Lung cancer patients with chronic obstructive pulmonary disease benefit from anti-PD-1/PD-L1 therapy

Low pre-immunotherapy forced vital capacity is associated with poor outcomes in non-small cell lung cancer patients receiving immunotherapy regardless of prior treatment history

Background

Many patients with lung cancer have underlying chronic lung diseases. We assume that baseline lung functions might also affect the prognosis of non-small cell lung cancer (NSCLC) patients receiving immunotherapy.

Objectives

We aimed to assess the impact of pretreatment clinical parameters, including lung function measures such as forced vital capacity (FVC), on the prognosis of patients with NSCLC following immune checkpoint inhibitors (ICIs) therapy.

Design

Retrospective multicenter study.

Methods

Study subjects were consecutively selected from a multicenter cohort of patients with NSCLC who were undergoing immunotherapy. Patients were selected regardless of their initial cancer stage and prior treatment. The primary outcome was immunotherapy-related overall survival (iOS), defined as the duration from the initiation of immunotherapy to the time patients were censored. Spirometry values were acquired before bronchodilator application and were performed within the year before the first ICI treatment.

Results

We selected 289 patients for evaluation. The median iOS was 10.9 months (95% confidence interval (CI), 7.5-14.3). Programmed death-ligand 1 (PD-L1) expression, tested by SP263, was <1% in 20.9%, 1%-49% in 44.3%, and ⩾50% in 32.6% of the patients. ICI was used most often as second-line treatment (70.2%), followed by first line (13.1%), and third line (11.4%). In the Kaplan-Meier analysis, the median iOS of the low FVC group was significantly shorter than that in the preserved FVC group (6.10 (95% CI, 4.45-7.76) months vs 14.40 (95% CI, 10.61-18.34) months, p < 0.001)). A Cox regression analysis for iOS showed that age, poor performance status, PD-L1 expression measured by SP263, stage at diagnosis, and FVC (% predicted) were independent predictive factors. When we replaced FVC (%) in the multivariable analysis with forced expiratory volume in 1 s (%), diffusing lung capacity for carbon monoxide (DLco; %), or DLco (absolute), each of the pulmonary function factors showed a significant association with iOS.

Conclusion

Pre-immunotherapy FVC (%) predicted immunotherapy-related outcomes in NSCLC patients, regardless of initial stage at diagnosis and prior treatment modalities.

Decision model for durable clinical benefit from front- or late-line immunotherapy alone or with chemotherapy in non-small cell lung cancer

BACKGROUND

Predictive biomarkers and models of immune checkpoint inhibitors (ICIs) have been extensively studied in non-small cell lung cancer (NSCLC). However, evidence for many biomarkers remains inconclusive, and the opaqueness of machine learning models hinders practicality. We aimed to provide compelling evidence for biomarkers and develop a transparent decision tree model.

METHODS

We consolidated data from 3,288 ICI-treated patients with NSCLC across real-world multicenter, public cohorts and the Choice-01 trial (ClinicalTrials.gov: NCT03856411). Over 50 features were examined for predicting durable clinical benefits (DCBs) from ICIs. Noteworthy biomarkers were identified to establish a decision tree model. Additionally, we explored the tumor microenvironment and peripheral CD8+ programmed death-1 (PD-1)+ T cell receptor (TCR) profiles.

FINDINGS

Multivariate logistic regression analysis identified tumor histology, PD-ligand 1 (PD-L1) expression, tumor mutational burden, line, and regimen of ICI treatment as significant factors. Mutation subtypes of EGFR, KRAS, KEAP1, STK11, and disruptive TP53 mutations were associated with DCB. The decision tree (DT10) model, using the ten clinicopathological and genomic markers, showed superior performance in predicting DCB in the training set (area under the curve [AUC] = 0.82) and consistently outperformed other models in test sets. DT10-predicted-DCB patients manifested longer survival, an enriched inflamed tumor immune phenotype (67%), and higher peripheral TCR diversity, whereas the DT10-predicted-NDB (non-durable benefit) group showed an enriched desert immune phenotype (86%) and higher peripheral TCR clonality.

CONCLUSIONS

The model effectively predicted DCB after front-/subsequent-line ICI treatment, with or without chemotherapy, for squamous and non-squamous lung cancer, offering clinicians valuable insights into efficacy prediction using cost-effective variables.

FUNDING

This study was supported by the National Key R&D Program of China.

Effectiveness of Immunotherapy in Non-Small Cell Lung Cancer Patients with a Diagnosis of COPD: Is This a Hidden Prognosticator for Survival and a Risk Factor for Immune-Related Adverse Events?

The interplay between the immune system and chronic obstructive pulmonary disease (COPD) and non-small cell lung cancer (NSCLC) is complex and multifaceted. In COPD, chronic inflammation and oxidative stress can lead to immune dysfunction that can exacerbate lung damage, further worsening the respiratory symptoms. In NSCLC, immune cells can recognise and attack the cancer cells, which, however, can evade or suppress the immune response by various mechanisms, such as expressing immune checkpoint proteins or secreting immunosuppressive cytokines, thus creating an immunosuppressive tumour microenvironment that promotes cancer progression and metastasis. The interaction between COPD and NSCLC further complicates the immune response. In patients with both diseases, COPD can impair the immune response against cancer cells by reducing or suppressing the activity of immune cells, or altering their cytokine profile. Moreover, anti-cancer treatments can also affect the immune system and worsen COPD symptoms by causing lung inflammation and fibrosis. Immunotherapy itself can also cause immune-related adverse events that could worsen the respiratory symptoms in patients with COPD-compromised lungs. In the present review, we tried to understand the interplay between the two pathologies and how the efficacy of immunotherapy in NSCLC patients with COPD is affected in these patients.

Exploring the Potential Role of Metabolomics in COPD: A Concise Review

Chronic Obstructive Pulmonary Disease (COPD) is a pathological condition of the respiratory system characterized by chronic airflow obstruction, associated with changes in the lung parenchyma (pulmonary emphysema), bronchi (chronic bronchitis) and bronchioles (small airways disease). In the last years, the importance of phenotyping and endotyping COPD patients has strongly emerged. Metabolomics refers to the study of metabolites (both intermediate or final products) and their biological processes in biomatrices. The application of metabolomics to respiratory diseases and, particularly, to COPD started more than one decade ago and since then the number of scientific publications on the topic has constantly grown. In respiratory diseases, metabolomic studies have focused on the detection of metabolites derived from biomatrices such as exhaled breath condensate, bronchoalveolar lavage, and also plasma, serum and urine. Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy are powerful tools in the precise identification of potentially prognostic and treatment response biomarkers. The aim of this article was to comprehensively review the relevant literature regarding the applications of metabolomics in COPD, clarifying the potential clinical utility of the metabolomic profile from several biologic matrices in detecting biomarkers of disease and prognosis for COPD. Meanwhile, a complete description of the technological instruments and techniques currently adopted in the metabolomics research will be described.

Impact of chronic obstructive pulmonary disease on the efficacy and safety of neoadjuvant immune checkpoint inhibitors combined with chemotherapy for resectable non-small cell lung cancer: a retrospective cohort study

BACKGROUND

Neoadjuvant immune checkpoint inhibitors(ICIs) combined with chemotherapy can improve non-small cell lung cancer(NSCLC) patients' pathological responses and show promising improvements in survival. Chronic obstructive pulmonary disease (COPD) is a systemic inflammatory disease, and its associated abnormal inflammatory response affects not only the immunotherapy efficacy but also immune-related adverse events. It remains unclear whether NSCLC patients with COPD can benefit from neoadjuvant ICIs combined with chemotherapy.

METHODS

A retrospective observational clinical study was conducted on 105 consecutive NSCLC patients receiving neoadjuvant ICIs combined with chemotherapy at the Department of Thoracic Surgery of Tianjin Chest Hospital between April 2020 and April 2023.

RESULTS

A total of 74 NSCLC patients were included in the study, including 30 patients with COPD and 44 patients without COPD. The percentage of patients with a pathological complete response (PCR) was higher in the COPD group than in the non-COPD group (43.3% vs. 20.5%, P = 0.042). Multivariate logistic regression analysis of factors associated with PCR showed that the adjusted odds ratio (OR) was statistically significant for presence of COPD (OR = 3.020, 95%CI: 1.042-8.757; P = 0.042). Major pathological response (66.7% vs. 50%, P = 0.155), R0 resection rate (96.7% vs.93.2%, P = 0.642), N2 lymph node downstaging(92.3% vs. 66.7%, P = 0.182) and objective response rate (70% vs. 63.6%, P = 0.57) were not significantly different between the groups. Progression-free survival(PFS) was not reached in the COPD group and 17 months (95%CI: 12.1-21.9) in the non-COPD group, with statistically significance (χ2 = 6.247, P = 0.012). Multivariate Cox's regression analysis showed that the adjusted hazard ratio (HRadj) was statistically significant for presence of COPD (HRadj = 0.321, 95%CI: 0.111-0.930; P = 0.036). The grade 3 and grade 4 adverse events in the COPD group were leukopenia (3.3%, 6.7%), neutropenia (3.3%, 6.7%), fatigue (6.7%, 0%), gastrointestinal reactions (3.3%, 0%), and hypothyroidism (3.3%, 0%). In the non-COPD group, the corresponding adverse events were leukopenia (6.8%, 6.8%), neutropenia (3.3%, 6.8%), fatigue (2.3%, 0%), gastrointestinal reactions (2.3%, 0%), and hypothyroidism (2.3%, 0%), respectively.

CONCLUSIONS

The present study indicates that the presence of COPD may improve PCR, prolong PFS, and have an acceptable safety profile in NSCLC patients receiving neoadjuvant ICIs combined with chemotherapy.

A Bibliometric Analysis of Comorbidity of COPD and Lung Cancer: Research Status and Future Directions

Objective

Although studies on the association between COPD and lung cancer are of great significance, no bibliometric analysis has been conducted in the field of their comorbidity. This bibliometric analysis explores the current situation and frontier trends in the field of COPD and lung cancer comorbidity, and to lay a new direction for subsequent research.

Methods

Articles in the field of COPD and cancer comorbidity were retrieved from Web of Science Core Collections (WoSCC) from 2004 to 2023, and analyzed by VOSviewer, CiteSpace, Biblimatrix and WPS Office.

Results

In total, 3330 publications were included. The USA was the leading country with the most publications and great influence. The University of Groningen was the most productive institution. Edwin Kepner Silverman was the most influential scholar in this field. PLOS One was found to be the most prolific journal. Mechanisms and risk factors were of vital importance in this research field. Environmental pollution and pulmonary fibrosis may be future research prospects.

Conclusion

This bibliometric analysis provided new guidance for the development of the field of COPD and lung cancer comorbidity by visualizing current research hotspots, and predicting possible hot research directions in the future.

Impact of COPD pulmonary structural remodeling on the prognosis of patients with advanced lung squamous cell carcinoma

Background

By observing the changes of lung imaging airway structure in patients with advanced lung squamous cell carcinoma（ALUSC）, the relationship between the different types of COPD pulmonary structural remodeling and the prognosis of patients with ALUSC was analyzed.

Methods

We reviewed the medical records of 278 patients with ALUSC. The degree of emphysema and the percentage of bronchial wall thickness（WT%） on chest HRCT were calculated by Synapse3D software, Lung structural remodeling can be divided into there types: airway remodeling dominated, emphysema dominated, and mixed types.

Results

Compared with the diagnosis, the Goddard score increased, the proportion of airway remodeling dominated type decreased and the proportion of mixed type increased during the progression of ALUSC. In Kaplan-Meier analysis, whether with or without COPD, the mPFS and mOS of patients with mixed type were the shortest, and the difference was statistically significant. Univariate and multivariate Cox proportional hazard regression analysis showed that mixed type was an independent risk factor for poor PFS and OS in patients with ALUSC.

Conclusion

Patients with ALUSC all have varying degrees of lung structural remodeling, and patients with mixed lung structural remodeling have the worst prognosis. In addition, the aggravation of emphysema during tumor progression is more pronounced than the thickening of the airway wall, and the changes of emphysema was more powerful in predicting the progression of ALUSC.Clinicians must pay more attention to the changes of COPD (especially emphysema) in the process of diagnosis and treatment of ALUSC.

International expert consensus on diagnosis and treatment of lung cancer complicated by chronic obstructive pulmonary disease

Background

Lung cancer combined by chronic obstructive pulmonary disease (LC-COPD) is a common comorbidity and their interaction with each other poses significant clinical challenges. However, there is a lack of well-established consensus on the diagnosis and treatment of LC-COPD.

Methods

A panel of experts, comprising specialists in oncology, respiratory medicine, radiology, interventional medicine, and thoracic surgery, was convened. The panel was presented with a comprehensive review of the current evidence pertaining to LC-COPD. After thorough discussions, the panel reached a consensus on 17 recommendations with over 70% agreement in voting to enhance the management of LC-COPD and optimize the care of these patients.

Results

The 17 statements focused on pathogenic mechanisms (n=2), general strategies (n=4), and clinical application in COPD (n=2) and lung cancer (n=9) were developed and modified. These statements provide guidance on early screening and treatment selection of LC-COPD, the interplay of lung cancer and COPD on treatment, and considerations during treatment. This consensus also emphasizes patient-centered and personalized treatment in the management of LC-COPD.

Conclusions

The consensus highlights the need for concurrent treatment for both lung cancer and COPD in LC-COPD patients, while being mindful of the mutual influence of the two conditions on treatment and monitoring for adverse reactions.

Radiomic biomarkers from chest computed tomography are assistive in immunotherapy response prediction for non-small cell lung cancer

Background

Immunotherapies, such as programmed death 1/programmed death ligand 1 (PD-1/PD-L1) antibodies have been shown to improve overall and progression-free survival (PFS) in patients with locally advanced or metastatic non-small cell lung cancer (NSCLC). However, not all patients derive a meaningful clinical benefit. Additionally, patients receiving anti-PD-1/PD-L1 therapy can experience immune-related adverse events (irAEs). Clinically significant irAEs may require temporary pause or discontinuation of treatment. Having a tool to identify patients who may not benefit and/or are at risk for developing severe irAEs from immunotherapy will aid in an informed decision-making process for the patients and their physicians.

Methods

Computed tomography (CT) scans and clinical data were retrospectively collected for this study to develop three prediction models using (I) radiomic features, (II) clinical features, and (III) radiomic and clinical features combined. Each subject had 6 clinical features and 849 radiomic features extracted. Selected features were run through an artificial neural network (NN) trained on 70% of the cohort, maintaining the case and control ratio. The NN was assessed by calculating the area-under-the-receiver-operating-characteristic curve (AUC-ROC), area-under-the-precision-recall curve (AUC-PR), sensitivity, and specificity.

Results

A cohort of 132 subjects, of which 43 (33%) had a PFS ≤90 days and 89 (67%) of which had a PFS >90 days was used to develop the prediction models. The radiomic model was able to predict progression-free survival with a training AUC-ROC of 87% and testing AUC-ROC, sensitivity, and specificity of 83%, 75%, and 81%, respectively. In this cohort, the clinical and radiomic combined features did add a slight increase in the specificity (85%) but with a decrease in sensitivity (75%) and AUC-ROC (81%).

Conclusions

Whole lung segmentation and feature extraction can identify those that would see a benefit from anti-PD-1/PD-L1 therapy.