5'-CpG island methylation of the FHIT gene is associated with reduced protein expression and higher clinical stage in cervical carcinomas

Recent findings on epigenetic gene abnormalities involved in uterine cancer

Selective aberrant genetic effects that do not depend on abnormal DNA sequences are referred to as epigenetic abnormalities and are involved in carcinogenesis. In uterine cancer, various genes involved in apoptosis, cell cycle, DNA repair, cell proliferation and cell adhesion are abnormally methylated, resulting in gene silencing. Reversal of such epigenetic abnormalities in cancer cells is a potential strategy for cancer therapy, and studies on epigenetic abnormalities and treatment methods in uterine cancer are in progress. These include the evaluation of 5-hydroxymethylcytosine, which is present in cancer tissues at lower levels compared with those in normal tissues, as a prognostic marker in cervical cancer; combination therapy with 5-azacytidine and cisplatin; combination treatment focusing on tumor necrosis factor-related apoptosis-inducing ligand in cervical cancer; studies focusing on DNA mismatch repair in endometrial cancer; and use of a demethylating agent to reactivate tumor suppressor genes and inhibit tumor proliferation. Detection of epigenetic changes using biomarkers may be used for histological classification, evaluation of disease progression and identification of compounds that are able to modulate epigenetic changes and may be useful for uterine cancer treatment.

The clinicopathological significance and ethnic difference of FHIT hypermethylation in non-small-cell lung carcinoma: a meta-analysis and literature review

Emerging evidence indicates that FHIT is a candidate tumor suppressor in many types of tumors including non-small-cell lung carcinoma (NSCLC). However, the prognostic value and correlation between FHIT hypermethylation and clinicopathological characteristics of NSCLC remains unclear. In this report, we performed a meta-analysis to evaluate the effects of FHIT hypermethylation on the incidence of NSCLC and clinicopathological characteristics of human NSCLC patients. Final analysis of 1,801 NSCLC patients from 18 eligible studies was performed. FHIT hypermethylation was found to be significantly higher in NSCLC than in normal lung tissue. The pooled odds ratio (OR) from ten studies included 819 NSCLC and 792 normal lung tissues (OR =7.51, 95% confidence interval [CI] =2.98-18.91, P<0.0001). Subgroup analysis based on ethnicity implied that FHIT hypermethylation level was higher in NSCLC tissues than in normal tissues in both Caucasians (P=0.02) and Asians (P<0.0001), indicating that the difference in Asians was much more significant. FHIT hypermethylation was also correlated with sex status, smoking status, as well as pathological types. In addition, patients with FHIT hypermethylation had a lower survival rate than those without (hazard ratio =1.73, 95% CI =1.10-2.71, P=0.02). The results of this meta-analysis suggest that FHIT hypermethylation is associated with an increased risk and poor survival in NSCLC patients. FHIT hypermethylation, which induces the inactivation of FHIT gene, plays an important role in the carcinogenesis and clinical outcome and may serve as a potential diagnostic marker and drug target of NSCLC.

The clinicopathological significance of FHIT hypermethylation in non-small cell lung cancer, a meta-analysis and literature review

Emerging evidence indicates that FHIT is a candidate tumor suppressor in non-small cell lung cancer (NSCLC). However, the correlation between FHIT hypermethylation and clinicopathological characteristics of NSCLC remains unclear. Thus, we conducted a meta-analysis to quantitatively evaluate the effects of FHIT hypermethylation on the incidence of NSCLC and clinicopathological characteristics. Final analysis of 1717 NSCLC patients from 16 eligible studies was performed. FHIT hypermethylation was found to be significantly higher in NSCLC than in normal lung tissue, the pooled OR from 8 studies including 735 NSCLC and 708 normal lung tissue, OR = 5.45, 95% CI = 2.15-13.79, p = 0.0003. FHIT hypermethylation was also correlated with sex status, smoking status, as well as pathological types. We did not find that FHIT hypermethylation was correlated with the differentiated types or clinical stages in NSCLC patients. However, patients with FHIT hypermethylation had a lower survival rate than those without, HR = 1.73, 95% CI = 1.10-2.71, p = 0.02. The results of this meta-analysis suggest that FHIT hypermethylation is associated with an increased risk and worsen survival in NSCLC patients. FHIT hypermethylation, which induces the inactivation of FHIT gene, plays an important role in the carcinogenesis and clinical outcome and may serve as a potential drug target of NSCLC.

Fragile histidine triad protein: structure, function, and its association with tumorogenesis

BACKGROUND

The human fragile histidine triad (FHIT) gene is a putative tumor suppressor gene, which is located at chromosome region 3p14.2. It was suggested that the loss of heterozygosity (LOH), homozygous deletions, and abnormal expression of the FHIT gene were involved in several types of human malignancies.

MATERIALS AND METHODS

To determine the role of FHIT in various cancers, we have performed structural and functional analysis of FHIT in detail.

RESULTS AND DISCUSSION

The protein FHIT catalyzes the Mg(2+) dependent hydrolysis of P1-5 cent-O-adenosine-P3-5 cent-O-adenosine triphosphate, Ap3A, to AMP, and ADP. The reaction is thought to follow a two-step mechanism. Histidine triad proteins, named for a motif related to the sequence H-cent-H-cent-H-cent-cent- (cent, a hydrophobic amino acid), belong to superfamily of nucleotide hydrolases and transferases. This enzyme acts on the R-phosphate of ribonucleotides, and contain a approximately 30-kDa domain that is typically a homodimer of approximately 15 kDa polypeptides with catalytic site.

CONCLUSION

Here we have gathered information is known about biological activities of FHIT, the structural and biochemical bases for their functions. Our approach may provide a comparative framework for further investigation of FHIT.

Utility of methylation markers in cervical cancer early detection: appraisal of the state-of-the-science

OBJECTIVE

We wanted to identify the most promising methylation marker candidates for cervical cancer early detection.

METHODS

A systematic literature review was performed in Medline and weighted average frequencies for methylated genes stratified by tissue source and methods used were computed.

RESULTS

51 studies were identified analyzing 68 different genes for methylation in 4376 specimens across all stages of cervical carcinogenesis. 15 genes, DAPK1, RASSF1, CDH1, CDKN2A, MGMT, RARB, APC, FHIT, MLH1, TIMP3, GSTP1, CADM1, CDH13, HIC1, and TERT have been analyzed in 5 or more studies. The published data on these genes is highly heterogeneous; 7 genes (CDH1, FHIT, TERT, CDH13, MGMT, TIMP3, and HIC1) had a reported range of methylation frequencies in cervical cancers of greater than 60% between studies. Stratification by analysis method did not resolve the heterogeneity. Three markers, DAPK1, CADM1, and RARB, showed elevated methylation in cervical cancers consistently across studies.

CONCLUSIONS

There is currently no methylation marker that can be readily translated for use in cervical cancer screening or triage settings. Large, well-conducted methylation profiling studies of cervical carcinogenesis could yield new candidates that are more specific for HPV-related carcinogenesis. New candidate markers need to be thoroughly validated in highly standardized assays.

A hybrid machine learning-based method for classifying the Cushing's Syndrome with comorbid adrenocortical lesions

BACKGROUND

The prognosis for many cancers could be improved dramatically if they could be detected while still at the microscopic disease stage. It follows from a comprehensive statistical analysis that a number of antigens such as hTERT, PCNA and Ki-67 can be considered as cancer markers, while another set of antigens such as P27KIP1 and FHIT are possible markers for normal tissue. Because more than one marker must be considered to obtain a classification of cancer or no cancer, and if cancer, to classify it as malignant, borderline, or benign, we must develop an intelligent decision system that can fullfill such an unmet medical need.

RESULTS

We have developed an intelligent decision system using machine learning techniques and markers to characterize tissue as cancerous, non-cancerous or borderline. The system incorporates learning techniques such as variants of support vector machines, neural networks, decision trees, self-organizing feature maps (SOFM) and recursive maximum contrast trees (RMCT). These variants and algorithms we have developed, tend to detect microscopic pathological changes based on features derived from gene expression levels and metabolic profiles. We have also used immunohistochemistry techniques to measure the gene expression profiles from a number of antigens such as cyclin E, P27KIP1, FHIT, Ki-67, PCNA, Bax, Bcl-2, P53, Fas, FasL and hTERT in several particular types of neuroendocrine tumors such as pheochromocytomas, paragangliomas, and the adrenocortical carcinomas (ACC), adenomas (ACA), and hyperplasia (ACH) involved with Cushing's syndrome. We provided statistical evidence that higher expression levels of hTERT, PCNA and Ki-67 etc. are associated with a higher risk that the tumors are malignant or borderline as opposed to benign. We also investigated whether higher expression levels of P27KIP1 and FHIT, etc., are associated with a decreased risk of adrenomedullary tumors. While no significant difference was found between cell-arrest antigens such as P27KIP1 for malignant, borderline, and benign tumors, there was a significant difference between expression levels of such antigens in normal adrenal medulla samples and in adrenomedullary tumors.

CONCLUSIONS

Our frame work focused on not only different classification schemes and feature selection algorithms, but also ensemble methods such as boosting and bagging in an effort to improve upon the accuracy of the individual classifiers. It is evident that when all sorts of machine learning and statistically learning techniques are combined appropriately into one integrated intelligent medical decision system, the prediction power can be enhanced significantly. This research has many potential applications; it might provide an alternative diagnostic tool and a better understanding of the mechanisms involved in malignant transformation as well as information that is useful for treatment planning and cancer prevention.

Epigenetics of cervical cancer. An overview and therapeutic perspectives

Cervical cancer remains one of the greatest killers of women worldwide. It is difficult to foresee a dramatic increase in cure rate even with the most optimal combination of cytotoxic drugs, surgery, and radiation; therefore, testing of molecular targeted therapies against this malignancy is highly desirable. A number of epigenetic alterations occur during all stages of cervical carcinogenesis in both human papillomavirus and host cellular genomes, which include global DNA hypomethylation, hypermetylation of key tumor suppressor genes, and histone modifications. The reversible nature of epigenetic changes constitutes a target for transcriptional therapies, namely DNA methylation and histone deacetylase inhibitors. To date, studies in patients with cervical cancer have demonstrated the feasibility of reactivating the expression of hypermethylated and silenced tumor suppressor genes as well as the hyperacetylating and inhibitory effect upon histone deacetylase activity in tumor tissues after treatment with demethylating and histone deacetylase inhibitors. In addition, detection of epigenetic changes in cytological smears, serum DNA, and peripheral blood are of potential interest for development of novel biomolecular markers for early detection, prediction of response, and prognosis.

Alterations of common chromosome fragile sites in hematopoietic malignancies

Conditions of replication stress affect expression of all common fragile regions, including FRA3B (chromosome 3p14.2), FRA16D (16q23), FRA6E (6q26), FRA7G (7q31.2), and FRAXB (Xp22.3), and a number of cancer cell lines exhibit homozygous deletions in 2 or more common fragile regions. In 1996 the fragile histidine triad (FHIT) gene was isolated from the region encompassing the most active fragile FRA3B locus, and recently the WW domain-containing oxidoreductase gene (WWOX) was identified at FRA16D. These 2 fragile genes are altered or deleted in various epithelial tumors and exhibit tumor suppressor function. Aberration or absence of WWOX expression recently was detected in primary hematopoietic malignancies. The aberration resulted not only from genomic deletions but also possibly from epigenetic modifications associated with expression of fragility. Thus chromosomal aberrations at common fragile sites, in addition to the well-defined hallmark leukemia chromosome translocations, are involved in clinicopathological outcomes of hematopoietic malignancies.