarcinoma cells. The targeted knockout of DCLK1 effectively reversed the EMT phenotype in TKI-resistant cells and improved EGFR-TKI sensitivity, which was further validated by the in vivo experiments.

CONCLUSIONS

DCLK1 facilitates acquired resistance to EGFR-TKI in lung adenocarcinoma by inducting EMT and accelerating the migration and invasion abilities of TKI-resistant cells.