Small cell lung cancer; recent advances of its biology and therapeutic perspective

TREM1/DAP12 based novel multiple chain CAR-T cells targeting DLL3 show robust anti-tumour efficacy for small cell lung cancer

Small cell lung cancer (SCLC), recognized as the most aggressive subtype of lung cancer, presents an extremely poor prognosis. Currently, patients with small cell lung cancer face a significant dearth of effective alternative treatment options once they experience recurrence and progression after first-line therapy. Despite the promising efficacy of immunotherapy, particularly immune checkpoint inhibitors in non-small cell lung cancer (NSCLC) and various other tumours, its impact on significantly enhancing the prognosis of SCLC patients remains elusive. DLL3 has emerged as a compelling target for targeted therapy in SCLC due to its high expression on the membranes of SCLC and other neuroendocrine carcinoma cells, with minimal to no expression in normal cells. Our previous work led to the development of a novel multiple chain chimeric antigen receptor (CAR) leveraging the TREM1 receptor and DAP12, which efficiently activated T cells and conferred potent cell cytotoxicity. In this study, we have developed a DLL3-TREM1/DAP12 CAR-T (DLL3-DT CAR-T) therapy, demonstrating comparable anti-tumour efficacy against SCLC cells in vitro. In murine xenograft and patient-derived xenograft models, DLL3-DT CAR-T cells exhibited a more robust tumour eradication efficiency than second-generation DLL3-BBZ CAR-T cells. Furthermore, we observed elevated memory phenotypes, induced durable responses, and activation under antigen-presenting cells in DLL3-DT CAR-T cells. Collectively, these findings suggest that DLL3-DT CAR-T cells may offer a novel and potentially effective therapeutic strategy for treating DLL3-expressing SCLC and other solid tumours.

A novel transformer-based aggregation model for predicting gene mutations in lung adenocarcinoma

In recent years, predicting gene mutations on whole slide imaging (WSI) has gained prominence. The primary challenge is extracting global information and achieving unbiased semantic aggregation. To address this challenge, we propose a novel Transformer-based aggregation model, employing a self-learning weight aggregation mechanism to mitigate semantic bias caused by the abundance of features in WSI. Additionally, we adopt a random patch training method, which enhances model learning richness by randomly extracting feature vectors from WSI, thus addressing the issue of limited data. To demonstrate the model's effectiveness in predicting gene mutations, we leverage the lung adenocarcinoma dataset from Shandong Provincial Hospital for prior knowledge learning. Subsequently, we assess TP53, CSMD3, LRP1B, and TTN gene mutations using lung adenocarcinoma tissue pathology images and clinical data from The Cancer Genome Atlas (TCGA). The results indicate a notable increase in the AUC (Area Under the ROC Curve) value, averaging 4%, attesting to the model's performance improvement. Our research offers an efficient model to explore the correlation between pathological image features and molecular characteristics in lung adenocarcinoma patients. This model introduces a novel approach to clinical genetic testing, expected to enhance the efficiency of identifying molecular features and genetic testing in lung adenocarcinoma patients, ultimately providing more accurate and reliable results for related studies.

Enhancement of the Tumor Suppression Effect of High-dose Radiation by Low-dose Pre-radiation Through Inhibition of DNA Damage Repair and Increased Pyroptosis

Radiation therapy has been a critical and effective treatment for cancer. However, not all cells are destroyed by radiation due to the presence of tumor cell radioresistance. In the current study, we investigated the effect of low-dose radiation (LDR) on the tumor suppressive effect of high-dose radiation (HDR) and its mechanism from the perspective of tumor cell death mode and DNA damage repair, aiming to provide a foundation for improving the efficacy of clinical tumor radiotherapy. We found that LDR pre-irradiation strengthened the HDR-inhibited A549 cell proliferation, HDR-induced apoptosis, and G2 phase cell cycle arrest under co-culture conditions. RNA-sequencing showed that differentially expressed genes after irradiation contained pyroptosis-related genes and DNA damage repair related genes. By detecting pyroptosis-related proteins, we found that LDR could enhance HDR-induced pyroptosis. Furthermore, under co-culture conditions, LDR pre-irradiation enhances the HDR-induced DNA damage and further suppresses the DNA damage-repairing process, which eventually leads to cell death. Lastly, we established a tumor-bearing mouse model and further demonstrated that LDR local pre-irradiation could enhance the cancer suppressive effect of HDR. To summarize, our study proved that LDR pre-irradiation enhances the tumor-killing function of HDR when cancer cells and immune cells were coexisting.

DNA topoisomerase II inhibition potentiates osimertinib's therapeutic efficacy in EGFR-mutant non-small cell lung cancer models

Development of effective strategies to manage the inevitable acquired resistance to osimertinib, a third-generation EGFR inhibitor for the treatment of EGFR-mutant (EGFRm) non-small cell lung cancer (NSCLC), is urgently needed. This study reports that DNA topoisomerase II (Topo II) inhibitors, doxorubicin and etoposide, synergistically decreased cell survival, with enhanced induction of DNA damage and apoptosis in osimertinib-resistant cells; suppressed the growth of osimertinib-resistant tumors; and delayed the emergence of osimertinib-acquired resistance. Mechanistically, osimertinib decreased Topo IIα levels in EGFRm NSCLC cells by facilitating FBXW7-mediated proteasomal degradation, resulting in induction of DNA damage; these effects were lost in osimertinib-resistant cell lines that possess elevated levels of Topo IIα. Increased Topo IIα levels were also detected in the majority of tissue samples from patients with NSCLC after relapse from EGFR tyrosine kinase inhibitor treatment. Enforced expression of an ectopic TOP2A gene in sensitive EGFRm NSCLC cells conferred resistance to osimertinib, whereas knockdown of TOP2A in osimertinib-resistant cell lines restored their susceptibility to osimertinib-induced DNA damage and apoptosis. Together, these results reveal an essential role of Topo IIα inhibition in mediating the therapeutic efficacy of osimertinib against EGFRm NSCLC, providing scientific rationale for targeting Topo II to manage acquired resistance to osimertinib.

Identification of Transferrin Receptor 1 (TfR1) Overexpressed in Lung Cancer Cells, and Internalization of Magnetic Au-CoFe2O4 Core-Shell Nanoparticles Functionalized with Its Ligand in a Cellular Model of Small Cell Lung Cancer (SCLC)

Lung cancer is, currently, one of the main malignancies causing deaths worldwide. To date, early prognostic and diagnostic markers for small cell lung cancer (SCLC) have not been systematically and clearly identified, so most patients receive standard treatment. In the present study, we combine quantitative proteomics studies and the use of magnetic core-shell nanoparticles (mCSNP’s), first to identify a marker for lung cancer, and second to functionalize the nanoparticles and their possible application for early and timely diagnosis of this and other types of cancer. In the present study, we used label-free mass spectrometry in combination with an ion-mobility approach to identify 220 proteins with increased abundance in small cell lung cancer (SCLC) cell lines. Our attention was focused on cell receptors for their potential application as mCSNP’s targets; in this work, we report the overexpression of Transferrin Receptor (TfR1) protein, also known as Cluster of Differentiation 71 (CD71) up to a 30-fold increase with respect to the control cell. The kinetics of endocytosis, evaluated by a flow cytometry methodology based on fluorescence quantification, demonstrated that receptors were properly activated with the transferrin supported on the magnetic core-shell nanoparticles. Our results are important in obtaining essential information for monitoring the disease and/or choosing better treatments, and this finding will pave the way for future synthesis of nanoparticles including chemotherapeutic drugs for lung cancer treatments.