Association between genetically proxied glucosamine and risk of cancer and non-neoplastic disease: A Mendelian randomization study.

Introduction: Observational investigations have examined the impact of glucosamine use on the risk of cancer and non-neoplastic diseases. However, the findings from these studies face limitations arising from confounding variables, reverse causation, and conflicting reports. Consequently, the establishment of a causal relationship between habitual glucosamine consumption and the risk of cancer and non-neoplastic diseases necessitates further investigation. Methods: For Mendelian randomization (MR) investigation, we opted to employ single-nucleotide polymorphisms (SNPs) as instruments that exhibit robust associations with habitual glucosamine consumption. We obtained the corresponding effect estimates of these SNPs on the risk of cancer and non-neoplastic diseases by extracting summary data for genetic instruments linked to 49 varied cancer types amounting to 378,284 cases and 533,969 controls, as well as 20 non-neoplastic diseases encompassing 292,270 cases and 842,829 controls. Apart from the primary analysis utilizing inverse-variance weighted MR, we conducted two supplementary approaches to account for potential pleiotropy (MR-Egger and weighted median) and assessed their respective MR estimates. Furthermore, the results of the leave-one-out analysis revealed that there were no outlying instruments. Results: Our results suggest divergence from accepted biological understanding, suggesting that genetically predicted glucosamine utilization may be linked to an increased vulnerability to specific illnesses, as evidenced by increased odds ratios and confidence intervals (95% CI) for diseases, such as malignant neoplasm of the eye and adnexa (2.47 [1.34-4.55]), benign neoplasm of the liver/bile ducts (2.12 [1.32-3.43]), benign neoplasm of the larynx (2.01 [1.36-2.96]), melanoma (1.74 [1.17-2.59]), follicular lymphoma (1.50 [1.06-2.11]), autoimmune thyroiditis (2.47 [1.49-4.08]), and autoimmune hyperthyroidism (1.93 [1.17-3.18]). In contrast to prior observational research, our genetic investigations demonstrate a positive correlation between habitual glucosamine consumption and an elevated risk of sigmoid colon cancer, lung adenocarcinoma, and benign neoplasm of the thyroid gland. Conclusion: Casting doubt on the purported purely beneficial association between glucosamine ingestion and prevention of neoplastic and non-neoplastic diseases, habitual glucosamine ingestion exhibits dichotomous effects on disease outcomes. Endorsing the habitual consumption of glucosamine as a preventative measure against neoplastic and non-neoplastic diseases cannot be supported.

Alterations of lower respiratory tract microbiome and short-chain fatty acids in different segments in lung cancer: a multiomics analysis.

Introduction: The lower respiratory tract microbiome is widely studied to pinpoint microbial dysbiosis of diversity or abundance that is linked to a number of chronic respiratory illnesses. However, it is vital to clarify how the microbiome, through the release of microbial metabolites, impacts lung health and oncogenesis. Methods: In order to discover the powerful correlations between microbial metabolites and disease, we collected, under electronic bronchoscopy examinations, samples of paired bronchoalveolar lavage fluids (BALFs) from tumor-burden lung segments and ipsilateral non-tumor sites from 28 lung cancer participants, further performing metagenomic sequencing, short-chain fatty acid (SCFA) metabolomics, and multiomics analysis to uncover the potential correlations of the microbiome and SCFAs in lung cancer. Results: In comparison to BALFs from normal lung segments of the same participant, those from lung cancer burden lung segments had slightly decreased microbial diversity in the lower respiratory tract. With 18 differentially prevalent microbial species, including the well-known carcinogens Campylobacter jejuni and Nesseria polysaccharea, the relative species abundance in the lower respiratory tract microbiome did not significantly differ between the two groups. Additionally, a collection of commonly recognized probiotic metabolites called short-chain fatty acids showed little significance in either group independently but revealed a strong predictive value when using an integrated model by machine learning. Multiomics also discovered particular species related to SCFAs, showing a positive correlation with Brachyspira hydrosenteriae and a negative one with Pseudomonas at the genus level, despite limited detection in lower airways. Of note, these distinct microbiota and metabolites corresponded with clinical traits that still required confirmation. Conclusions: Further analysis of metagenome functional capacity revealed that genes encoding environmental information processing and metabolism pathways were enriched in the lower respiratory tract metagenomes of lung cancer patients, further supporting the oncogenesis function of various microbial species by different metabolites. These findings point to a potent relationship between particular components of the integrated microbiota-metabolites network and lung cancer, with implications for screening and diagnosis in clinical settings.

Exploration of a novel prognostic model based on nomogram in non-small cell lung cancer patients with distant organ metastasis: implications for immunotherapy.

Background: Evidence for the effects of immunotherapy in non-small cell lung cancer (NSCLC) patients with distant organ metastasis is insufficient, and the predictive efficacy of established markers in tissue and blood is elusive. Our study aimed to determine the prognostic factors and develop a survival prognosis model for these patients. Methods: A total of 100 advanced NSCLC patients with distant organ metastases, who received single or combination immune checkpoint inhibitors (ICIs) in Xijing Hospital between June 2018 and June 2021, were enrolled for retrospective analysis. The major clinicopathological parameters were collected, and associated survival outcomes were followed up by telephone or inpatient follow-up for nearly 3 years to assess prognoses. The survival prognosis model was established based on univariate and multivariate Cox regression analyses to determine the candidate prognostic factors. Results: From the start of immunotherapy to the last follow-up, 77 patients progressed and 42 patients died, with a median follow-up of 18 months [95% confidence interval (CI): 15-19.9]. The median progression-free survival (PFS) and overall survival (OS) were 8 months (95% CI: 5.6-10.4) and 21 months (95% CI: 8.9-33.1), respectively. Multivariate Cox proportional hazards analysis showed Eastern Cooperative Oncology Group performance status (ECOG PS), body mass index (BMI), age-adjusted Charlson comorbidity index (ACCI), lactate dehydrogenase (LDH), and absolute neutrophil count (ANC) were correlated significantly with OS. Based on these five predictive factors, a nomogram and corresponding dynamic web page were constructed with a concordance index (C-index) of 0.81 and a 95% CI of 0.778-0.842. Additionally, the calibration plot and time-receiver operating characteristic (ROC) curve validated the precision of the model at 6-, 12-, and 18-month area under the curves (AUCs) reached 0.934, 0.829, and 0.846, respectively. According to the critical point of the model, patients were further divided into a high-risk total point score (TPS) >258, middle-risk (204< TPS ≤258), and low-risk group (TPS ≤204), and significant OS differences were observed among the three subgroups (median OS: 4.8 vs. 13.0 vs. 32.9 months). Conclusions: A feasible and practical model based on clinical characteristics has been developed to predict the prognosis of NSCLC patients with distant organ metastasis undergoing immunotherapy.

The debatable role of immune checkpoint blockade therapy in lung adenocarcinoma-oriented liver metastatic malignant lesions.

BACKGROUND: The use of anti-PD-1 or PD-L1 inhibitors in combination with other anti-cancer agents was a priority for treating advanced non-small cell lung cancer (NSCLC) patients with considerable PD-L1 expression. However, studies seldom show the progression of liver metastases after using immune checkpoint inhibitors (ICIs). METHODS: Data were obtained from the Department of Pulmonary and Critical Care of Medicine, the First Affiliated Hospital of the Air Force Military Medical University. In the present study, we analyzed five non-small cell lung cancer (NSCLC) patients who had liver metastases after they were treated with pembrolizumab between 2019 and 2021. All of them had both stable primary lesions and liver progression with pembrolizumab intervention. Blood laboratory tests and imaging examinations were performed regularly during the treatment to assess the tumor responses of patients. RESULTS: All patients displayed reduction or stability in the initial lesions as a result, but they also experienced the emergence of metastatic liver locations, which were regularly detected throughout immunotherapy. Additionally, the appearance of liver metastasis weakened their liver function gradually with the escalation of carcinoembryonic antigen, regarded as a predictor for evaluating the progression of tumors. These individuals were highly distinctive with hyper-progressive diseases associated with immunotherapy. We drew individualized intervention schemes for metastatic lesions in each patient and found that their life expectancy shared no significance given the restricting subjected population. CONCLUSIONS: Our study indicated a clinical phenomenon after using immune checkpoint inhibitors and presented a necessity for implementing large scales clinical studies to manage NSCLC-oriented liver metastasis.

Development of Diagnosis Model for Early Lung Nodules Based on a Seven Autoantibodies Panel and Imaging Features.

Background: There is increasing incidence of pulmonary nodules due to the promotion and popularization of low-dose computed tomography (LDCT) screening for potential populations with suspected lung cancer. However, a high rate of false-positive and concern of radiation-related cancer risk of repeated CT scanning remains a major obstacle to its wide application. Here, we aimed to investigate the clinical value of a non-invasive and simple test, named the seven autoantibodies (7-AABs) assay (P53, PGP9.5, SOX2, GAGE7, GUB4-5, MAGEA1, and CAGE), in distinguishing malignant pulmonary diseases from benign ones in routine clinical practice, and construct a neural network diagnostic model with the development of machine learning methods. Method: A total of 933 patients with lung diseases and 744 with lung nodules were identified. The serum levels of the 7-AABs were tested by an enzyme-linked Immunosorbent assay (ELISA). The primary goal was to assess the sensitivity and specificity of the 7-AABs panel in the detection of lung cancer. ROC curves were used to estimate the diagnosis potential of the 7-AABs in different groups. Next, we constructed a machine learning model based on the 7-AABs and imaging features to evaluate the diagnostic efficacy in lung nodules. Results: The serum levels of all 7-AABs in the malignant lung diseases group were significantly higher than that in the benign group. The sensitivity and specificity of the 7-AABs panel test were 60.7% and 81.5% in the whole group, and 59.7% and 81.1% in cases with early lung nodules. Comparing to the 7-AABs panel test alone, the neural network model improved the AUC from 0.748 to 0.96 in patients with pulmonary nodules. Conclusion: The 7-AABs panel may be a promising method for early detection of lung cancer, and we constructed a new diagnostic model with better efficiency to distinguish malignant lung nodules from benign nodules which could be used in clinical practice.

The Clinical Prediction Value of the Ubiquitination Model Reflecting the Immune Traits in LUAD.

Background: Increasing evidence shows that the ubiquitin-proteasome system has a crucial impact on lung adenocarcinoma. However, reliable prognostic signatures based on ubiquitination and immune traits have not yet been established. Methods: Bioinformatics was performed to analyze the characteristic of ubiquitination in lung adenocarcinoma. Principal component analysis was employed to identify the difference between lung adenocarcinoma and adjacent tissue. The ubiquitin prognostic risk model was constructed by multivariate Cox regression and least absolute shrinkage and selection operator regression based on the public database The Cancer Genome Atlas, with evaluation of the time-dependent receiver operating characteristic curve. A variety of algorithms was used to analyze the immune traits of model stratification. Meanwhile, the drug response sensitivity for subgroups was predicted by the "pRRophetic" package based on the database of the Cancer Genome Project. Results: The expression of ubiquitin genes was different in the tumor and in the adjacent tissue. The ubiquitin model was superior to the clinical indexes, and four validation datasets verified the prognostic effect. Additionally, the stratification of the model reflected distinct immune landscapes and mutation traits. The low-risk group was infiltrating plenty of immune cells and highly expressed major histocompatibility complex and immune genes, which illustrated that these patients could benefit from immune treatment. The high-risk group showed higher mutation and tumor mutation burden. Integrating the tumor mutation burden and the immune score revealed the patient's discrepancy between survival and drug response. Finally, we discovered that the drug targeting ubiquitin and proteasome would be a beneficial prospective treatment for lung adenocarcinoma. Conclusion: The ubiquitin trait could reflect the prognosis of lung adenocarcinoma, and it might shed light on the development of novel ubiquitin biomarkers and targeted therapy for lung adenocarcinoma.

PHB2 promotes tumorigenesis via RACK1 in non-small cell lung cancer.

Background: Lung cancer has the highest mortality rate among cancers worldwide, with non-small cell lung cancer (NSCLC) the most common type. Increasing evidence shows that PHB2 is highly expressed in other cancer types; however, the effects of PHB2 in NSCLC are currently poorly understood. Method: PHB2 expression and its clinical relevance in NSCLC tumor tissues were analyzed using a tissue microarray. The biological role of PHB2 in NSCLC was investigated in vitro and in vivo using immunohistochemistry and immunofluorescence staining, gene expression knockdown and overexpression, cell proliferation assay, flow cytometry, terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay, wound healing assay, Transwell assay, western blot analysis, qRT-PCR, coimmunoprecipitation, and mass spectrometry analysis. Results: Our major finding is that PHB2 facilitates tumorigenesis in NSCLC by interacting with and stabilizing RACK1, which further induces activation of downstream tumor-promoting effectors. PHB2 was found to be overexpressed in NSCLC tumor tissues, and its expression was correlated with clinicopathological features. Furthermore, PHB2 overexpression promoted proliferation, migration, and invasion, whereas PHB2 knockdown enhanced apoptosis in NSCLC cells. The stimulating effect of PHB2 on tumorigenesis was also verified in vivo. In addition, PHB2 interacted with RACK1 and increased its expression through posttranslational modification, which further induced activation of the Akt and FAK pathways. Conclusions: Our results reveal the effects of PHB2 on tumorigenesis and its regulation of RACK1 and RACK1-associated proteins and downstream signaling in NSCLC. We believe that the crosstalk between PHB2 and RACK1 provides us with a great opportunity to design and develop novel therapeutic strategies for NSCLC.

Assessment of Financial Toxicity Among Patients With Advanced Lung Cancer in Western China.

Background: Lung cancer is the leading source of cancer-caused disability-adjusted life years. Medical cost burden impacts the well-being of patients through reducing income, cutting daily expenses, curtailing leisure activities, and depleting exhausting savings. The COmprehensive Score for Financial Toxicity (COST) was created and validated by De Souza and colleagues. Our study intends to measure the financial burdens of cancer therapy and investigate the link between financial toxicity and health-related quality of life (HRQoL) in an advanced lung cancer population. Methods: Patients aged ≥ 18 years with confirmed stage III to IV lung cancer were eligible. The COST questionnaire verified by de Souza et al. was used to identify financial toxicity. Multivariable linear regression analysis with log transformation univariate analysis and Pearson correlations were used to perform the analysis. Results: The majority of the patients (90.8%, n = 138/152) had an annual income of $50,000 ($7,775). The cohort's insurance situation was as follows: 64.5% of the cohort had social insurance, 20.4% had commercial insurance, and 22.0% had both. Patients who were younger age (50-59, P < 0.001), employed but on sick leave, and had lower income reported increased levels of financial toxicity (P < 0.05). The risk factors for high financial toxicity: (i) younger age (50-59), (ii) <1 month of savings, and (iii) being employed but on sick leave. Increased financial toxicity is moderately correlated with a decrease in QoL. Conclusion: Poorer psychological status and specific demographics are linked to increased financial toxicity (lower COST). Financial toxicity has a modest relationship with HRQoL and may have a clear link with HRQoL measurements.