Exhaled Volatile Organic Compounds Detection in Pneumonia Screening: A Comprehensive Meta-analysis.

BACKGROUND: Pneumonia is a common lower respiratory tract infection, and early diagnosis is crucial for timely treatment and improved prognosis. Traditional diagnostic methods for pneumonia, such as chest imaging and microbiological examinations, have certain limitations. Exhaled volatile organic compounds (VOCs) detection, as an emerging non-invasive diagnostic technique, has shown potential application value in pneumonia screening. METHOD: A systematic search was conducted on PubMed, Embase, Cochrane Library, and Web of Science, with the retrieval time up to March 2024. The inclusion criteria were diagnostic studies evaluating exhaled VOCs detection for the diagnosis of pneumonia, regardless of the trial design type. A meta-analysis was performed using a bivariate model for sensitivity and specificity. RESULTS: A total of 14 diagnostic studies were included in this meta-analysis. The pooled results demonstrated that exhaled VOCs detection had a combined sensitivity of 0.94 (95% CI: 0.92-0.95) and a combined specificity of 0.83 (95% CI: 0.81-0.84) in pneumonia screening, with an area under the summary receiver operating characteristic (SROC) curve (AUC) of 0.96. The pooled diagnostic odds ratio (DOR) was 104.37 (95% CI: 27.93-390.03), and the pooled positive and negative likelihood ratios (LR) were 8.98 (95% CI: 3.88-20.80) and 0.11 (95% CI: 0.05-0.22), indicating a high diagnostic performance. CONCLUSION: This study highlights the potential of exhaled VOCs detection as an effective, non-invasive screening method for pneumonia, which could facilitate future diagnosis in pneumonia. Further high-quality, large-scale studies are required to confirm the clinical utility of exhaled VOCs detection in pneumonia screening. STUDY REGISTRATION: PROSPERO, Review no. CRD42024520498.

Exhaled VOC detection in lung cancer screening: a comprehensive meta-analysis.

BACKGROUND: Lung cancer (LC), characterized by high incidence and mortality rates, presents a significant challenge in oncology. Despite advancements in treatments, early detection remains crucial for improving patient outcomes. The accuracy of screening for LC by detecting volatile organic compounds (VOCs) in exhaled breath remains to be determined. METHODS: Our systematic review, following PRISMA guidelines and analyzing data from 25 studies up to October 1, 2023, evaluates the effectiveness of different techniques in detecting VOCs. We registered the review protocol with PROSPERO and performed a systematic search in PubMed, EMBASE and Web of Science. Reviewers screened the studies' titles/abstracts and full texts, and used QUADAS-2 tool for quality assessment. Then performed meta-analysis by adopting a bivariate model for sensitivity and specificity. RESULTS: This study explores the potential of VOCs in exhaled breath as biomarkers for LC screening, offering a non-invasive alternative to traditional methods. In all studies, exhaled VOCs discriminated LC from controls. The meta-analysis indicates an integrated sensitivity and specificity of 85% and 86%, respectively, with an AUC of 0.93 for VOC detection. We also conducted a systematic analysis of the source of the substance with the highest frequency of occurrence in the tested compounds. Despite the promising results, variability in study quality and methodological challenges highlight the need for further research. CONCLUSION: This review emphasizes the potential of VOC analysis as a cost-effective, non-invasive screening tool for early LC detection, which could significantly improve patient management and survival rates.

Spatial whole exome sequencing reveals the genetic features of highly-aggressive components in lung adenocarcinoma.

In invasive lung adenocarcinoma (LUAD), patients with micropapillary (MIP) or solid (SOL) components had a significantly poorer prognosis than those with only lepidic (LEP), acinar (ACI) or papillary (PAP) components. It is interesting to explore the genetic features of different histologic subtypes, especially the highly aggressive components. Based on a cohort of 5,933 patients, this study observed that in different tumor size groups, LUAD with MIP/SOL components showed a different prevalence, and patients with ALK alteration or TP53 mutations had a higher probability of developing MIP/SOL components. To control individual differences, this research used spatial whole-exome sequencing (WES) via laser-capture microdissection of five patients harboring these five coexistent components and identified genetic features among different histologic components of the same tumor. In tracing the evolution of components, we found that titin (TTN) mutation might serve as a crucial intratumor potential driver for MIP/SOL components, which was validated by a cohort of 146 LUAD patients undergoing bulk WES. Functional analysis revealed that TTN mutations enriched the complement and coagulation cascades, which correlated with the pathway of cell adhesion, migration, and proliferation. Collectively, the histologic subtypes of invasive LUAD were genetically different, and certain trunk genotypes might synergize with branching TTN mutation to develop highly aggressive components.

Albumin-bilirubin grade as a predictor of survival in hepatocellular carcinoma patients with thrombocytopenia.

BACKGROUND: The models for assessing liver function, mainly the Child-Pugh (CP), albuminbilirubin (ALBI), and platelet-ALBI (PALBI) classifications, have been validated for use in estimating the prognosis of hepatocellular carcinoma (HCC) patients. However, thrombocytopenia is a common finding and may influence the prognostic value of the three models in HCC. AIM: To investigate and compare the prognostic performance of the above three models in thrombocytopenic HCC patients. METHODS: A total of 135 patients with thrombocytopenic HCC who underwent radical surgery were retrospectively analyzed. Preoperative scores on the CP, ALBI and PALBI classifications were estimated accordingly. Kaplan-Meier curves with log-rank tests and Cox regression models were used to explore the significant factors associated with overall survival (OS) and recurrence-free survival (RFS). RESULTS: The preoperative platelet counts were significantly different among the CP, ALBI and PALBI groups. After a median follow-up of 28 mo, 39.3% (53/135) of the patients experienced postoperative recurrence, and 36.3% (49/135) died. Univariate analysis suggested that α-fetoprotein levels, tumor size, vascular invasion, and ALBI grade were significant predictors of OS and RFS. According to the multivariate Cox regression model, ALBI was identified as an independent prognostic factor. However, CP and PALBI grades were not statistically significant prognostic indicators. CONCLUSION: The ALBI grade, rather than CP or PALBI grade, is a significant prognostic indicator for thrombocytopenic HCC patients.

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.

The activity and immune dynamics of PD-1 inhibition on high-risk pulmonary ground glass opacity lesions: insights from a single-arm, phase II trial.

Immune checkpoint inhibitors targeting the programmed cell death-1 (PD-1) protein significantly improve survival in patients with advanced non-small-cell lung cancer (NSCLC), but its impact on early-stage ground-glass opacity (GGO) lesions remains unclear. This is a single-arm, phase II trial (NCT04026841) using Simon's optimal two-stage design, of which 4 doses of sintilimab (200 mg per 3 weeks) were administrated in 36 enrolled multiple primary lung cancer (MPLC) patients with persistent high-risk (Lung-RADS category 4 or had progressed within 6 months) GGOs. The primary endpoint was objective response rate (ORR). T/B/NK-cell subpopulations, TCR-seq, cytokines, exosomal RNA, and multiplexed immunohistochemistry (mIHC) were monitored and compared between responders and non-responders. Finally, two intent-to-treat (ITT) lesions (pure-GGO or GGO-predominant) showed responses (ORR: 5.6%, 2/36), and no patients had progressive disease (PD). No grade 3-5 TRAEs occurred. The total response rate considering two ITT lesions and three non-intent-to-treat (NITT) lesions (pure-solid or solid-predominant) was 13.9% (5/36). The proportion of CD8+ T cells, the ratio of CD8+/CD4+, and the TCR clonality value were significantly higher in the peripheral blood of responders before treatment and decreased over time. Correspondingly, the mIHC analysis showed more CD8+ T cells infiltrated in responders. Besides, responders' cytokine concentrations of EGF and CTLA-4 increased during treatment. The exosomal expression of fatty acid metabolism and oxidative phosphorylation gene signatures were down-regulated among responders. Collectively, PD-1 inhibitor showed certain activity on high-risk pulmonary GGO lesions without safety concerns. Such effects were associated with specific T-cell re-distribution, EGF/CTLA-4 cytokine compensation, and regulation of metabolism pathways.

Spatiotemporal distribution of mediastinal neoplasms: A comprehensive multi-center study.

OBJECTIVES: Mediastinal neoplasms are typical but uncommon thoracic diseases with increasing incidence and unfavorable prognoses. A comprehensive understanding of their spatiotemporal distribution is essential for accurate diagnosis and timely treatment. However, previous studies are limited in scale and data coverage. Therefore, this study aims to elucidate the distribution of mediastinal lesions, offering valuable insights into this disease. MATERIALS AND METHODS: This multi-center, hospital-based observational study included 20 nationwide institutions. A retrospective search of electronic medical records from January 1st, 2009, to December 31st, 2020, was conducted, collecting sociodemographic data, computed tomography images, and pathologic diagnoses. Analysis focused on age, sex, time, location, and geographical region. Comparative assessments were made with global data from a multi-center database. RESULTS: Among 7,765 cases, thymomas (30.7%), benign mediastinal cysts (23.4%), and neurogenic tumors (10.0%) were predominant. Distribution varied across mediastinal compartments, with thymomas (39.6%), benign cysts (28.1%), and neurogenic tumors (51.9%) most prevalent in the prevascular, visceral, and paravertebral mediastinum, respectively. Age-specific variations were notable, with germ cell tumors prominent in patients under 18 and aged 18-29, while thymomas were more common in patients over 30. The composition of mediastinal lesions across different regions of China remained relatively consistent, but it differs from that of the global population. CONCLUSION: This study revealed significant heterogeneity in the spatiotemporal distribution of mediastinal neoplasms. These findings provide useful demographic data when considering the differential diagnosis of mediastinal lesions, and would be beneficial for tailoring disease prevention and control strategies.

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.

Impact of lymphadenectomy extent on immunotherapy efficacy in postresectional recurred non-small cell lung cancer: a multi-institutional retrospective cohort study.

BACKGROUND: Lymph node (LN) dissection is a common procedure for non-small cell lung cancer (NSCLC) to ascertain disease severity and treatment options. However, murine studies have indicated that excising tumor-draining LNs diminished immunotherapy effectiveness, though its applicability to clinical patients remains uncertain. Hence, the authors aim to illustrate the immunological implications of LN dissection by analyzing the impact of dissected LN (DLN) count on immunotherapy efficacy, and to propose a novel 'immunotherapy-driven' LN dissection strategy. MATERIALS AND METHODS: The authors conducted a retrospective analysis of NSCLC patients underwent anti-PD-1 immunotherapy for recurrence between 2018 and 2020, assessing outcomes based on DLN count stratification. RESULTS: A total of 144 patients were included, of whom 59 had a DLN count less than or equal to 16 (median, IQR: 11, 7-13); 66 had a DLN count greater than 16 (median, IQR: 23, 19-29). With a median follow-up time of 14.3 months (95% CI: 11.0-17.6), the overall median progression-free survival (PFS) was 7.9 (95% CI: 4.1-11.7) months, 11.7 (95% CI: 7.9-15.6) months in the combination therapy subgroup, and 4.8 (95% CI: 3.1-6.4) months in the immunotherapy alone subgroup, respectively. In multivariable Cox analysis, DLN count less than or equal to 16 is associated with an improved PFS in all cohorts [primary cohort: HR=0.26 (95% CI: 0.07-0.89), P =0.03]; [validation cohort: HR=0.46 (95% CI: 0.22-0.96), P =0.04]; [entire cohort: HR=0.53 (95% CI: 0.32-0.89), P =0.02]. The prognostic benefit of DLN count less than or equal to 16 was more significant in immunotherapy alone, no adjuvant treatment, pN1, female, and squamous carcinoma subgroups. A higher level of CD8+ central memory T cell (Tcm) within LNs was associated with improved PFS (HR: 0.235, 95% CI: 0.065-0.845, P =0.027). CONCLUSIONS: An elevated DLN count (cutoff: 16) was associated with poorer immunotherapy efficacy in recurrent NSCLC, especially pronounced in the immunotherapy alone subgroup. CD8+Tcm proportions in LNs may also impact immunotherapy efficacy. Therefore, for patients planned for adjuvant immunotherapy, a precise rather than expanded lymphadenectomy strategy to preserve immune-depending LNs is recommended.

The impact of adjuvant EGFR-TKIs and 14-gene molecular assay on stage I non-small cell lung cancer with sensitive EGFR mutations.

Background: Currently, the role of EGFR-TKIs as adjuvant therapy for stage I, especially IA NSCLC, after surgical resection remains unclear. We aimed to compare the effect of adjuvant EGFR-TKIs with observation in such patients by incorporating an established 14-gene molecular assay for risk stratification. Methods: This retrospective cohort study was conducted at the First Affiliated Hospital of Guangzhou Medical University (Study ID: ChNCRCRD-2022-GZ01). From March 2013 to February 2019, completely resected stage I NSCLC (8th TNM staging) patients with sensitive EGFR mutation were included. Patients with eligible samples for molecular risk stratification were subjected to the 14-gene prognostic assay. Inverse probability of treatment weighting (IPTW) was employed to minimize imbalances in baseline characteristics. Findings: A total of 227 stage I NSCLC patients were enrolled, with 55 in EGFR-TKI group and 172 in the observation group. The median duration of follow-up was 78.4 months. After IPTW, the 5-year DFS (HR = 0.30, 95% CI, 0.14-0.67; P = 0.003) and OS (HR = 0.26, 95% CI, 0.07-0.96; P = 0.044) of the EGFR-TKI group were significantly better than the observation group. For subgroup analyses, adjuvant EGFR-TKIs were associated with favorable 5-year DFS rates in both IA (100.0% vs. 84.5%; P = 0.007), and IB group (98.8% vs. 75.3%; P = 0.008). The 14-gene assay was performed in 180 patients. Among intermediate-high-risk patients, EGFR-TKIs were associated with a significant improvement in 5-year DFS rates compared to observation (96.0% vs. 70.5%; P = 0.012), while no difference was found in low-risk patients (100.0% vs. 94.9%; P = 0.360). Interpretation: Our study suggested that adjuvant EGFR-TKI might improve DFS and OS of stage IA and IB EGFR-mutated NSCLC, and the 14-gene molecular assay could help patients that would benefit the most from treatment. Funding: This work was supported by China National Science Foundation (82022048, 82373121).

Cellular dynamics in tumour microenvironment along with lung cancer progression underscore spatial and evolutionary heterogeneity of neutrophil.

BACKGROUND: The cellular dynamics in the tumour microenvironment (TME) along with non-small cell lung cancer (NSCLC) progression remain unclear. METHODS: Multiplex immunofluorescence test detecting 10 immune-related markers on 553 primary tumour (PT) samples of NSCLC was conducted and spatial information in TME was assessed by the StarDist depth learning model. The single-cell transcriptomic atlas of PT (n = 4) and paired tumour-draining lymph nodes (TDLNs) (n = 5 for tumour-invaded, n = 3 for tumour-free) microenvironment was profiled. Various bioinformatics analyses based on Gene Expression Omnibus, TCGA and Array-Express databases were also used to validate the discoveries. RESULTS: Spatial distances of CD4+ T cells-CD38+ T cells, CD4+ T cells-neutrophils and CD38+ T cells-neutrophils prolonged and they were replaced by CD163+ macrophages in PT along with tumour progression. Neutrophils showed unique stage and location-dependent prognostic effects. A high abundance of stromal neutrophils improved disease-free survival in the early-stage, whereas high intratumoural neutrophil infiltrates predicted poor prognosis in the mid-to-late-stage. Significant molecular and functional reprogramming in PT and TDLN microenvironments was observed. Diverse interaction networks mediated by neutrophils were found between positive and negative TDLNs. Five phenotypically and functionally heterogeneous subtypes of tumour-associated neutrophil (TAN) were further identified by pseudotime analysis, including TAN-0 with antigen-presenting function, TAN-1 with strong expression of interferon (IFN)-stimulated genes, the pro-tumour TAN-2 subcluster, the classical subset (TAN-3) and the pro-inflammatory subtype (TAN-4). Loss of IFN-stimulated signature and growing angiogenesis activity were discovered along the transitional trajectory. Eventually, a robust six neutrophil differentiation relevant genes-based model was established, showing that low-risk patients had longer overall survival time and may respond better to immunotherapy. CONCLUSIONS: The cellular composition, spatial location, molecular and functional changes in PT and TDLN microenvironments along with NSCLC progression were deciphered, highlighting the immunoregulatory roles and evolutionary heterogeneity of TANs.

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.

"Major pathologic response" in lymph nodes: a modified nodal classification for non-small cell lung cancer patients treated with neoadjuvant immunochemotherapy.

We aim to examine the prognostic value of major pathologic response in metastatic lymph nodes (mLN-MPR) after immunochemotherapy in non-small cell lung cancer (NSCLC), and demonstrate the pathological characteristic of regression in mLN. Adult patients consecutively undergone neoadjuvant immunochemotherapy and radical-intent surgery for initial stage cIII NSCLC between 2020 and 2021 were included. Hematoxylin- and eosin-stained slides of paraffinembedded sections of the degree of pathologic response in the primary tumor (PT) and its paired involved LNs were reviewed. Imaging mass cytometry was conducted to quantify the immunological status. With 10% as residual viable tumor (RVT) cutoff, mLN-MPR (HR: 0.34, 95%CI: 0.14-0.78; P = 0.011, ref: mLN-MPR(-)) showed more significant correlation with DFS than ypN0 (HR: 0.40, 95%CI: 0.17-0.94; P = 0.036, ref: ypN1-N2). And mLN-MPR combined with PT-MPR, compared with ypN stage combined with PT-MPR (p-value: 0.030 vs. 0.117), can better distinguished the DFS curves of the 4 subgroups of patients. mLN-MPR(+)/PT-MPR(+) patients had the best prognosis compared with other subgroups. Pathologic responses of RVT in PT and paired regional LNs [MPR inconsistency rate: 21/53 (39.6%)], and across different LNs could be inconsistent, especially in squamous cell carcinoma. RVT% in mLNs after immunochemotherapy appeared to be polarized [16 (30.2%) cases with RVT ≥ 70%; 34 (64.2%) with RVT ≤ 10%]. Partial regression of LN metastasis could present with distinct immune subtypes: immune-inflamed or immune-evacuation subtype, and the former presented with higher CD3, CD8, and PD-1 expression in the invasive margin. mLN-MPR demonstrated a potential prognostic value in predicting DFS in patients treated with neoadjuvant immunochemotherapy, but further research is needed to validate its usefulness for other survival outcomes, including OS.

Intratumoral tertiary lymphoid structure (TLS) maturation is influenced by draining lymph nodes of lung cancer.

BACKGROUND: Tertiary lymphoid structure (TLS) is an organized infiltration of immune cells, showing features of germinal center (GC) commonly seen in secondary lymphoid organs. However, its relationship with tumor-draining lymph nodes (TDLNs) has not been studied and we hypothesized that TDLN may influence maturation of intratumoral TLS in non-small cell lung cancer (NSCLC). METHODS: Tissue slides of 616 patients that had undergone surgeries were examined. Cox proportional hazard regression model was used to assess risk factors of patients' survival, and logistic regression model was used for their relationship with TLS. Single-cell RNA-sequencing (scRNA-seq) was employed to explore transcriptomic features of TDLNs. Immunohistochemistry, multiplex immunofluorescence and flow cytometry were performed to analyze cellular composition. Cellular components of NSCLC samples from The Cancer Genome Atlas database were inferred with Microenvironment Cell Populations-counter (MCP-counter) method. Murine NSCLC models were used to dissect underlying mechanisms for relationship between TDLN and TLS maturation. RESULTS: While GC+ TLS was associated with better prognosis, GC- TLS was not. TDLN metastasis reduced the prognostic relevance of TLS, and was associated with less GC formation. Primary tumor sites showed reduced B cell infiltration in TDLN-positive patients, and scRNA-seq revealed diminished memory B cell formation in tumor-invaded TDLNs, together with an emphasis on weakened interferon (IFN)-γ response. Murine NSCLC models revealed that IFN-γ signaling is involved in memory B cell differentiation in TDLNs and GC formation in primary tumors. CONCLUSIONS: Our research emphasizes the influence of TDLN on intratumoral TLS maturation and suggests a role of memory B cells and IFN-γ signaling in this communication.

Development and validation of a deep transfer learning-based multivariable survival model to predict overall survival in lung cancer.

Background: Numerous deep learning-based survival models are being developed for various diseases, but those that incorporate both deep learning and transfer learning are scarce. Deep learning-based models may not perform optimally in real-world populations due to variations in variables and characteristics. Transfer learning, on the other hand, enables a model developed for one domain to be adapted for a related domain. Our objective was to integrate deep learning and transfer learning to create a multivariable survival model for lung cancer. Methods: We collected data from 601,480 lung cancer patients in the Surveillance, Epidemiology, and End Results (SEER) database and 4,512 lung cancer patients in the First Affiliated Hospital of Guangzhou Medical University (GYFY) database. The primary model was trained with the SEER database, internally validated with a dataset from SEER, and externally validated through transfer learning with the GYFY database. The performance of the model was compared with a traditional Cox model by C-indexes. We also explored the model's performance in the setting of missing data and generated the artificial intelligence (AI) certainty of the prediction. Results: The C-indexes in the training dataset (SEER full sample) with DeepSurv and Cox model were 0.792 (0.791-0.792) and 0.714 (0.713-0.715), respectively. The values were 0.727 (0.704-0.750) and 0.692 (0.666-0.718) after applying the trained model in the test dataset (GYFY). The AI certainty of the DeepSurv model output was from 0.98 to 1. For transfer learning through fine-tuning, the results showed that the test set could achieve a higher C-index (20% vs. 30% fine-tuning data) with more fine-tuning dataset. Besides, the DeepSurv model was more accurate than the traditional Cox model in predicting with missing data, after random data loss of 5%, 10%, 15%, 20%, and median fill-in missing values. Conclusions: The model outperformed the traditional Cox model, was robust with missing data and provided the AI certainty of prediction. It can be used for patient self-evaluation and risk stratification in clinical trials. Researchers can fine-tune the pre-trained model and integrate their own database to explore other prognostic factors.

Risk mapping of lung cancer: a comprehensive appraisal of published meta-analyses incorporating Mendelian randomization studies.

INTRODUCTION: A comprehensive appraisal of published meta-analyses incorporating Mendelian randomization studies was performed to map the different risk factors and assess the causality for lung cancer. METHODS: Systematic reviews and meta-analyses of observational and interventional studies were reviewed based on PubMed, Embase, Web of Science, and Cochrane Library. Mendelian randomization analyses were conducted to validate the causal associations of those various exposures with lung cancer using summary statistics from 10 genome-wide association studies (GWAS) consortia and other GWAS databases in MR-Base platform. RESULTS: In the review of meta-analyses, 105 risk factors associated with lung cancer were identified from 93 articles. It was found that 72 risk factors were nominally significant (P < 0.05) associated with lung cancer. Mendelian randomization analyses were performed to analyze 36 exposures based on 551 SNPs and 4,944,052 individuals, finding that 3 exposures had a consistent risk/protective effect on lung cancer with the results of the meta-analysis. In Mendelian randomization anaylses, smoking (OR 1.44, 95% CI 1.18-1.75; P = 0.001) and blood copper (OR 1.14, 95% CI 1.01-1.29; P = 0.039) significantly associated with increased risk of lung cancer, whereas aspirin use (OR 0.67, 95% CI 0.50-0.89; P = 0.006) showed protective effects. CONCLUSION: This study mapped putative associations of risk factors for lung cancer, revealing the causal hazard effect of smoking, blood copper, and the protective effect of aspirin use in the development of lung cancer. CLINICAL TRIAL REGISTRY: This study is registered with PROSPERO (CRD42020159082).