Characteristics of mast cell infiltration in lung adenocarcinoma and its impact on prognosis.

BACKGROUND: The role of mast cells in malignancies remains unclear, and there is no clear correlation between mast cells and tumor microvessels, tumor growth, or lung adenocarcinoma (LUAD) prognosis. This study aims to explore the association between mast cell density (MCD) and intratumoral microvessel density (MVD), clinicopathological parameters, and prognosis in LUAD, by evaluating mast cell infiltration characteristics and their prognostic significance. METHODS: This retrospective investigation involved 238 patients with LUAD undergoing complete resection. Tumor and normal lung tissue sections outside the tumor were immunohistochemically stained for MCD in the intratumoral and outside regions, respectively. CD34 polyclonal antibody was used to measure intratumoral MVD. RESULTS: Intratumoral regions of LUAD had a higher MCD (P < 0.001) than normal lung tissue. In the intratumoral region, MCD and CD34-MVD were positively correlated (r = 0.411, P < 0.001). Intratumoral MCD correlated with sex, smoking history, tumor differentiation, pathological subtype, and tumor size. Female sex (P = 0.012), no smoking history (P = 0.002), acinar predominant type (P = 0.012), and tumor size ≤ 3 cm (P = 0.009) were associated with a higher MCD, whereas poorly differentiated (P = 0.039) and solid/micropapillary predominant types (P = 0.001) were associated with a lower MCD. Higher intratumoral MCD exhibited a marginally improved overall survival, and individuals with higher MCD infiltration ratios (intratumoral MCD/outside the MCD) had higher disease-free and overall survival rates (log-rank P < 0.001). A high MCD infiltration ratio was associated with decreased risk of tumor progression and death following complete resection. CONCLUSION: The tumor microenvironment controls mast cell infiltration in LUAD, and patients with increased intratumoral mast cell infiltration have better prognosis.

Risk factors of immune checkpoint inhibitor-related pneumonitis after neoadjuvant immunochemotherapy for resectable NSCLC.

BACKGROUND: The incidence of checkpoint inhibitor-associated pneumonitis (CIP) in advanced non-small cell lung cancer (NSCLC) has been substantiated through large-scale clinical trials or real-world studies. However, reports on CIP incidence within the context of neoadjuvant immunotherapy for resectable NSCLC remain scarce. This study endeavors to investigate the incidence, risk factors, and outcomes of CIP in patients with resectable NSCLC receiving neoadjuvant immunochemotherapy. METHODS: A retrospective, case-control study was conducted on patients diagnosed with NSCLC stages IIA-IIIB who received neoadjuvant immunochemotherapy between January 2018 and September 2022. Patients were stratified into two groups based on the presence or absence of CIP, facilitating a comparative analysis of clinical characteristics, treatment modalities, physiological indicators, and prognostic outcomes . RESULTS: The study cohort comprised 245 patients, with 11.4% (28/245) experiencing CIP. The median period of CIP onset was 70 (range, 40-221) days. The incidence of severe CIP (grade 3-4) was 3.7% (9/245). Patients with CIP showed a higher all-cause mortality rate of 21.4% (6/28) compared to that of patients without CIP. Those who developed CIP exhibited elevated body mass index (BMI) values (p = 0.028) and increased fibrinogen (FIB) levels (p < 0.001), alongside a significant decrease in both diffusing capacity for carbon monoxide (DLCO)% pred (p = 0.001) and DLCO/VA% pred (p = 0.021) after neoadjuvant therapy compared to pre-indicators. Receiver operating characteristic curve (ROC) analysis showed that the area under the ROC curve of three assessed variables (FIB levels, BMI, DLCO) reached 0.806 in predicting CIP occurrence at an early stage. CONCLUSIONS: This cohort demonstrated that elevated BMI, increased FIB levels, and decreased pulmonary diffusion function after neoadjuvant therapy are risk factors of CIP occurrence. Early assessment and continuous monitoring of these indicators are imperative for the predictive identification of CIP, enhancing patient management and outcomes.

Clinical outcomes associated with neoadjuvant therapy for the treatment of resectable non-small cell lung cancer in real-world practice.

BACKGROUND: In order to improve survival outcomes in resectable non-small cell lung cancer (NSCLC), strategies for neoadjuvant therapy need to be revisited. We evaluated and compared the efficacy of different neoadjuvant therapeutic modalities in a real-world setting. METHODS: A total of 258 patients with clinical stage IIA to IIIB NSCLC was included. All the patients underwent surgical resection after one to four cycles of neoadjuvant treatment consisting of chemotherapy (83), immunotherapy (23), and immunotherapy plus chemotherapy (152). RESULTS: The radiologic response rate in the combined immunochemotherapy group was 67.8%, higher than that of 48.2% in the chemotherapy group and 4.3% in the immunotherapy group (p < 0.001). An improved major pathological response (MPR) was also achieved in the combined therapy group compared with the chemotherapy group and the immunotherapy group (53.9% vs. 10.8% vs. 8.7%, p < 0.001). Patients in the combined therapy group had a significant trend toward longer disease-free survival than those in the chemotherapy alone group (3-year disease-free survival [DFS] of 68.79% vs. 50.81%; hazard ratio [HR] for progression or death, 0.477; p = 0.003). Multivariate Cox analysis identified radical surgery (HR, 0.328; p = 0.033), ypN0-1 stage (HR, 0.591; p = 0.038) and MPR result (HR, 0.362; p = 0.007) to be independent prognostic factors for DFS. CONCLUSIONS: Neoadjuvant treatment with a combination of immunotherapy plus chemotherapy appears to achieve higher radiological and pathological responses than monotherapy for IIA-IIIB NSCLC. Log-rank analysis showed that a better outcome could be expected in patients with the addition of immunotherapy to neoadjuvant chemotherapy if compared with patients with chemotherapy alone in terms of DFS.

Integrase Interactor 1 (INI1) Deficiency in a Lung Cancer Patient Presents Nonresponse to Immunotherapy and Tazemetostat: A Case Report.

Integrase interactor 1 (INI1)-deficient lung cancer is extremely rare, often with poor prognosis, and lacks effective treatment. Previous studies have reported the efficacy of immunotherapy and enhancer of the zeste homolog 2 (EZH2) inhibitor tazemetostat in various types of INI1-deficient tumors, such as sarcomas. However, the effectiveness of these treatments in INI1-deficient lung cancer has not yet been verified. We hereby report a case of a patient who was diagnosed with advanced squamous lung cancer with INI1 deficiency and received chemotherapy, immunotherapy, and tazemetostat treatments successively. The patient showed optimal response in the initial chemotherapy combined with anti-programmed cell death protein 1 (PD-1) immunotherapy, made rapid progress in the subsequent stage of maintenance immunotherapy, and showed nonresponse to tazemetostat. To the best of our knowledge, this is the first case of a lung cancer patient with INI1 deficiency who received tazemetostat treatment.

Emerging Blood-Based Biomarkers for Predicting Response to Checkpoint Immunotherapy in Non-Small-Cell Lung Cancer.

Immune checkpoint inhibitors (ICIs) have brought impressive clinical benefits in a variety of malignancies over the past years, which dramatically revolutionized the cancer treatment paradigm. Monotherapy or in combination with chemotherapy of ICIs targeting programmed death 1/programmed death ligand 1 (PD-L1) has emerged as an alternative treatment for patients with advanced non-small-cell lung cancer (NSCLC). However, constrained by primary or acquired resistance, most patients obtain limited benefits from ICIs and occasionally suffer from severe immune-related adverse events. Moreover, owing to the complexity of the tumor microenvironment and the technical limitations, clinical application of PD-L1 and tumor mutation burden as biomarkers shows many deficiencies. Thus, additional predictive biomarkers are required to further advance the precision of proper patient selection, avoiding the exposure of potential non-responders to unnecessary immunotoxicity. Nowadays, an increasing number of investigations are focusing on peripheral blood as a noninvasive alternative to tissue biopsy in predicting and monitoring treatment outcomes. Herein, we summarize the emerging blood-based biomarkers that could predict the clinical response to checkpoint immunotherapy, specifically in patients with NSCLC.

Preoperative Risk Assessment of Lymph Node Metastasis in cT1 Lung Cancer: A Retrospective Study from Eastern China.

BACKGROUND: Lymph node status of clinical T1 (diameter ≤ 3 cm) lung cancer largely affects the treatment strategies in the clinic. In order to assess lymph node status before operation, we aim to develop a noninvasive predictive model using preoperative clinical information. METHODS: We retrospectively reviewed 924 patients (development group) and 380 patients (validation group) of clinical T1 lung cancer. Univariate analysis followed by polytomous logistic regression was performed to estimate different risk factors of lymph node metastasis between N1 and N2 diseases. A predictive model of N2 metastasis was established with dichotomous logistic regression, externally validated and compared with previous models. RESULTS: Consolidation size and clinical N stage based on CT were two common independent risk factors for both N1 and N2 metastases, with different odds ratios. For N2 metastasis, we identified five independent predictors by dichotomous logistic regression: peripheral location, larger consolidation size, lymph node enlargement on CT, no smoking history, and higher levels of serum CEA. The model showed good calibration and discrimination ability in the development data, with the reasonable Hosmer-Lemeshow test (p = 0.839) and the area under the ROC being 0.931 (95% CI: 0.906-0.955). When externally validated, the model showed a great negative predictive value of 97.6% and the AUC of our model was better than other models. CONCLUSION: In this study, we analyzed risk factors for both N1 and N2 metastases and built a predictive model to evaluate possibilities of N2 metastasis of clinical T1 lung cancers before the surgery. Our model will help to select patients with low probability of N2 metastasis and assist in clinical decision to further management.