Advances in lung cancer screening and early detection

Disposable Zirconium trisulfide-Reduced graphene oxide modified conducting thread based electrochemical biosensor for lung cancer diagnosis

Flexible technology in sensors have received much attention in monitoring of human health through various physiological indicators. Thus, it drawn a lot of interest in the development of flexible substrate for the diagnosis of various diseases via analysis of analytes. Present work focusses on the development of ecofriendly, portable, flexible, conducting thread (Th) and used as smart substrate for fabrication of biosensor towards ultrasensitive detection of the lung cancer biomarker (cytoskeleton-associated protein 4; CKAP4). The zirconium trisulfide-reduced graphene oxide nanocomposite and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) modified cotton thread based biosensor was fabricated via dip coating method. Next, successive immobilization of monoclonal antibodies of CKAP4 (anti-CKAP4) and bovine serum albumin (BSA) was performed via drop cast approach using fabricated electrode [nZrS3@rGO/PEDOT:PSS/Th]. The response of fabricated electrode (BSA/anti-CKAP4/ZrS3@rGO/PEDOT:PSS/Th) was recorded electrochemically versus CKAP4 concentration via chronoamperometry (CA). The results showed wider linear detection range of 6.25-800 pg mL-1, excellent sensitivity of 85.2 µA[log(pg mL-1)]-1cm-2 with good stability up to 42 days. The response of fabricated biosensor was supported by investigating response of CKAP4 biomarker present in patients of lung cancer (concentration as determined through enzyme-linked immunosorbent assay) and obtained results exhibited excellent correlation with that of standard samples.

Pulmonary Rehabilitation for Diseases Other Than COPD

Review the current literature regarding pulmonary rehabilitation (PR) for non-chronic obstructive pulmonary disease (COPD) diagnoses and what the evidence is regarding expected outcomes based on disease manifestations. Literature search was performed using PubMed database from March 2024 to June 2024. Terms included "pulmonary rehabilitation" and "exercise training" in conjunction with key words "interstitial lung disease (ILD)," "idiopathic pulmonary fibrosis," "asthma," "bronchiectasis," "post-acute sequalae of SARS-CoV-2 (PASC)," "long COVID," "pulmonary hypertension (PH)," and "lung cancer." Results were filtered for English language, randomized controlled trial, clinical trial, observational trial, meta-analysis, and guidelines. Emphasis was placed on more recent publications since prior reviews, where applicable. The abundance of literature involved ILD, where studies have demonstrated significant improvements in exercise capacity, health-related quality of life (HRQoL), and dyspnea, despite heterogeneity of diseases; benefits are similar to those seen with COPD. Those with milder disease have more sustained benefits longer term. Patients with asthma benefit in severe disease, lower exercise activity, elevated body mass index, or when comorbid conditions are present, and breathing exercises can improve symptoms of breathlessness. Patients with PASC have a multitude of symptoms and lack benefits in HRQoL measurements; PR improves performance on post-COVID-19 functional status scale, a more comprehensive measurement of symptoms. Those with bronchiectasis benefit from PR when airflow limitation or exacerbations are impacting symptoms and HRQoL. Those with stable PH can improve their exertional capacity without change in disease severity. PR reduces perioperative complications in those with lung cancer and preserve fitness during treatment.

A clinically effective model based on cell-free DNA methylation and low-dose CT for risk stratification of pulmonary nodules

Accurate, non-invasive, and cost-effective tools are needed to assist pulmonary nodule diagnosis and management due to increasing detection by low-dose computed tomography (LDCT). We perform genome-wide methylation sequencing on malignant and non-malignant lung tissues and designed a panel of 263 differential DNA methylation regions, which is used for targeted methylation sequencing on blood cell-free DNA (cfDNA) in two prospectively collected and retrospectively analyzed multicenter cohorts. We develop and optimize an integrative model for risk stratification of pulmonary nodules based on 40 cfDNA methylation biomarkers, age, and five simple computed tomography (CT) imaging features using machine learning approaches and validate its good performance in two cohorts. Using the two-threshold strategy can effectively reduce unnecessary invasive surgeries, overtreatment costs, and injury for patients with benign nodules while advising immediate treatment for patients with lung cancer, which can potentially improve the overall diagnosis of lung cancer following LDCT/CT screening.

USP10 promotes cell proliferation, migration, and invasion in NSCLC through deubiquitination and stabilization of EIF4G1

Lung cancer is one of the most common types of malignant cancer worldwide, causing a serious social and economic burden. It is classified into non-small cell lung cancer (NSCLC) and small cell lung cancer, with NSCLC accounting for 80-85% of cases. Eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) is highly expressed in NSCLC, playing an important role in regulating tumor growth, angiogenesis, malignant transformation, and phagocytosis. Ubiquitin-specific protease 10 (USP10) functions as a deubiquitinating enzyme to regulate substrate protein deubiquitination and reverse the ubiquitin proteasome degradation pathway. Our previous study identified an interaction between EIF4G1 and USP10; however, their regulatory mechanism remains unclear. Herein, we found that USP10 positively regulates EIF4G1 in NSCLC cells. An in vivo ubiquitination assay demonstrated deubiquitination of EIF4G1 by USP10, which reversed the ubiquitin proteasomal degradation of EIF4G1, thereby increasing its stability. Upregulation of EIF4G1 promoted cell proliferation, migration, and invasion in NSCLC cells. The current study not only reveals a novel mechanism through which USP10 positively regulates EIF4G1 in NSCLC, but also demonstrates the potential of USP10 as a therapeutic target to treat NSCLC.

Targeting the lung tumour stroma: harnessing nanoparticles for effective therapeutic interventions

Lung cancer remains an influential global health concern, necessitating the development of innovative therapeutic strategies. The tumour stroma, which is known as tumour microenvironment (TME) has a central impact on tumour expansion and treatment resistance. The stroma of lung tumours consists of numerous cells and molecules that shape an environment for tumour expansion. This environment not only protects tumoral cells against immune system attacks but also enables tumour stroma to attenuate the action of antitumor drugs. This stroma consists of stromal cells like cancer-associated fibroblasts (CAFs), suppressive immune cells, and cytotoxic immune cells. Additionally, the presence of stem cells, endothelial cells and pericytes can facilitate tumour volume expansion. Nanoparticles are hopeful tools for targeted drug delivery because of their extraordinary properties and their capacity to devastate biological obstacles. This review article provides a comprehensive overview of contemporary advancements in targeting the lung tumour stroma using nanoparticles. Various nanoparticle-based approaches, including passive and active targeting, and stimuli-responsive systems, highlighting their potential to improve drug delivery efficiency. Additionally, the role of nanotechnology in modulating the tumour stroma by targeting key components such as immune cells, extracellular matrix (ECM), hypoxia, and suppressive elements in the lung tumour stroma.

Advances in early detection of non-small cell lung cancer: A comprehensive review

BACKGROUND

Lung cancer has the highest mortality rate among malignancies globally. In addition, due to the growing number of smokers there is considerable concern over its growth. Early detection is an essential step towards reducing complications in this regard and helps to ensure the most effective treatment, reduce health care costs, and increase survival rates.

AIMS

To define the most efficient and cost-effective method of early detection in clinical practice.

MATERIALS AND METHODS

We collected the Information used to write this review by searching papers through PUBMED that were published from 2021 to 2024, mainly systematic reviews, meta-analyses and clinical-trials. We also included other older but notable papers that we found essential and valuable for understanding.

RESULTS

EB-OCT has a varied sensitivity and specificity-an average of 94.3% and 89.9 for each. On the other hand, detecting biomarkers via liquid biopsy carries an average sensitivity of 91.4% for RNA molecules detection, and 97% for combined methylated DNA panels. Moreover, CTCs detection did not prove to have a significant role as a screening method due to the rarity of CTCs in the bloodstream thus the need for more blood samples and for enrichment techniques.

DISCUSSION

Although low-dose CT scan (LDCT) is the current golden standard screening procedure, it is accompanied by a highly false positive rate. In comparison to other radiological screening methods, Endobronchial optical coherence tomography (EB-OCT) has shown a noticeable advantage with a significant degree of accuracy in distinguishing between subtypes of non-small cell lung cancer. Moreover, numerous biomarkers, including RNA molecules, circulating tumor cells, CTCs, and methylated DNA, have been studied in the literature. Many of these biomarkers have a specific high sensitivity and specificity, making them potential candidates for future early detection approaches.

CONCLUSION

LDCT is still the golden standard and the only recommended screening procedure for its high sensitivity and specificity and proven cost-effectiveness. Nevertheless, the notable false positive results acquired during the LDCT examination caused a presumed concern, which drives researchers to investigate better screening procedures and approaches, particularly with the rise of the AI era or by combining two methods in a well-studied screening program like LDCT and liquid biopsy. we suggest conducting more clinical studies on larger populations with a clear demographical target and adopting approaches for combining one of these new methods with LDCT to decrease false-positive cases in early detection.

Precision lung cancer screening from CT scans using a VGG16-based convolutional neural network

Objective

The research aims to develop an advanced and precise lung cancer screening model based on Convolutional Neural Networks (CNN).

Methods

Based on the health medical big data platform of Shandong University, we developed a VGG16-Based CNN lung cancer screening model. This model was trained using the Computed Tomography scans data of patients from Pingyi Traditional Chinese Medicine Hospital in Shandong Province, from January to February 2023. Data augmentation techniques, including random resizing, cropping, horizontal flipping, color jitter, random rotation and normalization, were applied to improve model generalization. We used five-fold cross-validation to robustly assess performance. The model was fine-tuned with an SGD optimizer (learning rate 0.001, momentum 0.9, and L2 regularization) and a learning rate scheduler. Dropout layers were added to prevent the model from relying too heavily on specific neurons, enhancing its ability to generalize. Early stopping was implemented when validation loss did not decrease over 10 epochs. In addition, we evaluated the model's performance with Area Under the Curve (AUC), Classification accuracy, Positive Predictive Value (PPV), and Negative Predictive Value (NPV), Sensitivity, Specificity and F1 score. External validation used an independent dataset from the same hospital, covering January to February 2022.

Results

The training and validation loss and accuracy over iterations show that both accuracy metrics peak at over 0.9 by iteration 15, prompting early stopping to prevent overfitting. Based on five-fold cross-validation, the ROC curves for the VGG16-Based CNN model, demonstrate an AUC of 0.963 ± 0.004, highlighting its excellent diagnostic capability. Confusion matrices provide average metrics with a classification accuracy of 0.917 ± 0.004, PPV of 0.868 ± 0.015, NPV of 0.931 ± 0.003, Sensitivity of 0.776 ± 0.01, Specificity of 0.962 ± 0.005 and F1 score of 0.819 ± 0.008, respectively. External validation confirmed the model's robustness across different patient populations and imaging conditions.

Conclusion

The VGG16-Based CNN lung screening model constructed in this study can effectively identify lung tumors, demonstrating reliability and effectiveness in real-world medical settings, and providing strong theoretical and empirical support for its use in lung cancer screening.

Circ_0006949 as a potential non-invasive diagnosis biomarker promotes the proliferation of NSCLC cells via miR-4673/GLUL axis

The 5-year survival for non-small cell lung cancer (NSCLC) remains <20 %, primarily due to the early symptoms of lung cancer are inconspicuous. Prompt identification and medical intervention could serve as effective strategies for mitigating the death rate. We therefore set out to identify biomarkers to help diagnose NSCLC. CircRNA microarray and qRT-PCR reveal that sputum circ_0006949 is a potential biomarker for the early diagnosis and therapy of NSCLC, which can enhance the proliferation and clone formation, regulate the cell cycle, and accelerate the migration and invasion of NSCLC cells. Circ_0006949 and miR-4673 are predominantly co-localized in the cytoplasm of NSCLC cell lines and tissues; it upregulates GLUL by adsorption of miR-4673 through competing endogenous RNAs mechanism. The circ_0006949/miR-4673/GLUL axis exerts pro-cancer effects in vitro and in vivo. Circ_0006949 can boost GLUL catalytic activity, and they are highly expressed in NSCLC tissues and correlate with poor prognosis. In summary, circ_0006949 is a potential biomarker for the early diagnosis and therapy of NSCLC. This novel sputum circRNA is statistically more predictive than conventional serum markers for NSCLC diagnosis. Non-invasive detection of patients with early-stage NSCLC using sputum has shown good potential for routine diagnosis and possible screening.

Recent Developments in Aerosol Pulmonary Drug Delivery: New Technologies, New Cargos, and New Targets

There is nothing like a global pandemic to motivate the need for improved respiratory treatments and mucosal vaccines. Stimulated by the COVID-19 pandemic, pulmonary aerosol drug delivery has seen a flourish of activity, building on the prior decades of innovation in particle engineering, inhaler device technologies, and clinical understanding. As such, the field has expanded into new directions and is working toward the efficient delivery of increasingly complex cargos to address a wider range of respiratory diseases. This review seeks to highlight recent innovations in approaches to personalize inhalation drug delivery, deliver complex cargos, and diversify the targets treated and prevented through pulmonary drug delivery. We aim to inform readers of the emerging efforts within the field and predict where future breakthroughs are expected to impact the treatment of respiratory diseases.

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.

Association of CCND1 rs9344 polymorphism with lung cancer susceptibility and clinical outcomes: a case-control study

BACKGROUND

Cyclin D1 (CCND1) plays a pivotal role in cancer susceptibility and the platinum-based chemotherapy response. This study aims to assess the relationship between a common polymorphism (rs9344 G > A) in CCND1 gene with cancer susceptibility, platinum-based chemotherapy response, toxicities and prognosis of patients with lung cancer.

METHODS

This study involved 498 lung cancer patients and 213 healthy controls. Among them, 467 patients received at least two cycles of platinum-based chemotherapy. Unconditional logistical regression analysis and meta-analysis were performed to evaluate the associations.

RESULTS

The lung adenocarcinoma risk was significantly higher in patients with AA than GG + GA genotype (adjusted OR = 1.755, 95%CI = 1.057-2.912, P = 0.030). CCND1 rs9344 was significantly correlated with platinum-based therapy response in patients receiving PP regimen (additive model: adjusted OR = 1.926, 95%CI = 1.029-3.605, P = 0.040; recessive model: adjusted OR = 11.340, 95%CI = 1.428-90.100, P = 0.022) and in the ADC subgroups (recessive model: adjusted OR = 3.345, 95%CI = 1.276-8.765, P = 0.014). Furthermore, an increased risk of overall toxicity was found in NSCLC patients (additive model: adjusted OR = 1.395, 95%CI = 1.025-1.897, P = 0.034; recessive model: adjusted OR = 1.852, 95%CI = 1.088-3.152, P = 0.023), especially ADC subgroups (additive model: adjusted OR = 1.547, 95%CI = 1.015-2.359, P = 0.043; recessive model: adjusted OR = 2.030, 95%CI = 1.017-4.052, P = 0.045). Additionally, CCND1 rs9344 was associated with an increased risk of gastrointestinal toxicity in non-smokers (recessive model: adjusted OR = 2.620, 95%CI = 1.083-6.336, P = 0.035). Non-significant differences were observed in the 5-year overall survival rate between CCND1 rs9344 genotypes. A meta-analysis of 5432 cases and 6452 control samples did not find a significant association between lung cancer risk and CCND1 rs9344 polymorphism.

CONCLUSION

This study suggests that in the Chinese population, CCND1 rs9344 could potentially serve as a candidate biomarker for cancer susceptibility and treatment outcomes in specific subgroups of patients.

Does the revised LDCT lung cancer screening guideline bridge the racial disparities gap: Results from the health and retirement study

PURPOSE

This study examined racial/ethnic disparities in lung cancer screening eligibility rates using 2013 US Preventive Services Task Force (USPSTF) guidelines for lung cancer with low-dose computed tomography (LDCT) and the revised 2021 guidelines.

METHODS

The study utilized a retrospective and cross-sectional research design by analyzing data from the Health and Retirement Study (HRS). N = 2,823 respondents aged 50-80 who self-reported current smoking were included in the analyses. Binary logistic regression analysis was conducted to examine the changed status of LDCT screening eligibility based on the revised 2021 guidelines by race/ethnicity after adjusting for respondent demographics.

RESULTS

Our study found substantial increases in screening eligibility rates across racial and ethnic groups when comparing the original and revised guidelines. The largest increase was observed among Black people (174%), Hispanics (152%), those in the other category (118%), and Whites who smoke (80.8%). When comparing original screening guidelines to revised guidelines, Whites who smoke had the highest percentage of changes from "not eligible" to "eligible" (28.3%), followed by individuals in the "other" category (28.1%), Black people (23.2%) and Hispanics who smoke (18.3%) (p < 0.001). Binary logistic regression results further showed that Black people who smoke (OR = 0.71, p = 0.001), as well as Hispanics who smoke (OR=0.54, p < 0.001), were less likely to change from not eligible to eligible for screening compared to Whites who smoke after adopting the revised screening guidelines. Based on the absolute differences in screening eligibility rates between Whites and other racial/ethnic groups, the disparities may have widened under the new guidelines, particularly with larger absolute differences observed between Whites, Black people, and Hispanics.

CONCLUSIONS

Our study highlights racial/ethnic disparities in LDCT screening eligibility among people who currently smoke. While the revised USPSTF guidelines increased screening eligibility for racial and ethnic minorities, they did not eliminate these disparities and may have widened under the new guidelines. Targeted interventions and policies are necessary to address barriers faced by underrepresented populations and promote equitable access to lung cancer screening.

Cutting-Edge Therapies for Lung Cancer

Lung cancer remains a formidable global health challenge that necessitates inventive strategies to improve its therapeutic outcomes. The conventional treatments, including surgery, chemotherapy, and radiation, have demonstrated limitations in achieving sustained responses. Therefore, exploring novel approaches encompasses a range of interventions that show promise in enhancing the outcomes for patients with advanced or refractory cases of lung cancer. These groundbreaking interventions can potentially overcome cancer resistance and offer personalized solutions. Despite the rapid evolution of emerging lung cancer therapies, persistent challenges such as resistance, toxicity, and patient selection underscore the need for continued development. Consequently, the landscape of lung cancer therapy is transforming with the introduction of precision medicine, immunotherapy, and innovative therapeutic modalities. Additionally, a multifaceted approach involving combination therapies integrating targeted agents, immunotherapies, or traditional cytotoxic treatments addresses the heterogeneity of lung cancer while minimizing its adverse effects. This review provides a brief overview of the latest emerging therapies that are reshaping the landscape of lung cancer treatment. As these novel treatments progress through clinical trials are integrated into standard care, the potential for more effective, targeted, and personalized lung cancer therapies comes into focus, instilling renewed hope for patients facing challenging diagnoses.

A PET/CT radiomics model for predicting distant metastasis in early-stage non-small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study

OBJECTIVES

Stereotactic body radiotherapy (SBRT) is a treatment option for patients with early-stage non-small cell lung cancer (NSCLC) who are unfit for surgery. Some patients may experience distant metastasis. This study aimed to develop and validate a radiomics model for predicting distant metastasis in patients with early-stage NSCLC treated with SBRT.

METHODS

Patients at five institutions were enrolled in this study. Radiomics features were extracted based on the PET/CT images. After feature selection in the training set (from Tianjin), CT-based and PET-based radiomics signatures were built. Models based on CT and PET signatures were built and validated using external datasets (from Zhejiang, Zhengzhou, Shandong, and Shanghai). An integrated model that included CT and PET radiomic signatures was developed. The performance of the proposed model was evaluated in terms of its discrimination, calibration, and clinical utility. Multivariate logistic regression was used to calculate the probability of distant metastases. The cutoff value was obtained using the receiver operator characteristic curve (ROC), and the patients were divided into high- and low-risk groups. Kaplan-Meier analysis was used to evaluate the distant metastasis-free survival (DMFS) of different risk groups.

RESULTS

In total, 228 patients were enrolled. The median follow-up time was 31.4 (2.0-111.4) months. The model based on CT radiomics signatures had an area under the curve (AUC) of 0.819 in the training set (n = 139) and 0.786 in the external dataset (n = 89). The PET radiomics model had an AUC of 0.763 for the training set and 0.804 for the external dataset. The model combining CT and PET radiomics had an AUC of 0.835 for the training set and 0.819 for the external dataset. The combined model showed a moderate calibration and a positive net benefit. When the probability of distant metastasis was greater than 0.19, the patient was considered to be at high risk. The DMFS of patients with high- and low-risk was significantly stratified (P < 0.001).

CONCLUSIONS

The proposed PET/CT radiomics model can be used to predict distant metastasis in patients with early-stage NSCLC treated with SBRT and provide a reference for clinical decision-making. In this study, the model was established by combining CT and PET radiomics signatures in a moderate-quantity training cohort of early-stage NSCLC patients treated with SBRT and was successfully validated in independent cohorts. Physicians could use this easy-to-use model to assess the risk of distant metastasis after SBRT. Identifying subgroups of patients with different risk factors for distant metastasis is useful for guiding personalized treatment approaches.

[Effectiveness Evaluation of Low-dose Spiral Computed Tomography for Lung Cancer Screening in Minhang District of Shanghai]

BACKGROUND

Low-dose spiral computed tomography (LDCT) has been recommended for lung cancer screening in high-risk populations. However, evidence from Chinese populations was limited due to the different criteria for high-risk populations and the short-term follow-up period. This study aimed to evaluate the effectiveness in Chinese adults based on the Lung Cancer Screening Program in Minhang District of Shanghai initiated in 2013.

METHODS

A total of 26,124 subjects aged 40 years or above were enrolled in the Lung Cancer Screening Program during the period of 2013 and 2017. Results of LDCT examination, and screen-detected cancer cases in all participants were obtained from the Reporting System of the Lung Cancer Screening Program. The newly-diagnosed cases and their vital status up to December 31, 2020 were identified through a record linkage with the Shanghai Cancer Registry and the Shanghai Vital Statistics. Standardized incidence ratio (SIR) and 95%CI were calculated using the local population at ages of 40 or above as the reference. Proportions of early-stage cancer (stage 0-I), pathological types, and 5-year observed survival rates of lung cancer cases were estimated and compared between the cases derived from the screened and non-screened populations. Cox regression models were applied to evaluate the hazard ratio (HR) and 95%CI of LDCT screening with all-cause death of the lung cancer cases.

RESULTS

The crude and age-standardized incidence of lung cancer in screened population were 373.3 (95%CI: 343.1-406.1) and 70.3 per 100,000 person-years, respectively, with an SIR of 1.8 (95%CI: 1.6-1.9), which was observed to decrease with following-up time. The early-stage cancer accounted for 49.4% of all lung cancer cases derived from the screened population, significantly higher than 38.4% in cases from the non-screened population during the same period (P<0.05). The proportion of lung adenocarcinoma (40.7% vs 35.9%) and 5-year survival rate (53.7% vs 41.5%) were also significantly higher in the cases from the screened population (all P<0.05). LDCT screening was associated with 30% (HR=0.7, 95%CI: 0.6-0.8) reduced all-cause deaths of the cases.

CONCLUSIONS

The participants of the screening program are at high-risk of lung cancer. LDCT favors the early-detection of lung cancer and improves 5-year survival of the screened cases, indicating a great potential of LDCT in reducing the disease burden of lung cancer in Chinese populations.

Combination drug therapy by herbal nanomedicine prevent multidrug resistance protein 1: promote apoptosis in Lung Carcinoma

Given the numerous adverse effects of lung cancer treatment, more research on non-toxic medications is urgently needed. Curcumin (CUR) and berberine (BBR) combat drug resistance by controlling the expression of multidrug resistant pump (MDR1). Fascinatingly, combining these medications increases the effectiveness of preventing lung cancer. Their low solubility and poor stability, however, restrict their therapeutic efficacy. Because of the improved bioavailability and increased encapsulation effectiveness of water-insoluble medicines, surfactant-based nanovesicles have recently received a great deal of attention. The current study sought to elucidate the Combination drug therapy by herbal nanomedicine prevent multidrug resistance protein 1: promote apoptosis in Lung Carcinoma. The impact of several tween (20, 60, and 80) types with varied hydrophobic tails on BBR/CUR-TNV was evaluated. Additionally, the MDR1 activity and apoptosis rate of the BBR/CUR-TNV combination therapy were assessed. The encapsulation effectiveness of TNV was affected by the type of tween. With the TNV made from tween 60, cholesterol, and PEG (47.5: 47.5:5), more encapsulation effectiveness was attained. By combining CUR with BBR, especially when given in TNV, apoptosis increased. Additionally, when CUR and BBR were administered in combination, they significantly reduced the risk of MDR1 development. The current work suggests that the delivery of berberine and curcumin as a combination medication therapy via tween-based nanovesicles may be a potential lung cancer treatment.

Bronchoalveolar lavage fluid assessment facilitates precision medicine for lung cancer

Lung cancer is the most common and fatal malignant disease worldwide and has the highest mortality rate among tumor-related causes of death. Early diagnosis and precision medicine can significantly improve the survival rate and prognosis of lung cancer patients. At present, the clinical diagnosis of lung cancer is challenging due to a lack of effective non-invasive detection methods and biomarkers, and treatment is primarily hindered by drug resistance and high tumor heterogeneity. Liquid biopsy is a method for detecting circulating biomarkers in the blood and other body fluids containing genetic information from primary tumor tissues. Bronchoalveolar lavage fluid (BALF) is a potential liquid biopsy medium that is rich in a variety of bioactive substances and cell components. BALF contains information on the key characteristics of tumors, including the tumor subtype, gene mutation type, and tumor environment, thus BALF may be used as a diagnostic supplement to lung biopsy. In this review, the current research on BALF in the diagnosis, treatment, and prognosis of lung cancer is summarized. The advantages and disadvantages of different components of BALF, including cells, cell-free DNA, extracellular vesicles, and microRNA are introduced. In particular, the great potential of extracellular vesicles in precision diagnosis and detection of drug-resistant for lung cancer is highlighted. In addition, the performance of liquid biopsies with different body fluid sources in lung cancer detection are compared to facilitate more selective studies involving BALF, thereby promoting the application of BALF for precision medicine in lung cancer patients in the future.

Quantification of diffuse parenchymal lung disease in non-small cell lung cancer patients with definitive concurrent chemoradiation therapy for predicting radiation pneumonitis

BACKGROUND

We sought to quantify diffuse parenchymal lung disease (DPLD) extent using quantitative computed tomography (CT) analysis and to investigate its association with radiation pneumonitis (RP) development in non-small cell lung cancer (NSCLC) patients receiving definitive concurrent chemoradiation therapy (CCRT).

METHODS

A total of 82 NSCLC patients undergoing definitive CCRT were included in this prospective cohort study. Pretreatment CT scans were analyzed using quantitative CT analysis software. Low-attenuation area (LAA) features based on lung density and texture features reflecting interstitial lung disease (ILD) were extracted from the whole lung. Clinical and dosimetric factors were also evaluated. RP development was assessed using the Common Terminology Criteria for Adverse Events version 5.0. Univariable and multivariable logistic regression analyses were performed to identify independent risk factors for grade ≥3 (≥GR3) RP.

RESULTS

RP was identified in 68 patients (73.9%), with nine patients (10.9%) experiencing ≥GR3 RP. Univariable logistic regression analysis identified excess kurtosis and high-attenuation area (HAA)_volume (cc) as significantly associated with ≥GR3 RP. Multivariable logistic regression analysis showed that the combined use of imaging features and clinical factors (forced expiratory volume in 1 second [FEV1], forced vital capacity [FVC], and CHEMO regimen) demonstrated the best performance (area under the receiver operating characteristic curve = 0.924) in predicting ≥GR3 RP.

CONCLUSION

Quantified imaging features of DPLD obtained from pretreatment CT scans would predict the occurrence of RP in NSCLC patients undergoing definitive CCRT. Combining imaging features with clinical factors could improve the accuracy of the predictive model for severe RP.

Circulating cell-free DNA sequencing for early detection of lung cancer

INTRODUCTION

Lung cancer is a leading cause of death in patients with cancer. Early diagnosis is crucial to improve the prognosis of patients with lung cancer. Plasma circulating cell-free DNA (cfDNA) contains comprehensive genetic and epigenetic information from tissues throughout the body, suggesting that early detection of lung cancer can be done non-invasively, conveniently, and cost-effectively using high-sensitivity techniques such as sequencing.

AREAS COVERED

In this review, we summarize the latest technological innovations, coupled with next-generation sequencing (NGS), regarding genomic alterations, methylation, and fragmentomic features of cfDNA for the early detection of lung cancer, as well as their clinical advances. Additionally, we discuss the suitability of study designs for diagnostic accuracy evaluation for different target populations and clinical questions.

EXPERT OPINION

Currently, cfDNA-based early screening and diagnosis of lung cancer faces many challenges, such as unsatisfactory performance, lack of quality control standards, and poor repeatability. However, the progress of several large prospective studies employing epigenetic features has shown promising predictive performance, which has inspired cfDNA sequencing for future clinical applications. Furthermore, the development of multi-omics markers for lung cancer, including genome-wide methylation and fragmentomics, is expected to play an increasingly important role in the future.

Recent advance of next-generation sequencing in patients with lung cancer

INTRODUCTION

Precision medicine based on the driver genes mutation status is the current systemic therapeutic paradigm in patients with lung cancer. Next-generation sequencing (NGS) has emerged as a powerful platform for molecular diagnosis by virtue of high-throughput and massively parallel sequencing. Liquid biopsy also enabled the dynamic monitoring and comprehensive profiling of lung cancer in a noninvasive manner. However, challenges remain in the field of technology and clinical applications, especially in the era of immunotherapy.

AREAS COVERED

Here, we update the role of NGS in the context of lung cancer screening, molecular diagnosis, predictive and prognostic biomarkers, and guiding personalized treatment.

EXPERT OPINION

The NGS application for actable genomic alternation has greatly changed the therapeutic landscape in patients with lung cancer including perioperative setting and advanced stage. Meanwhile, emerging evidence has shown the potential of other applications such as early screening and detection, and MRD. However, challenges remain such as the lack of standardized protocols across different platforms and bioinformatics analysis pipelines, and the complexity of interpreting and leveraging numerous genomic mutation messages for therapy selection. Future research is needed to overcome these challenges and expand the applications of NGS to other aspects such as immunotherapy.

The Association of IFN-γ, TNF-α, and Interleukins in Bronchoalveolar Lavage Fluid with Lung Cancer: A Prospective Analysis

Lung cancer is a leading cause of cancer-related mortality worldwide. Identifying novel diagnostic and prognostic biomarkers is essential for improving patient outcomes. This study aimed to investigate the predictive role of cytokines from bronchoalveolar lavage fluid (BALF) in lung cancer diagnosis and prognosis. A prospective study was conducted on 33 patients with suspected lung cancer, divided into inflammatory and non-inflammatory BALF groups. Inflammatory markers in BALF were assessed, and their association with lung cancer risk was analyzed using receiver operating characteristic (ROC) plot analysis, sensitivity and specificity percentages, and regression analysis. Statistically significant differences were observed between the inflammatory and non-inflammatory groups for several inflammatory markers, including IFN-gamma, IL-1b, IL-2, IL-6, IL-10, and IL-12p70. In the follow-up analysis, significant differences persisted for IFN-gamma, IL-1b, IL-2, IL-4, and IL-6. ROC plot analysis revealed that IL-12p70 had the highest area under the curve (AUC) value (0.702), followed by IL-2 (0.682), IL-6 (0.620), IL-4 (0.611), TNF-alpha (0.609), IL-10 (0.604), IL-1b (0.635), and IFN-gamma (0.521). IL-6 showed the highest sensitivity (73%), and IL-1b had the highest specificity (69%). Regression analysis demonstrated that IL-6 (cut-off = 25 pg/mL) and IL-12p70 (cut-off = 30 pg/mL) had the highest odds ratios for lung cancer risk, at 5.09 (95% CI: 2.38-9.24, p < 0.001) and 4.31 (95% CI: 1.85-8.16, p < 0.001), respectively. Cytokines from BALF, particularly IL-6 and IL-12p70, show potential as diagnostic and prognostic biomarkers for lung cancer. Further studies with larger cohorts are warranted to confirm these findings and elucidate the clinical implications of these markers in lung cancer management.

Loss of BCAA catabolism enhances Rab1A-mTORC1 signaling activity and promotes tumor proliferation in NSCLC

BACKGROUND

Non-small cell lung cancer (NSCLC) is a leading cause of cancer death. Branched-chain amino acid (BCAA) homeostasis is important for normal physiological metabolism. Branched-chain keto acid dehydrogenase kinase (BCKDK) is a rate-limiting enzyme involved in BCAA degradation. BCAA metabolism has been highlighted in human cancers. The aberrant activation of mTORC1 has been implicated in tumor progression. Rab1A is a small GTPase, an activator of mTORC1, and an oncogene. This study aimed to reveal the specific role of BCKDK-BCAA-Rab1A-mTORC1 signaling in NSCLC.

METHODS

We analyzed a cohort of 79 patients with NSCLC and 79 healthy controls. Plasma BCAA assays, immunohistochemistry, and network and pathway analyses were performed. The stable cell lines BCKDK-KD, BCKDK-OV A549, and H1299 were constructed. BCKDK, Rab1A, p-S6 and S6 were detected using western blotting to explore their molecular mechanisms of action in NSCLC. The effects of BCAA and BCKDK on the apoptosis and proliferation of H1299 cells were detected by cell function assays.

RESULTS

We demonstrated that NSCLC was primarily involved in BCAA degradation. Therefore, combining BCAA, CEA, and Cyfra21-1 is clinically useful for treating NSCLC. We observed a significant increase in BCAA levels, downregulation of BCKDHA expression, and upregulation of BCKDK expression in NSCLC cells. BCKDK promotes proliferation and inhibits apoptosis in NSCLC cells, and we observed that BCKDK affected Rab1A and p-S6 in A549 and H1299 cells via BCAA modulation. Leucine affected Rab1A and p-S6 in A549 and H1299 cells and affected the apoptosis rate of H1299 cells. In conclusion, BCKDK enhances Rab1A-mTORC1 signaling and promotes tumor proliferation by suppressing BCAA catabolism in NSCLC, suggesting a new biomarker for the early diagnosis and identification of metabolism-based targeted approaches for patients with NSCLC.

An Aptamer against MNK1 for Non-Small Cell Lung Cancer Treatment

Lung cancer is the leading cause of cancer-related death worldwide. Its late diagnosis and consequently poor survival make necessary the search for new therapeutic targets. The mitogen-activated protein kinase (MAPK)-interacting kinase 1 (MNK1) is overexpressed in lung cancer and correlates with poor overall survival in non-small cell lung cancer (NSCLC) patients. The previously identified and optimized aptamer from our laboratory against MNK1, apMNKQ2, showed promising results as an antitumor drug in breast cancer in vitro and in vivo. Thus, the present study shows the antitumor potential of apMNKQ2 in another type of cancer where MNK1 plays a significant role, such as NSCLC. The effect of apMNKQ2 in lung cancer was studied with viability, toxicity, clonogenic, migration, invasion, and in vivo efficacy assays. Our results show that apMNKQ2 arrests the cell cycle and reduces viability, colony formation, migration, invasion, and epithelial-mesenchymal transition (EMT) processes in NSCLC cells. In addition, apMNKQ2 reduces tumor growth in an A549-cell line NSCLC xenograft model. In summary, targeting MNK1 with a specific aptamer may provide an innovative strategy for lung cancer treatment.

LncRNA FOXD2-AS1 Increased Proliferation and Invasion of Lung Adenocarcinoma via Cell-Cycle Regulation

Background

Long non-coding RNA FOXD2 antisense RNA 1 (FOXD2-AS1) has been reported in many malignancies. However, the molecular mechanism of many actions is not clarified. This study was conducted to investigate the function of FOXD2-AS1 in lung adenocarcinoma and its molecular mechanism.

Methods

Bioinformatics and in vitro analysis including RT-qPCR, CFU, CCK8, Transwell, Cell Apoptosis and Cell Cycle Assay were used for the analysis of gene expression and related effects.

Results

It revealed increased expression of lncRNA FOXD2-AS1 in lung adenocarcinoma cell lines (A549 cells), and abundant expression of lncRNA FOXD2-AS1 was also observed in the acquired lung adenocarcinoma tissues. In vitro results showed that knockdown of lncRNA FOXD2-AS1 in A549 cells weakened cell proliferation, invasion and increased apoptosis. At the same time, we found that reducing the expression of lncRNA FOXD2-AS1 caused cell cycle arrest in the G1/S phase. Differential gene analysis of lung adenocarcinoma and adjacent normal tissues showed that the cell cycle and its related process regulation were significantly enriched. Gene Set Enrichment Analysis (GSEA) analysis showed that miR-206, miR-143, lL6-JAK-STAT3 signalling pathway, STAT3, E2F targets, EZH2, P53 signalling pathway and E2F3 targets interacting with lncRNA FOXD2-AS1 were also enriched.

Conclusion

This study demonstrates the role and mechanism of the lncRNA FOXD2-AS1 in lung adenocarcinoma and provides a better understanding for the treatment of lung adenocarcinoma, which indicates that interfering with lncRNA FOXD2-AS1 expression may be a novel strategy.

Image-Guided Percutaneous and Transarterial Therapies for Primary and Metastatic Lung Cancer

Lung cancer is the leading cause of cancer mortality in the world. A significant proportion of patients with lung cancer are not candidates for surgery and must resort to other treatment alternatives. Rapid technological advancements in fields like interventional radiology have paved the way for valid treatment modalities like image-guided percutaneous and transarterial therapies for treatment of both primary and metastatic lung cancer. The rationale of ablative therapies relies on the fact that focused delivery of energy induces tumor destruction and pathological necrosis. Image-guided percutaneous thermal ablation therapies are established techniques in the local treatment of hepatic, renal, bone, thyroid, or uterine lesions. In the lung, the 3 main indications for lung ablation include local curative intent, a strategy to achieve a chemoholiday in oligometastatic disease, and recently, oligoprogressive disease. Transarterial therapies include a set of catheter-based treatments that involve delivering embolic and/or chemotherapeutic agents directed into the target tumor via the supplying arteries. This article provides a comprehensive review of the various techniques available and discusses their applications and associated complications in primary and metastatic lung cancer.