Inhibition of HHIP Promoter Methylation Suppresses Human Gastric Cancer Cell Proliferation and Migration

Background/Aims: Human hedgehog-interacting protein (HHIP) is a negative regulator of the hedgehog (HH) signaling pathway. It is deregulated in gastric cancer. The underlying molecular mechanism of HHIP-induced inhibition of HH signaling remains to be determined. Methods: A lentiviral HHIP expression vector (“LV-HHIP”) was established to exogenously over-express HHIP in gastric cancer cells. HHIP protein and mRNA were tested by Western blotting assay and quantitative real-time PCR assay, respectively. Cell survival was tested by the Cell Counting Kit-8 (CCK-8) assay. Cell proliferation was examined by the BrdU ELISA assay and [H3] Thymidine DNA incorporation assay. Cell invasion and migration were tested by the phagokinetic track assay and the “Transwell” assay. The bisulfite-sequencing PCR was applied to test HHIP promoter methylation. Results: In the established (AGS cell line) and primary human gastric cancer cells, LV-HHIP transfection increased HHIP expression and inhibited cancer cell survival and proliferation as well as cell migration and invasion. Furthermore, LV-HHIP significantly attenuated promoter methylation of the endogenous HHIP gene in AGS cells, causing it upregulation. Inhibition of methylation by 5-aza-dc similarly induced HHIP expression in gastric cancer cells, which inhibited cancer cell proliferation and migration. Conclusions: Our results suggest that inhibition of HHIP promoter methylation can efficiently inhibit human gastric cancer cell proliferation and migration

Overexpression of Lymphocyte Antigen 6 Complex, Locus E in Gastric Cancer Promotes Cancer Cell Growth and Metastasis

Background/Aims: Lymphocyte antigen 6 complex, locus E (LY6E) is a member of the lymphostromal cell membrane Ly6 superfamily protein. The present study investigated the clinical significance and potential biological function of LY6E in gastric cancer (GC). Methods: LY6E mRNA and protein expressions in human GC tissues and GC cells were tested. Relationship between LY6E expression and the GC patients’ clinicopathologic characteristics was analyzed. LY6E was silenced by siRNA in the cultured GC cells. Results: The RNA expression microarray profiling assay results demonstrated that LY6E mRNA was significantly increased in multiple human GC tumor tissues. Immunohistochemistry (IHC) staining analysis revealed that 59 of 75 (78.7%) GC specimens were LY6E positive. LY6E over-expression in human GC was correlated with the histology grade, AJCC stage, N classification, lymphatic invasion, and tumor location. Notably, functional LY6E expression was also detected in AGS and other established GC cell lines. LY6E knockdown by targeted-siRNA inhibited AGS cell survival and proliferation. Meanwhile, the LY6E siRNA induced G1-S cell cycle arrest and apoptosis in AGC cells. Additionally, AGC cell migration was also inhibited by LY6E knockdown. Expressions of tumor-suppressing proteins, including PTEN (phosphatase and tensin homolog) and E-Cadherin, were increased in LY6E-silenced AGS cells. Conclusion: LY6E over-expression in GC is potentially required for cancer cell survival, proliferation and migration

Cluster-Mediated Nucleation and Growth of J- and H‑Type Polymorphs of Difluoroboron Avobenzone for Organic Microribbon Lasers

Controlled fabrication of organic polymorphisms with well-defined dimensions and tunable luminescent properties plays an important role in developing optoelectronic devices, sensors, and biolabeling agents but remains a challenge due to the weak intermolecular interactions among organic molecules. Herein, we developed a two-step solution self-assembly method for the controlled preparation of blue-emissive or green-emissive microribbons (MRs) of difluoroboron avobenzone (BF₂AVB) by adjusting the cluster-mediated nucleation and subsequent one-dimensional growth processes. We found that blue-emissive MRs belong to the monoclinic phase, in which BF₂AVB molecules form slipped π-stacks, resulting in J-aggregates with the solid-state photoluminescence efficiency φ = 68%. Meanwhile, green-emissive MRs are ascribed to the orthorhombic phase and exhibit cofacial π-stacks, which lead to H-aggregates with φ = 24%. Furthermore, these as-prepared MRs can both act as polymorph-dependent Fabry–Pérot resonators for lasing oscillators. The strategy described here might offer significant promise for the coherent light source of optoelectronic devices

Risk-based lung cancer screening in heavy smokers: a benefit–harm and cost-effectiveness modeling study

Abstract Background Annual screening through low-dose computed tomography (LDCT) is recommended for heavy smokers. However, it is questionable whether all individuals require annual screening given the potential harms of LDCT screening. This study examines the benefit–harm and cost-effectiveness of risk-based screening in heavy smokers and determines the optimal risk threshold for screening and risk-stratified screening intervals. Methods We conducted a comparative cost-effectiveness analysis in China, using a cohort-based Markov model which simulated a lung cancer screening cohort of 19,146 heavy smokers aged 50 ~ 74 years old, who had a smoking history of at least 30 pack-years and were either current smokers or had quit for < 15 years. A total of 34 risk-based screening strategies, varying by different risk groups for screening eligibility and screening intervals (1-year, 2-year, 3-year, one-off, non-screening), were evaluated and were compared with annual screening for all heavy smokers (the status quo strategy). The analysis was undertaken from the health service perspective with a 30-year time horizon. The willingness-to-pay (WTP) threshold was adopted as three times the gross domestic product (GDP) of China in 2021 (CNY 242,928) per quality-adjusted life year (QALY) gained. Results Compared with the status quo strategy, nine risk-based screening strategies were found to be cost-effective, with two of them even resulting in cost-saving. The most cost-effective strategy was the risk-based approach of annual screening for individuals with a 5-year risk threshold of ≥ 1.70%, biennial screening for individuals with a 5-year risk threshold of 1.03 ~ 1.69%, and triennial screening for individuals with a 5-year risk threshold of < 1.03%. This strategy had the highest incremental net monetary benefit (iNMB) of CNY 1032. All risk-based screening strategies were more efficient than the status quo strategy, requiring 129 ~ 656 fewer screenings per lung cancer death avoided, and 0.5 ~ 28 fewer screenings per life-year gained. The cost-effectiveness of risk-based screening was further improved when individual adherence to screening improved and individuals quit smoking after being screened. Conclusions Risk-based screening strategies are more efficient in reducing lung cancer deaths and gaining life years compared to the status quo strategy. Risk-stratified screening intervals can potentially balance long-term benefit–harm trade-offs and improve the cost-effectiveness of lung cancer screenings

Additional file 1 of Risk-based lung cancer screening in heavy smokers: a benefit–harm and cost-effectiveness modeling study

Additional file 1: Table S1. Risk-factors considered in the relative risk model for lung cancer. Table S2. Estimated incidence of lung cancer and mortality rates of non-lung cancer by sex and age (1/10^5). Table S3. Details of the evaluated LDCT screening strategies. Table S4. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Sensitivity of LDCT: 0.890). Table S5. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Sensitivity of LDCT: 1.000). Table S6. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Specificity of LDCT: 0.700). Table S7. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Specificity of LDCT: 0.930). Table S8. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (overdiagnosis rate when screening: 0.0155). Table S9. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (overdiagnosis rate when screening: 0.0465). Table S10. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Excess relative risk of LC per screening: 0.0003). Table S11. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Excess relative risk of LC per screening: 0.0019). Table S12. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Biopsy diagnosis cost: decreased by 50%). Table S13. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Biopsy diagnosis cost: increased by 50%). Table S14. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (LDCT test cost: decreased by 50%). Table S15. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (LDCT test cost: increased by 50%). Table S16. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Background medical treatment costs: decreased by 50%). Table S17. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Background medical treatment costs: increased by 50%). Table S18. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Disutility associated with a false positive screen: decreased by 50%). Table S19. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Disutility associated with a false positive screen: increased by 50%). Table S20. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Adherence: decreased by 50%). Table S21. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (No discount). Table S22. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Discount: 8%). Table S23. Cost-effectiveness estimates for lung cancer screening scenarios ordered by QALYs (Quit smoking with being screened). Fig. S1. Cost-effectiveness acceptability curves of H1-MH3-LMnone-Lnone vs No screening. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S2. Cost-effectiveness acceptability curves of H1-MH2-LMnone-Lnone vs H1-MH3-LMnone-Lnone. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S3. Cost-effectiveness acceptability curves of H1-MH3-LM3-L3 vs H1-MH2-LMnone-Lnone. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S4. Cost-effectiveness acceptability curves of H1-MH2-LM3-L3 vs H1-MH3-LM3-L3. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S5. Cost-effectiveness acceptability curves of H1-MH2-LM2-L2 vs H1-MH2-LM3-L3. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S6. Cost-effectiveness acceptability curves of H1-MH1-LM2-L2 vs H1-MH2-LM2-L2. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S7. Cost-effectiveness acceptability curves of H1-MHone-off-LMone-off-Lone-off vs No screening if individuals quit smoking with being screened. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S8. Cost-effectiveness acceptability curves of H1-MH3-LMone-off-Lone-off vs H1-MHone-off-LMone-off-Lone-off if individuals quit smoking with being screened. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S9. Cost-effectiveness acceptability curves of H1-MH3-LM3-L3 vs H1-MH3-LMone-off-Lone-off if individuals quit smoking with being screened. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S10. Cost-effectiveness acceptability curves of H1-MH2-LM3-L3 vs H1-MH3-LM3-L3 if individuals quit smoking with being screened. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S11. Cost-effectiveness acceptability curves of H1-MH1-LM3-L3 vs H1-MH2-LM3-L3 if individuals quit smoking with being screened. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S12. Cost-effectiveness acceptability curves of H1-MH2-LM2-L2 vs H1-MH1-LM3-L3 if individuals quit smoking with being screened. QALY, quality-adjusted life year; GDP, gross domestic product. Fig. S13. Cost-effectiveness acceptability curves of H1-MH1-LM2-L2 vs H1-MH2-LM2-L2 if individuals quit smoking with being screened. QALY, quality-adjusted life year; GDP, gross domestic product