Markers of Stroma in Lung Cancer: Influence of COPD

Prediction of the benign and malignant nature of masses in COPD background based on Habitat-based enhanced CT radiomics modeling: A preliminary study

BACKGROUND

It is difficult to differentiate between chronic obstructive pulmonary disease (COPD)-peripheral bronchogenic carcinoma (COPD-PBC) and inflammatory masses.

OBJECTIVE

This study aims to predict COPD-PBC based on clinical data and preoperative Habitat-based enhanced CT radiomics (HECT radiomics) modeling.

METHODS

A retrospective analysis was conducted on clinical imaging data of 232 cases of postoperative pathological confirmed PBC or inflammatory masses. The PBC group consisted of 82 cases, while the non-PBC group consisted of 150 cases. A training set and a testing set were established using a 7:3 ratio and a time cutoff point. In the training set, multiple models were established using clinical data and radiomics texture changes within different enhanced areas of the CT mass (HECT radiomics). The AUC values of each model were compared using Delong's test, and the clinical net benefit of the models was tested using decision curve analysis (DCA). The models were then externally validated in the testing set, and a nomogram of predicting COPD-PBC was created.

RESULTS

Univariate analysis confirmed that female gender, tumor morphology, CEA, Cyfra21-1, CT enhancement pattern, and Habitat-Radscore B/C were predictive factors for COPD-PBC (P< 0.05). The combination model based on these factors had significantly higher predictive performance [AUC: 0.894, 95% CI (0.836-0.936)] than the clinical data model [AUC: 0.758, 95% CI (0.685-0.822)] and radiomics model [AUC: 0.828, 95% CI (0.761-0.882)]. DCA also confirmed the higher clinical net benefit of the combination model, which was validated in the testing set. The nomogram developed based on the combination model helped predict COPD-PBC.

CONCLUSION

The combination model based on clinical data and Habitat-based enhanced CT radiomics can help differentiate COPD-PBC, providing a new non-invasive and efficient method for its diagnosis, treatment, and clinical decision-making.

Systemic Profiles of microRNAs, Redox Balance, and Inflammation in Lung Cancer Patients: Influence of COPD

Lung cancer (LC) risk increases in patients with chronic respiratory diseases (COPD). MicroRNAs and redox imbalance are involved in lung tumorigenesis in COPD patients. Whether systemic alterations of those events may also take place in LC patients remains unknown. Our objectives were to assess the plasma levels of microRNAs, redox balance, and cytokines in LC patients with/without COPD. MicroRNAs (RT-PCR) involved in LC, oxidized DNA, MDA-protein adducts, GSH, TEAC, VEGF, and TGF-beta (ELISA) were quantified in plasma samples from non-LC controls (n = 45), LC-only patients (n = 32), and LC-COPD patients (n = 91). In LC-COPD patients compared to controls and LC-only, MDA-protein adduct levels increased, while those of GSH decreased, and two patterns of plasma microRNA were detected. In both LC patient groups, miR-451 expression was downregulated, while those of microRNA-let7c were upregulated, and levels of TEAC and TGF-beta increased compared to the controls. Correlations were found between clinical and biological variables. A differential expression profile of microRNAs was detected in patients with LC. Moreover, in LC patients with COPD, plasma oxidative stress levels increased, whereas those of GSH declined. Systemic oxidative and antioxidant markers are differentially expressed in LC patients with respiratory diseases, thus implying its contribution to the pathogenesis of tumorigenesis in these patients.

Increased PARP Activity and DNA Damage in NSCLC Patients: The Influence of COPD

(1) Background: Lung cancer (LC) is a major leading cause of death worldwide. Poly (ADP-ribose) polymerase (PARP)-1 and PARP-2 are key players in cancer. We aimed to assess PARP-1 and PARP-2 expression and activity and DNA damage in tumors and non-tumor lungs from patients with/without chronic obstructive pulmonary disease (COPD). (2) Methods: Lung tumor and non-tumor specimens were obtained through video-assisted thoracoscopic surgery (VATS) in LC patients with/without underlying COPD (two groups of patients, n = 15/group). PARP-1 and PARP-2 expression (ELISA), PARP activity (PARP colorimetric assay kit) and DNA damage (immunohistochemistry) levels were identified in all samples. (3) Results: Both PARP-1 and PARP-2 expression levels were significantly lower in lung tumors (irrespective of COPD)compared to non-tumor specimens, while DNA damage and PARP activity levels significantly increased in lung tumors compared to non-tumor specimens only in LC-COPD patients. PARP-2 expression was positively correlated with smoking burden in LC-COPD patients. (4) Conclusions: In lung tumors of COPD patients, an overactivation of PARP enzyme was observed. A decline in PARP-1 and PARP-2 protein expression was seen in lung tumors irrespective of COPD. Other phenotypic features (airway obstruction) beyond cancer may account for the increase in PARP activity seen in the tumors of patients with underlying COPD.