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.

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.

BackgroundIncreasing 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.MethodsBioinformatics 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.ResultsThe 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.ConclusionThe 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.