Accuracy of minimal residual disease detection by circulating tumor DNA profiling in lung cancer: a meta-analysis.

BACKGROUND: The sensitivity and specificity of minimal residual disease detected by circulating tumor DNA profiling (ctDNA MRD) in lung cancer, with particular attention to the distinction between landmark strategy and surveillance strategy, for predicting relapse in lung cancer patients after definitive therapy has yet to be determined. METHODS: The prognostic value of ctDNA MRD by landmark strategy and surveillance strategy was evaluated in a large cohort of patients with lung cancer who received definitive therapy using a systemic literature review and meta-analysis. Recurrence status stratified by ctDNA MRD result (positive or negative) was extracted as the clinical endpoint. We calculated the area under the summary receiver operating characteristic curves, and pooled sensitivities and specificities. Subgroup analyses were conducted based on histological type and stage of lung cancer, types of definitive therapy, and ctDNA MRD detection methods (detection technology and strategy such as tumor-informed or tumor-agnostic). RESULTS: This systematic review and meta-analysis of 16 unique studies includes 1251 patients with lung cancer treated with definitive therapy. The specificity of ctDNA MRD in predicting recurrence is high (0.86-0.95) with moderate sensitivity (0.41-0.76), whether shortly after treatment or during the surveillance. The landmark strategy appears to be more specific but less sensitive than the surveillance strategy. CONCLUSIONS: Our study suggests that ctDNA MRD is a relatively promising biomarker for relapse prediction among lung cancer patients after definitive therapy, with a high specificity but suboptimal sensitivity, whether in landmark strategy or surveillance strategy. Although surveillance ctDNA MRD analysis decreases specificity compared with the landmark strategy, the decrease is minimal compared to the increase in sensitivity for relapse prediction of lung cancer.

Do testosterone and sex hormone-binding globulin affect cancer risk? A Mendelian randomization and bioinformatics study.

Using Mendelian Randomization (MR) and large-scale Genome-Wide Association Study (GWAS) data, this study aimed to investigate the potential causative relationship between testosterone and sex hormone-binding globulin (SHBG) levels and the onset of several cancers, including pathway enrichment analyses of single nucleotide polymorphisms (SNPs) associated with cancer allowed for a comprehensive bioinformatics approach, which offered a deeper biological understanding of these relationships. The results indicated that increased testosterone levels in women were associated with a higher risk of breast and cervical cancers but a lower risk of ovarian cancer. Conversely, increased testosterone was linked to lower stomach cancer risk for men, whereas high SHBG levels were related to decreased risks of breast and prostate cancers. The corresponding genes of the identified SNPs, as revealed by pathway enrichment analysis, were involved in significant metabolic and proliferative pathways. These findings emphasize the need for further research into the biological mechanisms behind these associations, paving the way for potential targeted interventions in preventing and treating these cancers.

Assessing the genetic relationship between gastroesophageal reflux disease and chronic respiratory diseases: a mendelian randomization study.

BACKGROUND: Previous observational studies have found an association between gastroesophageal reflux disease (GERD) and chronic respiratory diseases, but it remains uncertain whether GERD causally influences these diseases. In this study, we aimed to estimate the causal associations between GERD and 5 chronic respiratory diseases. METHODS: 88 GERD-associated single nucleotide polymorphisms (SNPs) identified by the latest genome-wide association study were included as instrumental variables. Individual-level genetic summary data of participants were obtained from corresponding studies and the FinnGen consortium. We applied the inverse-variance weighted method to estimate the causality between genetically predicted GERD and 5 chronic respiratory diseases. Furthermore, the associations between GERD and common risk factors were investigated, and mediation analyses were conducted using multivariable MR. Various sensitivity analyses were also performed to verify the robustness of the findings. RESULTS: Our study demonstrated that genetically predicted GERD was causally associated with an increased risk of asthma (OR 1.39, 95%CI 1.25-1.56, P < 0.001), idiopathic pulmonary fibrosis (IPF) (OR 1.43, 95%CI 1.05-1.95, P = 0.022), chronic obstructive disease (COPD) (OR 1.64, 95%CI 1.41-1.93, P < 0.001), chronic bronchitis (OR 1.77, 95%CI 1.15-2.74, P = 0.009), while no correlation was observed for bronchiectasis (OR 0.93, 95%CI 0.68-1.27, P = 0.645). Additionally, GERD was associated with 12 common risk factors for chronic respiratory diseases. Nevertheless, no significant mediators were discovered. CONCLUSIONS: Our study suggested that GERD was a causal factor in the development of asthma, IPF, COPD and chronic bronchitis, indicating that GERD-associated micro-aspiration of gastric contents process might play a role in the development of pulmonary fibrosis in these diseases.

Predicting EGFR mutation status in lung adenocarcinoma presenting as ground-glass opacity: utilizing radiomics model in clinical translation.

OBJECTIVES: This study aimed to establish a non-invasive radiomics model based on computed tomography (CT), with favorable sensitivity and specificity to predict EGFR mutation status in GGO-featured lung adenocarcinoma subsequently guiding the administration of targeted therapy. METHODS: Clinical-pathological information and preoperative CT images of 636 lung adenocarcinoma patients (464, 100, and 72 in the training, internal, and external validation sets, respectively) that underwent GGO lesions resection were included. A total of 1476 radiomics features were extracted with gradient boosting decision tree (GBDT). RESULTS: The established radiomics model containing 102 selected features showed an encouraging discrimination performance of EGFR mutation status (mutant or wild type), and the predictive ability was superior to that of the clinical model (AUC: 0.838 vs. 0.674, 0.822 vs. 0.730, and 0.803 vs. 0.746 for the training, internal validation, and external validation sets, respectively). The combined radiomics plus clinical model showed no additional benefit over the radiomics model in predicting EGFR status (AUC: 0.846 vs. 0.838, 0.816 vs. 0.822, and 0.811 vs. 0.803, respectively, in three cohorts). Uniquely, this model was validated in a cohort of lung adenocarcinoma patients who have undertaken adjuvant EGFR-TKI treatment and harbored unresected GGOs during the medication, leading to a significantly improved potency of EGFR-TKIs (response rate: 25.9% vs. 53.8%, p = 0.006; before and after prediction, respectively). CONCLUSION: This presented radiomics model can be served as a non-invasive and time-saving approach for predicting the EGFR mutation status in lung adenocarcinoma presenting as GGO. KEY POINTS: • We developed a GGO-specific radiomics model containing 102 radiomics features for EGFR mutation status differentiation. • An AUC of 0.822 and 0.803 in the internal and external validation cohorts, respectively, were achieved. • The radiomics model was utilized in clinical translation in an adjuvant EGFR-TKI treatment cohort with unresected GGOs. A significant improvement in the potency of EGFR-TKIs was achieved (response rate: 25.9% vs. 53.8%, p = 0.006; before and after prediction).

Artificial intelligence for stepwise diagnosis and monitoring of COVID-19.

BACKGROUND: Main challenges for COVID-19 include the lack of a rapid diagnostic test, a suitable tool to monitor and predict a patient's clinical course and an efficient way for data sharing among multicenters. We thus developed a novel artificial intelligence system based on deep learning (DL) and federated learning (FL) for the diagnosis, monitoring, and prediction of a patient's clinical course. METHODS: CT imaging derived from 6 different multicenter cohorts were used for stepwise diagnostic algorithm to diagnose COVID-19, with or without clinical data. Patients with more than 3 consecutive CT images were trained for the monitoring algorithm. FL has been applied for decentralized refinement of independently built DL models. RESULTS: A total of 1,552,988 CT slices from 4804 patients were used. The model can diagnose COVID-19 based on CT alone with the AUC being 0.98 (95% CI 0.97-0.99), and outperforms the radiologist's assessment. We have also successfully tested the incorporation of the DL diagnostic model with the FL framework. Its auto-segmentation analyses co-related well with those by radiologists and achieved a high Dice's coefficient of 0.77. It can produce a predictive curve of a patient's clinical course if serial CT assessments are available. INTERPRETATION: The system has high consistency in diagnosing COVID-19 based on CT, with or without clinical data. Alternatively, it can be implemented on a FL platform, which would potentially encourage the data sharing in the future. It also can produce an objective predictive curve of a patient's clinical course for visualization. KEY POINTS: • CoviDet could diagnose COVID-19 based on chest CT with high consistency; this outperformed the radiologist's assessment. Its auto-segmentation analyses co-related well with those by radiologists and could potentially monitor and predict a patient's clinical course if serial CT assessments are available. It can be integrated into the federated learning framework. • CoviDet can be used as an adjunct to aid clinicians with the CT diagnosis of COVID-19 and can potentially be used for disease monitoring; federated learning can potentially open opportunities for global collaboration.

Immune-related adverse events of a PD-L1 inhibitor plus chemotherapy versus a PD-L1 inhibitor alone in first-line treatment for advanced non-small cell lung cancer: A meta-analysis of randomized control trials.

BACKGROUND: The addition of chemotherapy to a programmed death 1/programmed death ligand 1 (PD-L1) inhibitor is a more effective option as a first-line treatment for advanced non-small cell lung cancer (NSCLC). It might also inhibit an overactive immune response and thereby reduce immune-related adverse events (irAEs). This meta-analysis assessed the rate of irAEs with a PD-(L)1 inhibitor plus chemotherapy (I+C) versus a PD-(L)1 inhibitor alone (I) and evaluated the indirect relative risk (RR) of I+C versus I. METHODS: The protocol of this study was registered with PROSPERO (CRD42020139923). The pooled rates of irAEs at different grades were calculated by a single-arm meta-analysis weighted by sample size, and RRs were determined by direct meta-analysis and indirect treatment comparison. RESULTS: Overall, I+C had a lower rate of grade 3 or higher irAEs than I (7.1% vs 10.6%; indirect RR, 0.516; 95% confidence interval [CI], 0.291-0.916), although irAEs of any grade were similar. The rate of pneumonitis with I+C was lower than the rate with I for any grade (5.9% vs 7.1%; indirect RR, 0.217; 95% CI, 0.080-0.588) and for grade 3 or higher. In the endocrine system, I+C was associated with a lower overall ratein comparison with I (16.1% vs 20.1%; indirect RR, 0.260; 95% CI, 0.120-0.564), whereas irAEs of the digestive system were similar with I+C and I. In other systems, I+C decreased the rate of skin reactions, including rash, in comparison with I (10.4% vs 12.9%; indirect RR, 0.474; 95% CI, 0.299-0.751). The rate of grade 3 or higher skin reactions (excluding rash) also decreased with I+C versus I (1.1% vs 2.0%) with an indirect RR of 0.158 (95% CI, 0.032-0.765), whereas other included irAEs were similar. CONCLUSIONS: In comparison with a PD-(L)1 inhibitor alone, a combination with chemotherapy for the first-line treatment of NSCLC decreased the rates of most irAEs, such as pneumonitis and endocrine and skin reactions, and the overall rate. LAY SUMMARY: In the first-line treatment of advanced non-small cell lung cancer (NSCLC), the addition of chemotherapy to a programmed death 1/programmed death ligand 1 (PD-(L)1) inhibitor is a more effective option. Adding chemotherapy might reduce immune-related adverse events (irAEs). Thus, this article assesses the rate of irAEs with a PD-(L)1 inhibitor plus chemotherapy (I+C) in comparison with a PD-(L)1 inhibitor alone (I) and evaluates the indirect relative risk (RR) with I+C versus I. The key finding is that in comparison with a PD-(L)1 inhibitor alone, a combination with chemotherapy for the first-line treatment of NSCLC decreases the rates of most irAEs, such as pneumonitis and endocrine and skin reactions, and the overall rate.

Breast cancer risk in patients with polycystic ovary syndrome: a Mendelian randomization analysis.

PURPOSE: The association between polycystic ovary syndrome (PCOS) and breast cancer remains inconclusive. Conventional observational studies are susceptible to inverse causality and potential confounders. With a Mendelian randomization (MR) approach, we aimed to investigate the causal relationship between genetically predicted PCOS and breast cancer risk. METHODS: Our study included 11 PCOS-associated single nucleotide polymorphisms as instrumental variables identified by the latest genome-wide association study. Individual-level genetic summary data of participants were obtained from the Breast Cancer Association Consortium, with a total of 122,977 cases and 105,974 controls. The inverse-variance weighted method was applied to estimate the causality between genetically predicted PCOS and breast cancer risk. To further evaluate the pleiotropy, the weighted median and MR-Egger regression methods were implemented as well. RESULTS: Our study demonstrated that genetically predicted PCOS was causally associated with an increased risk of overall breast cancer (odds ratio (OR) = 1.07; 95% confidence interval (CI) 1.02-1.12, p = 0.005). The subgroup analyses according to immunohistochemical type further illustrated that genetically predicted PCOS was associated with an increased risk of estrogen receptor (ER)-positive breast cancer (OR = 1.09; 95% CI 1.03-1.15, p = 0.002), while no causality was observed for ER-negative breast cancer (OR = 1.02; 95% CI 0.96-1.09, p = 0.463). In addition, no pleiotropy was found in our study. CONCLUSIONS: Our findings indicated that PCOS was likely to be a causal factor in the development of ER-positive breast cancer, providing a better understanding for the etiology of breast cancer and the prevention of breast cancer.

Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. OBJECTIVE: To evaluate the risk of serious adverse outcomes in patients with COVID-19 by stratifying the comorbidity status. METHODS: We analysed data from 1590 laboratory confirmed hospitalised patients from 575 hospitals in 31 provinces/autonomous regions/provincial municipalities across mainland China between 11 December 2019 and 31 January 2020. We analysed the composite end-points, which consisted of admission to an intensive care unit, invasive ventilation or death. The risk of reaching the composite end-points was compared according to the presence and number of comorbidities. RESULTS: The mean age was 48.9 years and 686 (42.7%) patients were female. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached the composite end-points. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD (HR (95% CI) 2.681 (1.424-5.048)), diabetes (1.59 (1.03-2.45)), hypertension (1.58 (1.07-2.32)) and malignancy (3.50 (1.60-7.64)) were risk factors of reaching the composite end-points. The hazard ratio (95% CI) was 1.79 (1.16-2.77) among patients with at least one comorbidity and 2.59 (1.61-4.17) among patients with two or more comorbidities. CONCLUSION: Among laboratory confirmed cases of COVID-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.

Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicentre) and outside Hubei (non-epicentre): a nationwide analysis of China.

BACKGROUND: During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences. METHODS: Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined. RESULTS: At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7 versus 44.9 years), had more cases with comorbidity (32.9% versus 19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7 versus 4.5 days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0% versus 11.1%, death rate 7.3% versus 0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4 versus 4.7 days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08)). CONCLUSION: There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted.

PD-(L)1 inhibitors vs. chemotherapy vs. their combination in front-line treatment for NSCLC: An indirect comparison.

We comprehensively compared the therapeutic effects and safety of PD-1/L1 antibodies (I), chemotherapy (C) or their combination (I + C) as first-line treatments for advanced NSCLC. Online databases were searched to identify RCTs. Survival outcomes and safety events were pooled by indirect treatment comparison. Main subgroup analyses were conducted according to PD-L1 expression. A total of 11 RCTs involving 6,731 patients were included. Overall, PD-1/L1 inhibitors showed no difference to chemotherapy in PFS (HR 0.90, 0.65-1.24) and OS (HR 0.84, 0.64-1.09), while I + C was superior to chemotherapy both in PFS (HR 0.64, 0.58-0.71) and OS (HR 0.74, 0.62-0.89). I + C also showed advantages over PD-1/L1 in PFS (HR 0.71, 0.51-0.99) but not OS (HR 0.88, 0.64-1.22). In the PD-L1 < 1% subgroup, I + C was beneficial both in OS (HR 0.78, 0.67-0.90) and PFS (HR 0.72, 0.65-0.80) than chemotherapy. In PD-L1 ≥ 50% population, PD-1/L1 had longer OS than chemotherapy (HR 0.71, 0.60-0.84); I + C also had longer OS (HR 0.61, 0.49-0.77) and PFS (HR 0.41,0.34-0.49) than chemotherapy. In indirect analysis (PD-L1 ≥ 50%), I + C was superior to PD-1/L1 in terms of PFS (HR 0.54, 0.35-0.82), but not OS (HR 0.86, 0.65-1.14). Both treatment-related and immune-mediated adverse events occurred most frequently in the combination therapy group. We suggest that a combination regimen is preferable as first-line treatment for NSCLC patients with different PD-L1 expression, in the meanwhile, in cautious of side effects.

Association between certain non-small cell lung cancer driver mutations and predictive markers for chemotherapy or programmed death-ligand 1 inhibition.

This study aimed to analyze the association between driver mutations and predictive markers for some anti-tumor agents in non-small cell lung cancer (NSCLC). A cohort of 785 Chinese patients with NSCLC who underwent resection from March 2016 to November 2017 in the First Affiliated Hospital of Guangzhou Medical University was investigated. The specimens were subjected to hybridization capture and sequence of 8 important NSCLC-related driver genes. In addition, the slides were tested for PD-L1, excision repair cross-complementation group 1 (ERCC1), ribonucleotide reductase subunit M1 (RRM1), thymidylate synthase (TS) and ß-tubulin III by immunohistochemical staining. A total of 498 (63.4%) patients had at least 1 driver gene alteration. Wild-type, EGFR rare mutation (mut), ALK fusion (fus), RAS mut, RET fus and MET mut had relatively higher proportions of lower ERCC1 expression. EGFR 19del, EGFR L858R, EGFR rare mut, ALK fus, HER2 mut, ROS1 fus and MET mut were more likely to have TS low expression. Wild-type, EGFR L858R, EGFR rare mut and BRAF mut were associated with lower ß-tubulin III expression. In addition, wild-type, RAS mut, ROS1 fus, BRAF and MET mut had higher proportion of PD-L1 high expression. As a pilot validation, 21 wild-type patients with advanced NSCLC showed better depth of response and response rate to taxanes compared with pemetrexed/gemcitabine (31.2%/60.0% vs 26.6%/45.5%). Our study may aid in selecting the optimal salvage regimen after targeted therapy failure, or the chemo-regimen where targeted therapy has not been a routine option. Further validation is warranted.

Inhibition of Methylglyoxal-Induced AGEs/RAGE Expression Contributes to Dermal Protection by N-Acetyl-L-Cysteine.

BACKGROUND/AIM: Accumulation of advanced glycation end products (AGEs) is a major cause of diabetes mellitus (DM) skin complications. Methylglyoxal (MGO), a reactive dicarbonyl compound, is a crucial intermediate of AGEs generation. N-acetyl-L-cysteine (NAC), an active ingredient of some medicines, can induce endogenous GSH and hydrogen sulfide generation, and set off a condensation reaction with MGO. However, there is rare evidence to show NAC can alleviate DM-induced skin injury through inhibition of AGEs generation or toxicity. The present study aimed to observe the effects of NAC on MGO-induced inflammatory injury and investigate the roles of AGEs and its receptor (RAGE) in NAC's dermal protection in human HaCaT keratinocytes. METHODS: The cells were exposed to MGO to simulate a high MGO status in diabetic blood or tissues. The content of AGEs in serum or cell medium was measured with ELISA. The protective effects of NAC against MGO-induce injury were evaluated by administration before MGO one hour, in virtue of cell viability, mitochondrial membrane potential, inflammation reaction, nuclear factor (NF)-κB activation, matrix metalloproteinase (MMP)-9 expression, as well as cellular behavioral function. RESULTS: We found the AGEs levels of patients with DM were elevated comparing with healthy volunteers. The in vitro AGEs generation was also able to be enhanced by the exposure of HaCaT cells to MGO, which reduced dose-dependently cellular viability, damaged mitochondrial function, triggered secretion of interleukin (IL)-6 and IL-8, activated NF-κB and upregulated MMP-9 expression. Furthermore, the exposure caused cellular adhesion and migration dysfunction, as well as collagen type I inhibition. Importantly, before the exposure to MGO, the preconditioning with NAC significantly attenuated MGO-induced AGEs generation, improved cellular viability and mitochondrial function, partially reversed the overexpression of proinflammatory factors and MMP-9, as well as the activation of NF-κB. Lastly, NAC blocked MGO-induced RAGE upregulation, and inhibition of RAGE with its neutralizing antibody significantly alleviated MGO-induced NF-κB activation, MMP-9 upregulation and inflammatory injury in HaCaT cells. CONCLUSION: The present work indicates the administration of NAC can prevent MGO-induced dermal inflammatory injury through inhibition of AGEs/RAGE signal, which may provide a basal support for the treatment of diabetic skin complications with NAC-containing medicines in the future.

Identifying genetically-supported drug repurposing targets for non-small cell lung cancer through mendelian randomization of the druggable genome.

Background: Lung cancer is responsible for most cancer-related deaths, and non-small cell lung cancer (NSCLC) accounts for the majority of cases. Targeted therapy has made promising advancements in systemic treatment for NSCLC over the last two decades, but inadequate drug targets with clinically proven survival benefits limit its universal application in clinical practice compared to chemotherapy and immunotherapy. There is an urgent need to explore new drug targets to expand the beneficiary group. This study aims to identify druggable genes and to predict the efficacy and prognostic value of the corresponding targeted drugs in NSCLC. Methods: Two-sample mendelian randomization (MR) of druggable genes was performed to predict the efficacy of their corresponding targeted therapy for NSCLC. Subsequent sensitivity analyses were performed to assess potential confounders. Accessible RNA sequencing data were incorporated for subsequent verifications, and Kaplan-Meier survival curves of different gene expressions were used to explore the prognostic value of candidate druggable genes. Results: MR screening encompassing 4,863 expression quantitative trait loci (eQTL) and 1,072 protein quantitative trait loci (pQTL, with 453 proteins overlapping) were performed. Seven candidate druggable genes were identified, including CD33, ENG, ICOSLG and IL18R1 for lung adenocarcinoma, and VSIR, FSTL1 and TIMP2 for lung squamous cell carcinoma. The results were validated by further transcriptomic investigations. Conclusions: Drugs targeting genetically supported genomes are considerably more likely to yield promising efficacy and succeed in clinical trials. We provide compelling genetic evidence to prioritize drug development for NSCLC.

Loratidine is associated with improved prognosis and exerts antineoplastic effects via apoptotic and pyroptotic crosstalk in lung cancer.

BACKGROUND: Tumor-associated inflammation suggests that anti-inflammatory medication could be beneficial in cancer therapy. Loratadine, an antihistamine, has demonstrated improved survival in certain cancers. However, the anticancer mechanisms of loratadine in lung cancer remain unclear. OBJECTIVE: This study investigates the anticancer mechanisms of loratadine in lung cancer. METHODS: A retrospective cohort of 4,522 lung cancer patients from 2006 to 2018 was analyzed to identify noncancer drug exposures associated with prognosis. Cellular experiments, animal models, and RNA-seq data analysis were employed to validate the findings and explore the antitumor effects of loratadine. RESULTS: This retrospective study revealed a positive association between loratadine administration and ameliorated survival outcomes in lung cancer patients, exhibiting dose dependency. Rigorous in vitro and in vivo assays demonstrated that apoptosis induction and epithelial-mesenchymal transition (EMT) reduction were stimulated by moderate loratadine concentrations, whereas pyroptosis was triggered by elevated dosages. Intriguingly, loratadine was found to augment PPARγ levels, which acted as a gasdermin D transcription promoter and caspase-8 activation enhancer. Consequently, loratadine might incite a sophisticated interplay between apoptosis and pyroptosis, facilitated by the pivotal role of caspase-8. CONCLUSION: Loratadine use is linked to enhanced survival in lung cancer patients, potentially due to its role in modulating the interplay between apoptosis and pyroptosis via caspase-8.

Landscape of C-MET overexpression in non-small cell lung cancer: a large-scale study of clinicomolecular features and prognosis based on Chinese data.

Background: Real-world data on C-MET protein overexpression in non-small cell lung cancer (NSCLC) patients, particularly among the Asian Chinese population, are limited. Objectives: This study aimed to evaluate the clinicomolecular characteristics and prognosis of C-MET overexpression in Chinese NSCLC patients, focusing on those with positive C-MET overexpression (immunohistochemistry (IHC) 3+). Design: A retrospective and observational study. Methods: Data were collected from NSCLC patients diagnosed at the First Affiliated Hospital of Guangzhou Medical University between November 2006 and April 2021. We identified C-MET overexpression using IHC and C-MET overexpression positivity was defined as IHC 3+ with ⩾50% tumor cells. Additionally, patient genotypes were collected for subgroup analysis. Results: Data from 9785 NSCLC patients were collected. C-MET (-) accounted for 5% (503/9785), C-MET (+) for 27% (2654/9785), C-MET (++) for 36% (3464/9785), and C-MET (+++) for 32% (3164/9785). Genetic testing was available for 4326 patients. Wild-type was observed in 37% (1591 cases), with epidermal growth factor receptor (EGFR) abnormalities being the most common at 49% (2127 cases). Positive C-MET overexpression correlated significantly with women (p < 0.001), early-stage (p = 0.003), adenocarcinoma (p < 0.001), and driver mutations (p < 0.001). Patients with anaplastic lymphoma kinase (ALK) alterations had a higher occurrence of C-MET overexpression positivity (57.1%). Positive C-MET overexpression was significantly associated with EGFR (p < 0.001), ALK (p < 0.001), and KRAS alterations (p = 0.024). Compared to C-MET overexpression (IHC 0), C-MET overexpression (IHC 2+) (hazard ratio (HR) = 0.455, p < 0.001) and C-MET overexpression (IHC 3+) (HR = 0.569, p < 0.001) were correlated with better overall survival in overall NSCLC patients, especially for C-MET overexpression (IHC 2+). Conclusion: Our study elucidates the clinicomolecular characteristics and prognosis of C-MET overexpression in NSCLC patients, particularly those with positive C-MET overexpression (IHC 3+). This provides insight into the prevalence of C-MET overexpression in Chinese NSCLC patients and offers a basis for considering C-MET overexpression as a prognostic and predictive marker in NSCLC.

Molecular and immune characterization of Chinese early-stage non-squamous non-small cell lung cancer: a multi-omics cohort study.

Background: Albeit considered with superior survival, around 30% of the early-stage non-squamous non-small cell lung cancer (Ns-NSCLC) patients relapse within 5 years, suggesting unique biology. However, the biological characteristics of early-stage Ns-NSCLC, especially in the Chinese population, are still unclear. Methods: Multi-omics interrogation of early-stage Ns-NSCLC (stage I-III), paired blood samples and normal lung tissues (n=76) by whole-exome sequencing (WES), RNA sequencing, and T-cell receptor (TCR) sequencing were conducted. Results: An average of 128 exonic mutations were identified, and the most frequently mutant gene was EGFR (55%), followed by TP53 (37%) and TTN (26%). Mutations in MUC17, ABCA2, PDE4DIP, and MYO18B predicted significantly unfavorable disease-free survival (DFS). Moreover, cytobands amplifications in 8q24.3, 14q13.1, 14q11.2, and deletion in 3p21.1 were highlighted in recurrent cases. Higher incidence of human leukocyte antigen loss of heterozygosity (HLA-LOH), higher tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were identified in ever-smokers than never-smokers. HLA-LOH also correlated with higher TMB, TNB, intratumoral heterogeneity (ITH), and whole chromosomal instability (wCIN) scores. Interestingly, higher ITH was an independent predictor of better DFS in early-stage Ns-NSCLC. Up-regulation of immune-related genes, including CRABP2, ULBP2, IL31RA, and IL1A, independently portended a dismal prognosis. Enhanced TCR diversity of peripheral blood mononuclear cells (PBMCs) predicted better prognosis, indicative of a noninvasive method for relapse surveillance. Eventually, seven machine-learning (ML) algorithms were employed to evaluate the predictive accuracy of clinical, genomic, transcriptomic, and TCR repertoire data on DFS, showing that clinical and RNA features combination in the random forest (RF) algorithm, with area under the curve (AUC) of 97.5% and 83.3% in the training and testing cohort, respectively, significantly outperformed other methods. Conclusions: This study comprehensively profiled the genomic, transcriptomic, and TCR repertoire spectrums of Chinese early-stage Ns-NSCLC, shedding light on biological underpinnings and candidate biomarkers for prognosis development.

[Results of Lung Cancer Screening with Low-dose Computed Tomography 
and Exploration of Risk Factors in Guangzhou].

BACKGROUND: Both of lung cancer incidence and mortality rank first among all cancers in China. Previous lung cancer screening trials were mostly selective screening for high-risk groups such as smokers. Non-smoking women accounted for a considerable proportion of lung cancer cases in Asia. This study aimed to evaluate the outcome of community-based mass screening in Guangzhou and identify the high-risk factors for lung cancer. METHODS: Residents aged 40-74 years in Guangzhou were screened with low-dose computed tomography (LDCT) for lung cancer and the pulmonary nodules were classified and managed according to China National Lung Cancer Screening Guideline with Low-dose Computed Tomography (2018 version). The detection rate of positive nodules was calculated. Before the LDCT examination, residents were required to complete a "lung cancer risk factors questionnaire". The risk factors of the questionnaire were analyzed by least absolute shrinkage and selection operator (LASSO) penalized Logistic regression analysis. RESULTS: A total of 6256 residents were included in this study. 1228 positive nodules (19.63%) and 117 lung cancers were confirmed, including 6 cases of Tis, 103 cases of stage I (accounting for 88.03% of lung cancer). The results of LASSO penalized Logistic regression analysis indicated that age ≥50 yr (OR=1.07, 95%CI: 1.06-1.07), history of cancer (OR=3.29, 95%CI: 3.22-3.37), textile industry (OR=1.10, 95%CI: 1.08-1.13), use coal for cooking in childhood (OR=1.14, 95%CI: 1.13-1.16) and food allergy (OR=1.10, 95%CI: 1.07-1.13) were risk factors of lung cancer for female in this district. CONCLUSIONS: This study highlighted that numerous early stages of lung cancer cases were detected by LDCT, which could be applied to screening of lung cancer in women. Besides, age ≥50 yr, personal history of cancer, textile industry and use coal for cooking in childhood are risk factors for women in this district, which suggested that it's high time to raise the awareness of early lung cancer screening in this group.

Development of a genome atlas for discriminating benign, preinvasive, and invasive lung nodules.

To tackle misdiagnosis in lung cancer screening with low-dose computed tomography (LDCT), we aimed to compile a genome atlas for differentiating benign, preinvasive, and invasive lung nodules and characterize their molecular pathogenesis. We collected 432 lung nodule tissue samples from Chinese patients, spanning benign, atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IA). We performed comprehensive sequencing, examining somatic variants, gene expressions, and methylation levels. Our findings uncovered EGFR and TP53 mutations as key drivers in - early lung cancer development, with EGFR mutation frequency increasing with disease progression. Both EGFR mutations and EGF/EGFR hypo-methylation activated the EGFR pathway, fueling cancer growth. Transcriptome analysis identified four lung nodule subtypes (G1-4) with distinct molecular features and immune cell infiltrations: EGFR-driven G1, EGFR/TP53 co-mutation G2, inflamed G3, stem-like G4. Estrogen/androgen response was associated with the EGFR pathway, proposing a new therapy combining tyrosine kinase inhibitors with antiestrogens. Preinvasive nodules exhibited stem cell pathway enrichment, potentially hindering invasion. Epigenetic regulation of various genes was essential for lung cancer initiation and development. This study provides insights into the molecular mechanism of neoplastic progression and identifies potential diagnostic biomarkers and therapeutic targets for lung cancer.