Ataxia-Telangiectasia-Mutated Protein Expression as a Prognostic Marker in Adenoid Cystic Carcinoma of the Salivary Glands

PURPOSE: Adenoid cystic carcinoma (ACC) is a high-grade malignant tumor of the salivary glands, clinically characterized by multiple recurrences and late distant metastasis. Biological markers for assessing the prognosis of ACC have remained elusive. The purpose of this study was to investigate whether the protein expressions of ataxia telangiectasia mutated (ATM), p53, and ATM-mediated phosphorylated p53 are related to patient survival in ACC. MATERIALS AND METHODS: In this study, 48 surgical samples were used to assess the expressions of ATM and its downstream target p53. Fisher's exact test and Kaplan-Meier analysis were conducted to evaluate the role of ATM, p53, and phospho-p53 (S15) protein expressions in predicting patient survival and distant metastasis. RESULTS: Myb expression was positive in 85.4% of ACCs, but did not reflect patient survival rate. In contrast, low expression of ATM in cancer cells was significantly correlated with poor survival rate (p=0.037). Moreover, under positive p53 expression, low expression of ATM was highly predictive of poor survival in ACC (p=0.017). CONCLUSION: These data indicate that combined assessment of ATM and p53 expression can serve as a useful prognostic marker for assessing survival rate in patients with ACC of the salivary glands.ope

Paip1 overexpression is involved in the progression of gastric cancer and predicts shorter survival of diagnosed patients

Background: Gastric cancer (GC) is a major leading cause of cancer mortality worldwide. Polyadenylate (poly(A))-binding protein (PABP)-interacting protein 1 (Paip1) is a key regulator in the initiation of translation; however, its role in GC remains to be investigated. Purpose: The purpose of this study is to determine Paip1 expression levels and investigate its underlying molecular mechanism in GC. Patients and methods: In the present study, a total of 90 GC samples and 90 adjacent noncancerous tissues were used to examine the expression of Paip1. In order to gain a deep insight into the molecular mechanism of Paip1 in GC, the Paip1 siRNA sequences were transfected into GC cell lines (MGC-803 and SGC-7901), respectively. Meanwhile, Paip1 plasmid was used to mediate overexpression of Paip1. Cell proliferation were examined via colony formation assay, EdU assay and flow cytometry assay. Cell metastasis were discovered via wound healing assay and Transwell assays. In addition, key EMT makers were detected by Western blotting assay. Results: In this study, Paip1 expression was observed to be upregulated in GC and was associated with shorter overall survival. Knockdown of Paip1 inhibited cell proliferation, migration and caused cell cycle arrest in GC cells, whereas its overexpression reversed these effects. Another mechanistic study showed that Paip1 overexpression promoted EMT progression and regulated its targets expression. Conclusion: High expression of Paip1 plays a significant role in the progression of GC and may be a potential biomarker of poor prognosis as well as a therapeutic target.ope

Cancer-associated fibroblast stimulates cancer cell invasion in an interleukin-1 receptor (IL-1R)-dependent manner

Tumor microenvironment serves an important role in tumor growth and metastasis. Cancer cells can promote growth and malignancy by altering the surrounding stroma. Cancer-associated fibroblast (CAF) are an abundant cell type present within the tumor microenvironment and provide tumorigenic features by secreting cytokines. In the current study, the CAF-mediated invasion of oral squamous cell carcinoma (OSCC) was investigated and the associated mechanisms were elucidated. Cancer invasion was estimated using a Matrigel-coated Transwell chamber and FITC-gelatin matrix. To verify the effect of the tumor microenvironment, conditioned media (CM) from normal fibroblast (NF) and CAFs were prepared. An ELISA was performed to estimate the level of IL-1β. A proteome profiler human protease array was performed to verify the proteases affected by stimulation with CM, from CAF. Recombinant IL-1β protein increased the invasion of OSCC cells. IL-1β expression was higher in CAF than NF. CM from CAF (CM-CAF) increased cancer invasion and FITC-gelatin matrix degradation. The invasive capacity provided by CAF was abrogated by an IL-1 receptor (IL-1R) antagonist. Additionally, CM-CAF increased the secretion of ADAM 9 and Kallikrein 11 from OSCC cells. The invasion activity by CM-CAF was partially abrogated by the neutralization of ADAM 9 or Kallikrein 11. In conclusion, by providing stromal factor, CAFs were a critical inducer of OSCC invasion, and CAF secretes the required amount of IL-1β to increase cancer invasion activity. The invasive capacity of CAF was identified to be IL-1R-dependent. ADAM 9 and Kallikrein 11 were influencing factors involved in the increase of CAF-mediated cancer invasion.ope

The Axin2-snail axis promotes bone invasion by activating cancer-associated fibroblasts in oral squamous cell carcinoma

Background: In bone-invasive oral squamous cell carcinoma (OSCC), cancer-associated fibroblasts (CAFs) infiltrate into bony tissue ahead of OSCC cells. In the present study, we aimed to investigate the role of the Axin2-Snail axis in the biological behaviour of CAFs and bone invasion in OSCC. Methods: The clinicopathological significance of Axin2 and Snail expression was investigated by immunohistochemistry in an OSCC cohort containing 217 tissue samples from patients with long-term follow-up. The influence of the Axin2-Snail axis on the biological behaviour of OSCC cells and CAFs was further investigated both in vitro and in vivo. Results: Axin2 expression was significantly associated with Snail expression, the desmoplasia status, and bone invasion in patients with OSCC. In multivariate analysis, lymph node metastasis, desmoplasia, Axin2 expression, and Snail expression were independent poor prognostic factors in our cohort. Consistent with these findings, OSCC cells demonstrated attenuated oncogenic activity as well as decreased expression of Snail and various cytokines after Axin2 knockdown in vitro. Among the related cytokines, C-C motif chemokine ligand 5 (CCL5) and interleukin 8 (IL8) demonstrated a strong influence on the biological behaviour of CAFs in vitro. Moreover, both the desmoplastic reaction and osteolytic lesions in the calvaria were predominantly decreased after Axin2 knockdown in OSCC cells in vivo using a BALB/c athymic nude mouse xenograft model. Conclusions: Oncogenic activities of the Axin2-Snail axis are not limited to the cancer cells themselves but rather extend to CAFs via regulation of the cytokine-mediated cancer-stromal interaction, with further implications for bone invasion as well as a poor prognosis in OSCC.ope

Identification of combined biomarkers for predicting the risk of osteoporosis using machine learning

Osteoporosis is a severe chronic skeletal disorder that affects older individuals, especially postmenopausal women. However, molecular biomarkers for predicting the risk of osteoporosis are not well characterized. The aim of this study was to identify combined biomarkers for predicting the risk of osteoporosis using machine learning methods. We merged three publicly available gene expression datasets (GSE56815, GSE13850, and GSE2208) to obtain expression data for 6354 unique genes in postmenopausal women (45 with high bone mineral density and 45 with low bone mineral density). All machine learning methods were implemented in R, with the GEOquery and limma packages, for dataset download and differentially expressed gene identification, and a nomogram for predicting the risk of osteoporosis was constructed. We detected 378 significant differentially expressed genes using the limma package, representing 15 major biological pathways. The performance of the predictive models based on combined biomarkers (two or three genes) was superior to that of models based on a single gene. The best predictive gene set among two-gene sets included PLA2G2A and WRAP73. The best predictive gene set among three-gene sets included LPN1, PFDN6, and DOHH. Overall, we demonstrated the advantages of using combined versus single biomarkers for predicting the risk of osteoporosis. Further, the predictive nomogram constructed using combined biomarkers could be used by clinicians to identify high-risk individuals and in the design of efficient clinical trials to reduce the incidence of osteoporosis.ope

Risk of radiation-induced pneumonitis after helical and static-port tomotherapy in lung cancer patients and experimental rats

BACKGROUND: Radiotherapy (RT) is one of the major non-operative treatment modalities for treating lung cancer. Tomotherapy is an advanced type of intensity-modulated radiotherapy (IMRT) in which radiation may be delivered in a helical fashion. However, unexpected pneumonitis may occur in patients treated with tomotherapy, especially in combination with chemotherapy, as a result of extensive low-dose radiation of large lung volumes. The aim of our study was to investigate the risk of radiation-induced pneumonitis after helical-mode and static-mode tomotherapy in patients with lung cancer and in an animal model. METHOD: A total of 63 patients with primary lung cancer who were treated with static or helical tomotherapy with or without concurrent chemoradiotherapy (CCRT) were analyzed. Additionally, rats with radiation-induced pulmonary toxicity, which was induced by the application of helical or static tomography with or without CCRT, were evaluated. RESULTS: Helical-mode tomotherapy resulted in a significantly higher rate of late radiation pneumonitis in lung cancer patients than static-mode tomotherapy when evaluated by the Radiation Therapy Oncology Group (RTOG) and National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) scoring system. In the animal model, helical tomotherapy alone induced significantly higher expression of interleukin (IL)-1α, IL-1β, IL-6, and transforming growth factor (TGF)-β in lung specimens, especially on the untreated side, compared to static tomotherapy alone. Additionally, rats treated with helical tomotherapy and CCRT demonstrated significantly higher expression of inflammatory cytokines compared to those treated with static tomotherapy and CCRT. CONCLUSION: Rat models treated with tomotherapy with or without CCRT could present similar patterns of pulmonary toxicity to those shown in lung cancer patients. The models can be used in further investigations of radiation induced pulmonary toxicity.ope

Use of a Combined Gene Expression Profile in Implementing a Drug Sensitivity Predictive Model for Breast Cancer

PURPOSE: Chemotherapy targets all rapidly growing cells, not only cancer cells, and thus is often associated with unpleasant side effects. Therefore, examination of the chemosensitivity based on genotypes is needed in order to reduce the side effects. MATERIALS AND METHODS: Various computational approaches have been proposed for predicting chemosensitivity based on gene expression profiles. A linear regression model can be used to predict the response of cancer cells to chemotherapeutic drugs, based on genomic features of the cells, and appropriate sample size for this method depends on the number of predictors. We used principal component analysis and identified a combined gene expression profile to reduce the number of predictors. RESULTS: The coefficients of determinanation (R2) of prediction models with combined gene expression and several independent gene expressions were similar. Corresponding F values, which represent model significances were improved by use of a combined gene expression profile, indicating that the use of a combined gene expression profile is helpful in predicting drug sensitivity. Even better, a prediction model can be used even with small samples because of the reduced number of predictors. CONCLUSION: Combined gene expression analysis is expected to contribute to more personalized management of breast cancer cases by enabling more effective targeting of existing therapies. This procedure for identifying a cell-type-specific gene expression profile can be extended to other chemotherapeutic treatments and many other heterogeneous cancer types.ope

CXCL1 induces senescence of cancer-associated fibroblasts via autocrine loops in oral squamous cell carcinoma

Cancer-associated fibroblasts (CAFs) have emerged as one of the main factors related to cancer progression, however, the conversion mechanism of normal fibroblasts (NOFs) to CAFs has not been well elucidated. The aim of this study was to investigate the underlying mechanism of CAF transformation from NOFs in oral squamous cell carcinoma (OSCC). This study found that NOFs exposed to OSCC cells transformed to senescent cells. The cytokine antibody array showed the highest secretion levels of IL-6 and CXCL1 in NOFs co-cultured with OSCC cells. Despite that both IL-6 and CXCL1 induced the senescent phenotype of CAFs, CXCL1 secretion showed a cancer-specific response to transform NOFs into CAFs in OSCC, whereas IL-6 secretion was eventuated by common co-culture condition. Further, CXCL1 was released from NOFs co-cultured with OSCC cells, however, CXCL1 was undetectable in mono-cultured NOFs or co-cultured OSCC cells with NOFs. Taken together, this study demonstrates that CXCL1 can transform NOFs into senescent CAFs via an autocrine mechanism. These data might contribute to further understanding of CAFs and to development of a potential therapeutic approach targeting cancer cells-CAFs interactions.ope

Highly preserved consensus gene modules in human papilloma virus 16 positive cervical cancer and head and neck cancers

In this study, we investigated the consensus gene modules in head and neck cancer (HNC) and cervical cancer (CC). We used a publicly available gene expression dataset, GSE6791, which included 42 HNC, 14 normal head and neck, 20 CC and 8 normal cervical tissue samples. To exclude bias because of different human papilloma virus (HPV) types, we analyzed HPV16-positive samples only. We identified 3824 genes common to HNC and CC samples. Among these, 977 genes showed high connectivity and were used to construct consensus modules. We demonstrated eight consensus gene modules for HNC and CC using the dissimilarity measure and average linkage hierarchical clustering methods. These consensus modules included genes with significant biological functions, including ATP binding and extracellular exosome. Eigengen network analysis revealed the consensus modules were highly preserved with high connectivity. These findings demonstrate that HPV16-positive head and neck and cervical cancers share highly preserved consensus gene modules with common potentially therapeutic targets.ope

Identification of a combined biomarker for malignant transformation in oral submucous fibrosis

BACKGROUND: Oral submucous fibrosis (OSF) is a chronic progressive disease of the oral cavity that is considered a common potentially malignant disorder in South Asia. Areca nut chewing is the main etiological factor, but its carcinogenic mechanism has yet to be proven. The purpose of this study was to identify the useful biomarkers in predicting high-risk patients with OSF. METHODS: Thirty-six cases of OSF and six cases of normal oral mucosa (NOM) were used for this study. Immunohistochemical staining was performed for Ki67, cyclin D1, p16, p53, β-catenin, c-Jun, c-Met, and insulin-like growth factor II mRNA-binding protein 3 (IMP3). The expression patterns of NOM served as guidelines for the scoring system. RESULTS: The expression of Ki67, cyclin D1, c-Met, IMP3, and β-catenin showed a significant difference between OSF and NOM samples. The combined biomarkers of Ki67 and p16 showed significantly different expression between the transformation and non-transformation groups. With discriminant analysis, we proposed a noble formula and cutoff value for predicting high-risk patients with OSF. CONCLUSION: The notable biomarkers in our present study were Ki67 and p16 showing significantly different expression levels between the transformation and non-transformation groups. With the identification of high-risk patients with OSF, we can expect to develop more intensive treatment modalities, leading to the reduction in cancer transformation rate from OSF.ope