Integrating predictive coding and a user-centric interface for enhanced auditing and quality in cancer registry data.

Data curation for a hospital-based cancer registry heavily relies on the labor-intensive manual abstraction process by cancer registrars to identify cancer-related information from free-text electronic health records. To streamline this process, a natural language processing system incorporating a hybrid of deep learning-based and rule-based approaches for identifying lung cancer registry-related concepts, along with a symbolic expert system that generates registry coding based on weighted rules, was developed. The system is integrated with the hospital information system at a medical center to provide cancer registrars with a patient journey visualization platform. The embedded system offers a comprehensive view of patient reports annotated with significant registry concepts to facilitate the manual coding process and elevate overall quality. Extensive evaluations, including comparisons with state-of-the-art methods, were conducted using a lung cancer dataset comprising 1428 patients from the medical center. The experimental results illustrate the effectiveness of the developed system, consistently achieving F1-scores of 0.85 and 1.00 across 30 coding items. Registrar feedback highlights the system's reliability as a tool for assisting and auditing the abstraction. By presenting key registry items along the timeline of a patient's reports with accurate code predictions, the system improves the quality of registrar outcomes and reduces the labor resources and time required for data abstraction. Our study highlights advancements in cancer registry coding practices, demonstrating that the proposed hybrid weighted neural-symbolic cancer registry system is reliable and efficient for assisting cancer registrars in the coding workflow and contributing to clinical outcomes.

Microbiome signatures associated with clinical stages of gastric Cancer: whole metagenome shotgun sequencing study.

BACKGROUND: Gastric cancer is one of the global health concerns. A series of studies on the stomach have confirmed the role of the microbiome in shaping gastrointestinal diseases. Delineation of microbiome signatures to distinguish chronic gastritis from gastric cancer will provide a non-invasive preventative and treatment strategy. In this study, we performed whole metagenome shotgun sequencing of fecal samples to enhance the detection of rare bacterial species and increase genome sequence coverage. Additionally, we employed multiple bioinformatics approaches to investigate the potential targets of the microbiome as an indicator of differentiating gastric cancer from chronic gastritis. RESULTS: A total of 65 patients were enrolled, comprising 33 individuals with chronic gastritis and 32 with gastric cancer. Within each group, the chronic gastritis group was sub-grouped into intestinal metaplasia (n = 15) and non-intestinal metaplasia (n = 18); the gastric cancer group, early stage (stages 1 and 2, n = 13) and late stage (stages 3 and 4, n = 19) cancer. No significant differences in alpha and beta diversities were detected among the patient groups. However, in a two-group univariate comparison, higher Fusobacteria abundance was identified in phylum; Fusobacteria presented higher abundance in gastric cancer (LDA scored 4.27, q = 0.041 in LEfSe). Age and sex-adjusted MaAsLin and Random Forest variable of importance (VIMP) analysis in species provided meaningful features; Bacteria_caccae was the most contributing species toward gastric cancer and late-stage cancer (beta:2.43, se:0.891, p:0.008, VIMP score:2.543). In contrast, Bifidobacterium_longum significantly contributed to chronic gastritis (beta:-1.8, se:0.699, p:0.009, VIMP score:1.988). Age, sex, and BMI-adjusted MasAsLin on metabolic pathway analysis showed that GLCMANNANAUT-PWY degradation was higher in gastric cancer and one of the contributing species was Fusobacterium_varium. CONCLUSION: Microbiomes belonging to the pathogenic phylum Fusobacteria and species Bacteroides_caccae and Streptococcus_anginosus can be significant targets for monitoring the progression of gastric cancer. Whereas Bifidobacterium_longum and Lachnospiraceae_bacterium_5_1_63FAA might be protection biomarkers against gastric cancer.

Clinical outcome of bevacizumab or ramucirumab combined with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors as the first line therapy in susceptible EGFR-mutated advanced non-small-cell lung.

Combining epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) with an anti- vascular endothelial growth factor (VEGF) agent, bevacizumab or ramucirumab, is indicated for advanced lung adenocarcinoma harboring EGFR mutation. This study aimed to show the real-world data of combination therapy and compare the effectiveness between bevacizumab and ramucirumab in combination with an EGFR-TKI. This retrospective study enrolled 47 patients diagnosed of stage IV lung adenocarcinoma with exon 19 deletion or L858R point mutation, receiving a first-line EGFR-TKI with anti-VEGF agent, including 34 (72%) and 13 (28%) patients receiving bevacizumab and ramucirumab, respectively. The response rate was similar in both groups (p = 0.38). Patients receiving bevacizumab had similar progression free survival (PFS) as those receiving ramucirumab (median PFS: 21.9 vs. 24.2 months, p = 0.4871); similar finding was noted in overall survival (OS) (median OS: 33.5 months vs. not reached, p = 0.4618). Patients receiving ramucirumab experienced a significantly high-grade hypertension compared to those receiving bevacizumab (p = 0.0351). Multivariable Cox regression analysis found independent risk factors for worse PFS included poorer ECOG performance status, multiple (≥3) metastatic sites, brain metastasis, and pleural metastasis/effusion, while the type of anti-VEGF agent was not a risk factor. Pericardial metastasis/effusion was the only one independent risk factor for worse OS. In summary, ramucirumab may have similar effectiveness as bevacizumab in combination with an EGFR-TKI as first line therapy for advanced lung adenocarcinoma harboring susceptible EGFR mutation. Further large-scale registry-based cohort studies may be needed to validate our findings.

An evolutionary learning-based method for identifying a circulating miRNA signature for breast cancer diagnosis prediction.

Breast cancer (BC) is one of the most commonly diagnosed cancers worldwide. As key regulatory molecules in several biological processes, microRNAs (miRNAs) are potential biomarkers for cancer. Understanding the miRNA markers that can detect BC may improve survival rates and develop new targeted therapeutic strategies. To identify a circulating miRNA signature for diagnostic prediction in patients with BC, we developed an evolutionary learning-based method called BSig. BSig established a compact set of miRNAs as potential markers from 1280 patients with BC and 2686 healthy controls retrieved from the serum miRNA expression profiles for the diagnostic prediction. BSig demonstrated outstanding prediction performance, with an independent test accuracy and area under the receiver operating characteristic curve were 99.90% and 0.99, respectively. We identified 12 miRNAs, including hsa-miR-3185, hsa-miR-3648, hsa-miR-4530, hsa-miR-4763-5p, hsa-miR-5100, hsa-miR-5698, hsa-miR-6124, hsa-miR-6768-5p, hsa-miR-6800-5p, hsa-miR-6807-5p, hsa-miR-642a-3p, and hsa-miR-6836-3p, which significantly contributed towards diagnostic prediction in BC. Moreover, through bioinformatics analysis, this study identified 65 miRNA-target genes specific to BC cell lines. A comprehensive gene-set enrichment analysis was also performed to understand the underlying mechanisms of these target genes. BSig, a tool capable of BC detection and facilitating therapeutic selection, is publicly available at https://github.com/mingjutsai/BSig.

Translating GWAS Findings to Inform Drug Repositioning Strategies for COVID-19 Treatment.

We developed a computational framework that integrates Genome-Wide Association Studies (GWAS) and post-GWAS analyses, designed to facilitate drug repurposing for COVID-19 treatment. The comprehensive approach combines transcriptomic-wide associations, polygenic priority scoring, 3D genomics, viral-host protein-protein interactions, and small-molecule docking. Through GWAS, we identified nine druggable host genes associated with COVID-19 severity and SARS-CoV-2 infection, all of which show differential expression in COVID-19 patients. These genes include IFNAR1, IFNAR2, TYK2, IL10RB, CXCR6, CCR9, and OAS1. We performed an extensive molecular docking analysis of these targets using 553 small molecules derived from five therapeutically enriched categories, namely antibacterials, antivirals, antineoplastics, immunosuppressants, and anti-inflammatories. This analysis, which comprised over 20,000 individual docking analyses, enabled the identification of several promising drug candidates. All results are available via the DockCoV2 database (https://dockcov2.org/drugs/). The computational framework ultimately identified nine potential drug candidates: Peginterferon alfa-2b, Interferon alfa-2b, Interferon beta-1b, Ruxolitinib, Dactinomycin, Rolitetracycline, Irinotecan, Vinblastine, and Oritavancin. While its current focus is on COVID-19, our proposed computational framework can be applied more broadly to assist in drug repurposing efforts for a variety of diseases. Overall, this study underscores the potential of human genetic studies and the utility of a computational framework for drug repurposing in the context of COVID-19 treatment, providing a valuable resource for researchers in this field.

Prognostic microRNA signature for estimating survival in patients with hepatocellular carcinoma.

OBJECTIVE: Hepatocellular carcinoma (HCC) is one of the leading cancer types with increasing annual incidence and high mortality in the USA. MicroRNAs (miRNAs) have emerged as valuable prognostic indicators in cancer patients. To identify a miRNA signature predictive of survival in patients with HCC, we developed a machine learning-based HCC survival estimation method, HCCse, using the miRNA expression profiles of 122 patients with HCC. METHODS: The HCCse method was designed using an optimal feature selection algorithm incorporated with support vector regression. RESULTS: HCCse identified a robust miRNA signature consisting of 32 miRNAs and obtained a mean correlation coefficient (R) and mean absolute error (MAE) of 0.87 ±â€…0.02 and 0.73 years between the actual and estimated survival times of patients with HCC; and the jackknife test achieved an R and MAE of 0.73 and 0.97 years between actual and estimated survival times, respectively. The identified signature has seven prognostic miRNAs (hsa-miR-146a-3p, hsa-miR-200a-3p, hsa-miR-652-3p, hsa-miR-34a-3p, hsa-miR-132-5p, hsa-miR-1301-3p and hsa-miR-374b-3p) and four diagnostic miRNAs (hsa-miR-1301-3p, hsa-miR-17-5p, hsa-miR-34a-3p and hsa-miR-200a-3p). Notably, three of these miRNAs, hsa-miR-200a-3p, hsa-miR-1301-3p and hsa-miR-17-5p, also displayed association with tumor stage, further emphasizing their clinical relevance. Furthermore, we performed pathway enrichment analysis and found that the target genes of the identified miRNA signature were significantly enriched in the hepatitis B pathway, suggesting its potential involvement in HCC pathogenesis. CONCLUSIONS: Our study developed HCCse, a machine learning-based method, to predict survival in HCC patients using miRNA expression profiles. We identified a robust miRNA signature of 32 miRNAs with prognostic and diagnostic value, highlighting their clinical relevance in HCC management and potential involvement in HCC pathogenesis.

Artificial intelligence-driven pan-cancer analysis reveals miRNA signatures for cancer stage prediction.

The ability to detect cancer at an early stage in patients who would benefit from effective therapy is a key factor in increasing survivability. This work proposes an evolutionary supervised learning method called CancerSig to identify cancer stage-specific microRNA (miRNA) signatures for early cancer predictions. CancerSig established a compact panel of miRNA signatures as potential markers from 4,667 patients with 15 different types of cancers for the cancer stage prediction, and achieved a mean performance: 10-fold cross-validation accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of 84.27% ± 6.31%, 0.81 ± 0.12, 0.80 ± 0.10, and 0.80 ± 0.06, respectively. The pan-cancer analysis of miRNA signatures suggested that three miRNAs, hsa-let-7i-3p, hsa-miR-362-3p, and hsa-miR-3651, contributed significantly toward stage prediction across 8 cancers, and each of the 67 miRNAs of the panel was a biomarker of stage prediction in more than one cancer. CancerSig may serve as the basis for cancer screening and therapeutic selection..

Pulmonary alveolar proteinosis in Taiwan.

BACKGROUND/PURPOSE: Pulmonary alveolar proteinosis (PAP) is rare disease manifested as alveolar macrophage dysfunction and abnormal accumulation of surfactant protein in the alveoli. In this nationwide, population-based study, we investigated the epidemiology of PAP in Taiwan, and discovered the comorbidities and prognostic factors of PAP. METHODS: From the National Health Insurance Research Database (NHIRD), we obtained comprehensive information about all patients of PAP in Taiwan between 1995 and 2013. The incidence, baseline characteristics comorbidities, and prognostic factors of PAP were investigated. RESULTS: The annual incidence rate of PAP was around 0.79 (range: 0.49-1.17) patients per million people after 2000, and the prevalence rate was 7.96 patients per million people by the end of 2013. In total, 276 patients of PAP were identified, including 177 (64%) and 99 (36%) patients with primary and secondary PAP, respectively. The median age of diagnosis was 53.8 years. The median survival was 9.6 years after the initial PAP diagnosis, and the 5-year survival rate was 65.96%. Twenty (7%) patients received whole lung lavage (WLL) within three months after the diagnosis had significantly better survival compared to the others. Multivariable Cox regression analyses showed that elder age, secondary PAP, and malignancy were associated with poorer survival, while WLL within 3 months of diagnosis might greatly improve the survival. CONCLUSION: We demonstrated the epidemiology of PAP in Taiwan, showing several poor prognostic factors and the potential effectiveness of WLL. Further prospective studies based on registry are warranted to improve the diagnosis and treatment of PAP.

Local Consolidative Therapy May Have Prominent Clinical Efficacy in Patients with EGFR-Mutant Advanced Lung Adenocarcinoma Treated with First-Line Afatinib.

Afatinib is an irreversible tyrosine kinase inhibitor (TKI) targeting the epidermal growth factor receptor (EGFR), which is utilized for the treatment of patients with advanced lung cancer that harbors EGFR mutations. No studies have evaluated the clinical efficacy of LCT in patients treated with first-line afatinib. In this study, we retrospectively enrolled patients with advanced lung adenocarcinomas harboring susceptible EGFR mutations who were diagnosed and treated with first-line afatinib in three hospitals. A total of 254 patients were enrolled, including 30 (12%) patients who received LCT (15 patients received definitive radiotherapy for the primary lung mass and 15 patients received curative surgery). Patients who received LCT had a significantly longer PFS than those who did not (median PFS: 32.8 vs. 14.5 months, p = 0.0008). Patients who received LCT had significantly longer OS than those who did not (median OS: 67.1 vs. 34.5 months, p = 0.0011). Multivariable analysis showed LCT was an independent prognostic factor for improved PFS (adjusted hazard ratio [aHR] [95% confidence interval (CI)]: 0.44 [0.26-0.73], p = 0.0016) and OS (aHR [95% CI]: 0.26 [0.12-0.54], p = 0.0004). The analyses using propensity score-weighting showed consistent results. We conclude that LCT may improve clinical outcomes, in terms of PFS and OS, in patients with advanced EGFR-mutant lung adenocarcinomas who are treated with first-line afatinib.

Real-world treatment pattern and prognostic factors of stage IV lung squamous cell carcinoma patients.

Lung squamous cell carcinoma (LUSC) represents a minor proportion of nonsmall cell lung cancer (NSCLC) harboring a poor prognosis. Herein, retrospective medical record research was performed to investigate real-world treatment patterns and identify the prognostic factors among LUSC patients. A total of 173 patients with a median age of 68 years were enrolled for analysis. Males were predominant (n = 143, 83%) and current or ex-smokers contributed to 78% of the entire cohort. Pleura and lung were the most common metastatic sites, whereas brain metastasis was only 7%. After diagnosis, however, only 107 patients (62%) had received first-line chemotherapy. In the chemotherapy cohort, median progression-free survival (PFS) and overall survival (OS) were 3.9 and 11.1 months, respectively. After multivariable analysis, bone metastasis and the use of first-line single-agent chemotherapy independently predicted shorter PFS. For baseline characteristics, male sex, metastasis to lung, pleura, liver, and bone independently predicted worse OS. Regarding the treatment pattern, patients who had undergone standard first-line doublet therapy and employed targeted therapies after disease progression linked to longer OS. In the real world, even those who underwent chemotherapy still had poor outcome. The findings may help clinicians to orchestrate the treatment strategies for LUSC patients and provide further direction of large-scale studies.

Survival estimation in patients with stomach and esophageal carcinoma using miRNA expression profiles.

Identifying a miRNA signature associated with survival will open a new window for developing miRNA-targeted treatment strategies in stomach and esophageal cancers (STEC). Here, using data from The Cancer Genome Atlas on 516 patients with STEC, we developed a Genetic Algorithm-based Survival Estimation method, GASE, to identify a miRNA signature that could estimate survival in patients with STEC. GASE identified 27 miRNAs as a survival miRNA signature and estimated the survival time with a mean squared correlation coefficient of 0.80 ± 0.01 and a mean absolute error of 0.44 ± 0.25 years between actual and estimated survival times, and showed a good estimation capability on an independent test cohort. The miRNAs of the signature were prioritized and analyzed to explore their roles in STEC. The diagnostic ability of the identified miRNA signature was analyzed, and identified some critical miRNAs in STEC. Further, miRNA-gene target enrichment analysis revealed the involvement of these miRNAs in various pathways, including the somatotrophic axis in mammals that involves the growth hormone and transforming growth factor beta signaling pathways, and gene ontology annotations. The identified miRNA signature provides evidence for survival-related miRNAs and their involvement in STEC, which would aid in developing miRNA-target based therapeutics.

Cognitive Function Associated with Gut Microbial Abundance in Sucrose and S-Adenosyl-L-Methionine (SAMe) Metabolic Pathways.

BACKGROUND: Differential abundance of gut microbiota has found to be associated with Alzheimer's disease (AD). However, the relative abundance of gut microbiota between dementia and mild cognitive impairment (MCI) in AD is not well studied. OBJECTIVE: We attempted to identify differentially enriched gut microbes and their metabolic pathways in AD patients with dementia comparing to AD patients with MCI. METHODS: Fecal samples were collected at Shuang Ho Hospital, Taipei Medical University, Taiwan and analyzed by whole metagenomic sequencing technique. For normal controls without AD (NC), 16S rRNA sequencing was obtained from the Taiwan Microbiome Database. A total of 48 AD (38 dementia and 10 MCI defined by cognitive function scores) and 50 NC were included. Microbiome alpha and beta diversities were estimated. Differentially enriched microbes were identified with HAllA, MaAsLin, DESeq2, and LEfSe statistical modeling approaches. RESULTS: We found significantly increased abundance of Firmicutes but decreased abundance of Bacteroidetes at phylum level in AD compared to NC. In AD patients, cognitive function scores were negatively associated with abundance of Blautia hydrogenotrophica (Firmicutes), Anaerotruncus colihominis (Firmicutes), and Gordonibacter pamelaeae (Actinobacteria). In addition, microbial abundance in the sucrose and S-Adenosyl-L-methionine (SAMe) metabolic pathways was more enriched in AD with MCI than AD with dementia and significantly associated with higher cognitive function scores. CONCLUSION: Gut microbe community diversity was similar in AD patients regardless of MCI or dementia status. However, differential analyses probed in lower-level taxa and metabolic pathways suggested that specific gut microbes in Firmicutes and Actinobacteria might involve in cognitive decline.

Proton pump inhibitors reduce the survival of advanced lung cancer patients with therapy of gefitinib or erlotinib.

Gefitinib and erlotinib are the first-line tyrosine kinase inhibitors (TKI) for advanced non-small-cell lung cancer. However, co-administration of either drug with proton pump inhibitors (PPI) or histamine-2 receptor antagonists (H2RA) may reduce TKI's bioavailability. Therefore, we aimed to investigate the effects of these drug-drug interactions. We surveyed nationwide population-based databases between Jan 1, 2010, and Dec 30, 2018. Newly diagnosed patients with advanced lung adenocarcinoma who received first-line gefitinib or erlotinib were identified. Effects on overall survival (OS) and time to next treatment (TTNT) association between PPIs or H2RAs and co-administrated gefitinib or erlotinib were evaluated. PPIs or H2RAs users were defined if the period overlapped with TKIs by ≥ 20%. A total of 4340 gefitinib and 1635 erlotinib users were included. PPI group had the shortest median OS and TTNT compared to the H2RA and non-user groups (in gefitinib cohort: OS: 14.35 vs. 17.67 vs. 21.87 months; P < 0.0001, TTNT: 8.47 vs. 10.78 vs. 10.33 months; P < 0.0001); (in erlotinib cohort: OS: 16.97 vs. 20.07 vs. 23.92 months; P < 0.0001, TTNT: 9.06 vs. 11.85 vs. 10.90 months; P = 0.0808). Compared with the non-user group, the adjusted hazard ratio (aHR) of the PPI group in the gefitinib was 1.58 on OS (95% CI 1.42-1.76), 1.37 on TTNT (95% CI 1.24-1.52); in the erlotinib was 1.54 on OS (95% CI 1.30-1.82) and 1.19 on TTNT (95% CI 1.01-1.39). Concurrent use of PPIs with first-line gefitinib or erlotinib therapy was associated with a worse OS and TTNT in patients with lung adenocarcinoma harboring EGFR mutations.

MicroRNA signature for estimating the survival time in patients with bladder urothelial carcinoma.

Bladder urothelial carcinoma (BLC) is one of the most common cancers in men, and its heterogeneity challenges the treatment to cure this disease. Recently, microRNAs (miRNAs) gained promising attention as biomarkers due to their potential roles in cancer biology. Identifying survival-associated miRNAs may help identify targets for therapeutic interventions in BLC. This work aims to identify a miRNA signature that could estimate the survival in patients with BLC. We developed a survival estimation method called BLC-SVR based on support vector regression incorporated with an optimal feature selection algorithm to select a robust set of miRNAs as a signature to estimate the survival in patients with BLC. BLC-SVR identified a miRNA signature consisting of 29 miRNAs and obtained a mean squared correlation coefficient and mean absolute error of 0.79 ± 0.02 and 0.52 ± 0.32 year between actual and estimated survival times, respectively. The prediction performance of BLC-SVR had a better estimation capability than other standard regression methods. In the identified miRNA signature, 14 miRNAs, hsa-miR-432-5p, hsa-let-7e-3p, hsa-miR-652-3p, hsa-miR-629-5p, and hsa-miR-203a-3p, hsa-miR-129-5p, hsa-miR-769-3p, hsa-miR-570-3p, hsa-miR-320c, hsa-miR-642a-5p, hsa-miR-496, hsa-miR-5480-3p, hsa-miR-221-5p, and hsa-miR-7-1-3p, were found to be good biomarkers for BLC diagnosis; and the six miRNAs, hsa-miR-652-5p, hsa-miR-193b-5p, hsa-miR-129-5p, hsa-miR-143-5p, hsa-miR-496, and hsa-miR-7-1-3p, were found to be good biomarkers of prognosis. Further bioinformatics analysis of this miRNA signature demonstrated its importance in various biological pathways and gene ontology annotation. The identified miRNA signature would further help in understanding of BLC diagnosis and prognosis in the development of novel miRNA-target based therapeutics in BLC.

Comparing survival and subsequent treatment of first-line tyrosine kinase inhibitors in patients of advanced lung adenocarcinoma with epidermal growth factor receptor mutation.

BACKGROUND/PURPOSE: Three first-line epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are widely available to treat advanced lung adenocarcinoma harboring EGFR mutation. However, studies comparing efficacy or effectiveness of these EGFR TKIs came out with inconclusive results. METHODS: In this real-world data analysis with a nationwide retrospective cohort design, adult patients with newly diagnosed advanced lung adenocarcinoma with EGFR mutation between 2011 and 2016, who received a first-line EGFR TKI, were included. Overall survival (OS) and time to next treatment (TTNT) were compared between patients receiving different EGFR TKIs after overlap weighting. RESULTS: We enrolled 10,431 patients, including 6,230, 2,359, and 1842 in gefitinib, erlotinib, and afatinib groups, respectively. The median (95% confidence interval [CI]) OS were 24.2 (22.9-26.2), 25.7 (24.0-27.9), and 29.1 (25.8-32.1) months for those receiving gefitinib, erlotinib, and afatinib, respectively (p = 0.001). The hazard ratios (95% CI) for the afatinib group were 0.85 (0.74-0.98) and 0.91 (0.79-1.05) comparing with the gefitinib and erlotinib groups, respectively. The median (95% CI) TTNT were 10.9 (10.4-11.2), 11.7 (11.3-12.1), 13.4 (12.5-14.3) months for those receiving gefitinib, erlotinib, and afatinib, respectively (p < 0.001). The hazard ratios (95% CI) for the afatinib group were 0.79 (0.70-0.88) and 0.89 (0.79-1.00) comparing with the gefitinib and erlotinib groups, respectively. There were 6111 (59%) patients receiving subsequent therapies, and the majority of them received a second-line chemotherapy, particularly platinum-based chemotherapy. CONCLUSION: Afatinib, compared with gefitinib, might provide better effectiveness as the first-line targeted therapy for patients of advanced lung adenocarcinoma with EGFR mutation.

Different Tyrosine Kinase Inhibitors Used in Treating EGFR-Mutant Pulmonary Adenocarcinoma with Brain Metastasis and Intracranial Intervention Have No Impact on Clinical Outcomes.

Brain metastasis in patients with non-small-cell lung cancer (NSCLC) harboring epidermal growth factor receptor (EGFR) mutations is a factor of poor prognosis. We conducted a retrospective study to determine the optimal treatment strategy for EGFR-mutant NSCLC patients with brain metastasis receiving or not receiving intracranial intervention. A total of 186 patients treated with an EGFR TKI were enrolled in the study, and 79 (42%) received intracranial intervention. Patients who received intracranial intervention and those who did not had a similar treatment response rate (RR), progression-free survival (PFS) (median PFS: 11.0 vs. 10.0 months, p = 0.4842), and overall survival (OS) (median OS: 23.0 vs. 23.2 months, p = 0.2484). Patients treated with gefitinib, erlotinib, afatinib, or osimertinib had a similar RR (63%, 76%, 81%, or 100%, respectively, p = 0.1390), but they had significantly different PFS (median PFS: 7.5, 10.0, 14.8 months, or not reached, respectively, p = 0.0081). In addition, OS tended to be different between different EGFR TKI treatments (median OS of 19.2, 23.7, or 33.0 months for gefitinib, erlotinib, or afatinib treatments, respectively, p = 0.0834). Afatinib and osimertinib both demonstrated significantly longer PFS than gefitinib in a Cox regression model. Graded prognostic assessment (GPA) versions 2017 and 2022 stratified patients with different OS; patients with higher GPA index scores had significantly longer OS (p = 0.0368 and 0.0407 for version 2017 and 2022, respectively).

miR-150-5p-Containing Extracellular Vesicles Are a New Immunoregulator That Favor the Progression of Lung Cancer in Hypoxic Microenvironments by Altering the Phenotype of NK Cells.

Natural killer (NKs) cells are cytotoxic effector cells, which can modulate tumor metastasis according to their function; however, the role of NK cells in lung cancer has not been extensively investigated. In this study, we determined the functional profiles of NK cells in a hypoxic tumor microenvironment (TME) of lung cancer. We revealed CD226 downregulation and functional repression of NK cells after hypoxic lung cancer priming and we then investigated their interaction with extracellular vesicles (EVs) and miR-150-5p. We also found that NK cells from lung cancer patients had lower expression of CD226 on their surface and exhibited a pro-inflammatory, pro-angiogenic and tumorigenesis phenotype by expressing VEGF, CXCL1, CXCL8, S100A8 and MMPs. Moreover, inhibition of miR-150 improved tumor surveillance by reversing CD226 expression and subsequently reinstating cytotoxic NK cell activity in an animal model. Our study introduces a new scenario for the pro-inflammatory and pro-angiogenic activities of NK cells in the hypoxic TME in lung cancer.

Male adolescents with contralateral blebs undergoing surgery for primary spontaneous pneumothorax may benefit from simultaneous contralateral blebectomies.

BACKGROUND: In adults with primary spontaneous pneumothorax (PSP), contralateral recurrence occurs in about 25-28% when there are asymptomatic blebs. How to treat contralateral recurrence of PSP in pediatric populations remains controversial. This study evaluated the outcomes of excising contralateral blebs to prevent recurrence in adolescents being operated on for PSP under the same anesthesia. METHODS: One hundred thirty-two male PSP patients under age 19 were surgically treated in a single institution between January 2008 and December 2016. Thoracoscopic blebectomies with pleurodesis were performed in all patients. The patients were categorized into those with contralateral blebs receiving one-stage bilateral surgeries (32 patients), those with contralateral blebs only receiving unilateral surgeries (40 patients), and those without contralateral blebs only receiving unilateral surgeries (60 patients). Perioperative details and outcomes were retrospectively analyzed. RESULTS: Significant differences in contralateral recurrence rate were found among the three groups (0%, 30%, and 1%, respectively; P < 0.001). Multivariate analysis showed that being under 16.5 years old was a risk factor for overall recurrence (Hazard ratio [HR] 2.81, 95% confidence interval [CI] 1.08-7.30, P = 0.034). Moreover, patients who had contralateral blebs and only received unilateral surgery were at greater risk of overall recurrence (HR 6.06, 95% CI 1.77-20.75, P = 0.004). Kaplan-Meier analysis showed that contralateral and overall recurrence-free survival differed among the three groups (P < 0.0001, P = 0.0002). CONCLUSIONS: Although younger male PSP adolescents treated with surgery were more likely to have postoperative recurrences, the performance of simultaneous contralateral blebectomies in those receiving one-stage bilateral surgeries significantly reduced future contralateral recurrence without compromising patient safety.