Objective: To determine the additional relationship between factors discovered by searching for sociodemographic and metastasis factors, as well as treatment outcomes, which could help improve the prediction of the survival rate in cancer patients. Material and Methods. A total of 56 patients were recruited from the ambulatory clinic at the Hospital Universiti Sains Malaysia (USM). In this retrospective study, advanced computational statistical modeling techniques were used to evaluate data descriptions of several variables such as treatment, age, and distant metastasis. The R-Studio software and syntax were used to implement and test the hazard ratio. The statistics for each sample were calculated using a combination model that included methods such as bootstrap and multiple linear regression (MLR).
Results: The statistical strategy showed R demonstrates that regression modeling outperforms an R-squared. It demonstrated that when data is partitioned into a training and testing dataset, the hybrid model technique performs better at predicting the outcome. The variable validation was determined using the well-established bootstrap-integrated MLR technique. In this case, three variables are considered: age, treatment, and distant metastases. It is important to note that three things affect the hazard ratio: age (β 1: -0.006423; p < 2e - 16), treatment (β 2: -0.355389; p < 2e - 16), and distant metastasis (β 3: -0.355389; p < 2e - 16). There is a 0.003469102 MSE for the linear model in this scenario.
Conclusion: In this study, a hybrid approach combining bootstrapping and multiple linear regression will be developed and extensively tested. The R syntax for this methodology was designed to ensure that the researcher completely understood the illustration. In this case, a hybrid model demonstrates how this critical conclusion enables us to better understand the utility and relative contribution of the hybrid method to the outcome. The statistical technique used in this study, R, demonstrates that regression modeling outperforms R-squared values of 0.9014 and 0.00882 for the predicted mean squared error, respectively. The conclusion of the study establishes the superiority of the hybrid model technique used in the study.
OBJECTIVES: This study was performed to identify mechanisms of afatinib resistance and to explore potential afatinib-based combination treatments with other targeted inhibitors in oral squamous cell carcinoma.
METHODS: We determined the anti-proliferative effects of afatinib on a panel of oral squamous cell carcinoma cell lines using a crystal violet-growth inhibition assay, click-iT 5-ethynyl-2'-deoxyuridine staining, and cell-cycle analysis. Biochemical assays were performed to study the underlying mechanism of drug treatment as a single agent or in combination with the MEK inhibitor trametinib. We further evaluated and compared the anti-tumor effects of single agent and combined treatment by using oral squamous cell carcinoma xenograft models.
RESULTS: In this study, we showed that afatinib inhibited oral squamous cell carcinoma cell proliferation via cell-cycle arrest at the G0/G1 phase, and inhibited tumor growth in xenograft mouse models. Interestingly, we demonstrated reactivation of the mitogen-activated protein kinase (ERK1/2) pathway in vitro, which possibly reduced the effects of ErbB inhibition. Concomitant treatment of oral squamous cell carcinoma cells with afatinib and trametinib synergized the anti-tumor effects in oral squamous cell carcinoma-bearing mouse models.
CONCLUSIONS: Our findings provide insight into the molecular mechanism of resistance to afatinib and support further clinical evaluation into the combination of afatinib and MEK inhibition in the treatment of oral squamous cell carcinoma.
METHODS: Methods involved were MTT assay (cytotoxic activity), morphological cells analysis, flow cytometry and cell cycle analysis and western blot.
RESULTS: MTT assay revealed IC50 concentration was 1.61 µg/mL, 3T3-L1 cell lines were used to determine whether AgNps-CN is cytotoxic to normal cells. At the highest concentration (3 µg/mL), no cytotoxic activity has been observed. Flow cytometry assay revealed AgNps-CN caused apoptosis effects towards HSC-4 cell lines with significant changes were observed at G1 phase when compared with untreated cells. Morphological cells analysis revealed that most of the cells exhibit apoptosis characteristics rather than necrosis. Protein study revealed that ratio of Bax/Bcl-2 increased mainly due to down-regulation of Bcl-2 expression.
CONCLUSION: AgNps-CN have shown potential in inhibiting HSC-4 cell lines. IC50 was low compared to few studies involving biosynthesized of silver nanoparticles. Apoptosis effects were shown towards HSC-4 cell lines by the increased in Bax/Bcl-2 protein ratio. Further study such as PCR or in vivo studies are required.
METHODS: We analysed frozen samples from 105 OSCC as well as 105 oral specimens derived from healthy individuals. PCR assays targeting two regions of the virus were used. PCR amplification for the analysis of p53 codon 72 arginine/proline alleles was carried out in a separate reaction.
RESULTS: HPV DNA was detected in 51.4% OSCC samples, while 24.8% controls were found to be HPV positive. HPV was found to be significantly associated with OSCC (P
OBJECTIVES: To screen hypermethylated genes with a microarray approach and to validate selected hypermethylated genes with the methylation-specific polymerase chain reaction (MSPCR).
MATERIALS AND METHODS: Genome-wide analysis of normal oral mucosa and OSCC tissues was conducted using the Illumina methylation microarray. The specified differential genes were selected and hypermethylation status was further verified with an independent cohort sample of OSCC samples. Candidate genes were screened using microarray assay and run by MSPCR analysis.
RESULTS: TP73, PIK3R5, and CELSR3 demonstrated high percentages of differential hypermethylation status.
CONCLUSIONS: Our microarray screening and MSPCR approaches revealed that the signature candidates of differentially hypermethylated genes may possibly become potential biomarkers which would be useful for diagnostic, prognostic and therapeutic targets of OSCC in the near future.