Translational lung cancer research最新文献

Lung cancer is a malignant tumor with high incidence and mortality rates in both men and women worldwide. Although anticancer drugs are prescribed to treat lung cancer patients, individual responses to these drugs vary, making it crucial to identify the most suitable treatment for each patient. Therefore, it is necessary to develop an anticancer drug efficacy prediction model that can analyze drug efficacy before patient treatment and establish personalized treatment strategies. Unlike two-dimensional (2D) cultured lung cancer cells, lung cancer organoid (LCO) models have a three-dimensional (3D) structure that effectively mimics the characteristics and heterogeneity of lung cancer cells. Lung cancer patient-derived organoids (PDOs) also have the advantage of recapitulating histological and genetic characteristics similar to those of patient tissues under in vitro conditions. Due to these advantages, LCO models are utilized in various fields, including cancer research, and precision medicine, and are especially employed in various new drug development processes, such as targeted therapies and immunotherapy. LCO models demonstrate potential applications in precision medicine and new drug development research. This review discusses the various methods for implementing LCO models, LCO-based anticancer drug efficacy analysis models, and new trends in lung cancer-targeted drug development.

Background: Osimertinib, a third-generation tyrosine kinase inhibitor (TKI), has been authorized for use in patients with epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC). This study aimed to evaluate the effectiveness and safety of neoadjuvant osimertinib in individuals with resectable locally advanced NSCLC harboring EGFR mutation.

Methods: Ten centers located in mainland China took part in a single-arm, real-world, multicenter retrospective study (registration number: ChiCTR2100049954). Enrollment included individuals with lung adenocarcinoma who had EGFR mutations. Following the administration of osimertinib, the patients underwent a surgical procedure for resection. The main endpoint was the objective response rate (ORR). The subsequent endpoint analyzed was the joint assessment of overall survival (OS) and disease-free survival (DFS).

Results: From July 31, 2018 to April 28, 2023, a total of 38 individuals were involved and received neoadjuvant osimertinib treatment. The ORR was 60.5% (23/38). Thirty-eight patients underwent surgery, and 36 (94.7%) underwent successful R0 resection. Out of 38 patients, sixteen (42.1%) experienced adverse events (AEs) due to treatment in the neoadjuvant phase, with none of them reaching grade 3. Skin irritation [14 (36.8%)], stomach upset [5 (13.2%)], mouth sores [1 (2.6%)] and increased liver enzyme levels [1 (2.6%)] were the common AEs of treatment. The follow-up period lasted an average of 24.9 months. The 1-year OS rate is 94.2%, while the 2-year OS rate is 89.2%. The 1-year DFS rate is 87.9%, and the 2-year DFS rate remains at 87.9%.

Conclusions: In the actual clinical setting, osimertinib displays encouraging possibilities as a neoadjuvant therapy for individuals with operable EGFR-mutated NSCLC, exhibiting adequate efficacy and an acceptable safety record. The phase III clinical trial of NeoADAURA is expected to provide further efficacy and safety results.

Background: Sublobar resection is suitable for peripheral stage I lung adenocarcinoma (LUAD). However, if tumor spread through air spaces (STAS) present, the lobectomy will be considered for a survival benefit. Therefore, STAS status guide peripheral stage I LUAD surgical approach. This study aimed to identify radiological features associated with STAS in peripheral stage I LUAD and to develop a predictive machine learning (ML) model using radiomics to improve surgical decision-making for thoracic surgeons.

Methods: We conducted a retrospective analysis of patients who underwent surgical treatment for lung tumors from January 2022 to December 2023, focusing on clinical peripheral stage I LUAD. High-resolution computed tomography (CT) scans were used to extract 1,581 radiomics features. Least absolute shrinkage and selection operator (LASSO) regression was applied to select the most relevant features for predicting STAS, reducing model overfitting and enhancing predictability. Ten ML algorithms were evaluated using performance metrics such as area under the receiver operating characteristic curve (AUROC), accuracy, recall, F1-score, and Matthews Correlation Coefficient (MCC) after a 10-fold cross-validation process. SHapley Additive exPlanations (SHAP) values were calculated to provide interpretability and illustrate the contribution of individual features to the model's predictions. Additionally, a user-friendly web application was developed to enable clinicians to use these predictive models in real-time for assessing the risk of STAS.

Results: The study identified significant associations between STAS and radiological features, including the longest diameter, consolidation-to-tumor ratio (CTR), and the presence of spiculation. The Random Forest (RF) model for 3-mm peritumoral extensions demonstrated strong predictive performance, with a Recall_Mean of 0.717, Accuracy_Mean of 0.891, F1-Score_Mean of 0.758, MCC_Mean of 0.708, and an AUROC_Mean of 0.944. SHAP analyses highlighted the influential radiomics features, enhancing our understanding of the model's decision-making process.

Conclusions: The RF model, employing specific intratumoral and 3-mm peritumoral radiomics features, was highly effective in predicting STAS in peripheral stage I LUAD. This model is recommended for clinical use to optimize surgical strategies for LUAD patients, supported by a real-time web application for STAS risk assessment.

Background: Oligoprogression (OP) is common in patients with metastatic non-small cell lung cancer (mNSCLC) treated with immune checkpoint inhibitors (ICIs). This study aims to assess the benefit and the safety profile of ablative radiotherapy (RT) for OP in mNSCLC treated with pembrolizumab in first-line setting.

Methods: We retrospectively analyzed records of all consecutive mNSCLC patients who underwent treatment with pembrolizumab (+/- chemotherapy) in first-line setting and developed an OP treated with ablative RT while continuing pembrolizumab, in a French Hospital from 2019 to 2022. Primary endpoint was time to next systemic treatment (TTNT). Secondary endpoints included progression-free survival (PFS), overall survival (OS), objective response rate (ORR), and safety profile. Furthermore, we investigated features associated with clinical outcomes.

Results: Thirty-six patients were included and 47 OPs were reported (27 patients experienced one OP, 7 two OP, and 2 three OP). The median TTNT (mTTNT) after the first OP was 19.6 months [95% confidence interval (CI): 12.4-not reached (NR)]. The median PFS (mPFS) after the first OP was 12 months (95% CI: 6.1-NR) and 10.4 months (95% CI: 3.9-NR) after the second or third OP. The median OS (mOS) from the first OP and from pembrolizumab initiation were NR. In multivariable analysis, the presence of adrenal gland was associated with shorter TTNT and OS, while OP involving bone metastasis was associated with shorter PFS. The ORR of the lesions treated with RT was 70.2%. No RT-induced severe adverse event was reported. Three patients experienced severe pembrolizumab-induced adverse events.

Conclusions: In this study, RT alongside the maintenance of pembrolizumab for patients experiencing OP during first-line pembrolizumab-based therapy for mNSCLC demonstrated an acceptable safety profile and favorable outcomes. Data from phase 3 randomized trials are needed to clearly establish the benefits of this strategy in treating oligoprogressive mNSCLC.

Background: Non-small cell lung cancers (NSCLCs) with ALK fusions are effectively treated with ALK tyrosine kinase inhibitors (TKIs). The widespread use of next-generation sequencing (NGS) assays to study the molecular profile of NSCLCs, can identify rare fusion partners of ALK. Therapy decisions are made without considering which fusion partner is present and its potential oncogenic properties. However clinical and experimental studies have shown that the 5' partner of kinase fusion variants could have a biological role in the response to targeted therapies. The objective of this report was to study the impact of a rare fusion partner of ALK on the specific TKI treatment with an in silico molecular modelling evaluating the efficiency of the protein-ligand site.

Case description: Here we describe a case of a stage IV lung adenocarcinoma with a rare striatin STRN-ALK fusion with a Partial Response of short duration to alectinib and no response to lorlatinib at progression. We investigated a computational molecular model of the protein translated from the translocated gene to suggest a mechanistic explanation for the clinical findings.

Conclusions: Our model calculations suggested that the effect of the translocation was to induce the dimerization of ALK into a complex that distorted the binding pocket, which is the same for alectinib, lorlatinib and crizotinib. The distortion of the binding pocket observed in the simulations also provides a rationale to explain the different variations of efficacy of alectinib, lorlatinib and crizotinib caused by the translocation. Our observations suggest that molecular modelling based on artificial intelligence (AI) tools may offer potential predictive information in fusions with rare partner genes. Further retrospective and prospective studies are warranted to demonstrate the predictive robustness of these tools.

Background: Thoracic tumors characterized by a deficiency in SMARCA4 are highly aggressive and linked to a poor prognosis. This retrospective study explores the efficacy and safety of immune checkpoint inhibitors (ICIs) in combination with chemotherapy for SMARCA4-deficient undifferentiated tumors (SMARCA4-dUT) and SMARCA4-deficient non-small cell lung cancer (SMARCA4-dNSCLC).

Methods: A cohort of 59 individuals was analyzed, including 35 patients with SMARCA4-dUT and 24 with SMARCA4-dNSCLC.

Results: Clinical characteristics as gender, age, smoking status, and metastatic sites did not significantly vary between SMARCA4-dUT and SMARCA4-dNSCLC. Nonsense and frameshift mutations in the SMARCA4 gene can result in the loss of its protein expression. Following a median follow-up of 7.6 months, the median progression-free survival (mPFS) notably increased with ICIs-based combination therapy compared to chemotherapy, the mPFS was 12.60 vs. 4.03 months in the SMARCA4-dUT subgroup (P=0.007) and not reached vs. 3.42 months in the SMARCA4-dNSCLC subgroup (P=0.03). In stage IV patients, the risk of disease progression and death decreased with ICIs-based combination therapy vs. chemotherapy [ICIs-based therapy vs. chemotherapy: hazard ratio (HR) =0.076; 95% confidence interval (CI): 0.009-0.624]. The most prevalent grade 3 or higher adverse events (AEs) in both groups were hematologic decreases, consistent with typical chemotherapy AEs. No treatment-related AEs led to patient fatalities.

Conclusions: The combination of ICIs and chemotherapy is more effective than chemotherapy for patients with advanced SMARCA4-deficient thoracic tumors (SMARCA4-dTT), and the safety is manageable.

Background: Lung adenocarcinoma (LUAD) is a sub-type of non-small cell lung cancer (NSCLC) that is often associated with genetic alterations, including the Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation. The KRAS mutation is particularly challenging to treat due to resistance to targeted therapies. This study aims to develop a predictive model for the KRAS mutation in patients with LUAD by integrating clinical, dual-energy spectral computed tomography (DESCT), and radiomics features.

Methods: A total of 172 patients with LUAD were retrospectively enrolled and divided into a developing cohort (n=120) and a validation cohort (n=52). Clinical, DESCT and radiomics features were extracted and analyzed. Four predictive models were constructed: clinical, DESCT, radiomics, and combined clinical-DESCT-radiomics (C-S-R) model. The performance of these models was evaluated by the receiver operating characteristic curves. A nomogram incorporating clinical, DESCT, radiomics features with R-score was developed in the validation cohort.

Results: In this study, 8.7% (15/172) of the patients showed KRAS mutation. The C-S-R model demonstrated the best performance, with an area under the curve (AUC) of 0.92 in the developing cohort and 0.87 in the validation cohort. The C-S-R model was not superior to radiomics model (P=0.28), but it was significantly better than DESCT model (P=0.01).

Conclusions: This study suggests that integrating clinical, DESCT, and radiomics features can enhance the prediction of KRAS mutation in patients with LUAD.

Background: Small-cell lung cancer (SCLC) is highly malignant. Despite being highly sensitive to initial chemotherapy and radiotherapy, the recurrence rate is high. Atezolizumab is the first immune checkpoint inhibitor (ICI) that has been proven to provide an overall survival (OS) benefit for extensive-stage SCLC (ES-SCLC), making ICIs in combination with chemotherapy the standard first-line treatment for ES-SCLC. However, the real-world treatment of SCLC is more complex, and multimodal therapy may be needed to achieve long-term patient survival. Few reports on later-line chemotherapy combined with immunotherapy have been published thus far. Moreover, there is limited data on the efficacy and safety of thoracic radiotherapy and radiotherapy for metastatic lesions after multiple lines of treatment have failed in ES-SCLC, and the value of small-molecule antiangiogenesis combined with immunotherapy also needs further exploration.

Case description: A patient was diagnosed with mediastinal limited-stage SCLC (LS-SCLC) and experienced local progression following standard chemoradiotherapy and prophylactic cranial irradiation. Subsequently, the patient underwent second-line irinotecan chemotherapy, which resulted in severe hematological toxicity. Upon initiation of third-line therapy with anlotinib, the disease remained stable for 9 months. Unfortunately, imaging revealed the presence of a new lesion at the right lung apex. Nevertheless, there was renewed hope for survival when atezolizumab was introduced as part of the treatment regimen. Despite the later development of brain metastases and metastasis adjacent to the aortic arch, long-term survival was achieved through combination therapy involving immunotherapy, antiangiogenic therapy, and radiotherapy targeting the metastatic lesions. By March 2024, the OS had reached 70 months, with a duration of treatment with atezolizumab of 48 months, and only grade II hypothyroidism occurred during treatment, with no other immunotherapy-related adverse events being observed.

Conclusions: This case report suggests the potential efficacy and safety of integrating chemotherapy, immunotherapy, radiotherapy, and antiangiogenic therapy for the treatment of SCLC. Further clinical trials are warranted to validate the value of combining chemotherapy, immunotherapy, radiotherapy, and antiangiogenic therapy.