Identification of novel prognostic markers in cervical intraepithelial neoplasia using LDMAS (LOH Data Management and Analysis Software).

BACKGROUND: Detection of Loss of Heterozygosity (LOH) is one of the most common molecular applications in the study of human diseases, in particular cancer. The technique is commonly used to examine whether a known tumour suppressor gene is inactivated or to map unknown tumour suppressor gene(s). However, with the increasing number of samples analysed using different software, no tool is currently available to integrate and facilitate the extensive and efficient data retrieval and analyses, such as correlation of LOH data with various clinical data sets. RESULTS: An algorithm to identify prognostic disease markers is devised and implemented as novel software called LDMAS. LDMAS is a software suite designed for data retrieval, management and integrated analysis of the clinico-pathological data and molecular results from independent databases. LDMAS is used in stratification of disease stages according to clinical stage or histological features and correlation of various clinico-pathological features with molecular findings to obtain relevant prognostic markers such as those used in predicting the outcome of cervical intraepithelial neoplasia (CIN). This approach lead to the identification of novel prognostic cervical cancer markers and extraction of useful clinical information such as correlation of Human Papilloma Virus (HPV) status with CIN lesions. CONCLUSIONS: A novel software called LDMAS is implemented and used to extract and identify prognostic disease markers. The software is used to successfully identify 4 novel prognostic markers that can be used to predict the outcome of CIN. LDMAS provides an essential platform for the extraction of useful information from large amount of data generated by LOH studies. LDMAS provides three unique and novel features for LOH analysis: (1) automatic extraction of relevant data from patient records and reports (2) correlation of LOH data with clinico-pathological data and (3) storage of complex data in flexible format. The first feature automates the creation of database of clinically relevant information from huge amount of data, the second feature extracts useful biomedical information such as prognostic markers in CIN and the third feature simplifies the statistical analyses of the data and allows non-statisticians to carry out the analysis. Additionally, LDMAS can be used to extract clinically useful markers from other diseases and interface to high throughput genotyping analysis software such as GDAS used to generate LOH data from Affymetrix GeneChip Mapping arrays.

Clonality analysis of archival cervical smears. Correlation of monoclonality with grade and clinical behavior of cervical intraepithelial neoplasia.

OBJECTIVE: To establish a polymerase chain reaction (PCR)-based clonality assay for archival cervical smears and examine its value in the detection of cervical intraepithelial neoplasia (CIN) and prediction of its clinical behavior. STUDY DESIGN: Dyskaryotic cells were microdissected from archival cervical smears of 33 cases and subjected to PCR-based clonality analysis of the androgen receptor gene. High-risk HPV subtypes were screened by PCR. RESULTS: Monoclonal patterns were found in 9/9 CIN 3 and 15/21 CIN 2, while polyclonal patterns were observed in the remaining 6 CIN 2 and 3/3 CIN 1. All patients with monoclonal CIN lesions, including 15 CIN 2, showed recurrence of the disease despite treatment. The original CIN 2 and recurrent CIN lesion in each of the 6 examined cases showed the same monoclonal pattern, suggesting a clonal link. In contrast, the patients with polyclonal CIN 1 or 2 became negative and remained disease free. High-risk HPV subtypes were found in all monoclonal CIN lesions, including 9 CIN 3 and 15 CIN 2, and in 4/6 polyclonal CIN 2 but not in CIN 1 lesions. CONCLUSION: Clonality analysis of cervical smears is potentially valuable in the identification of true neoplastic cells and prediction of clinical behavior of CIN 2 lesions.

Archival fixed histologic and cytologic specimens including stained and unstained materials are amenable to RT-PCR.

Formalin-fixed and paraffin-embedded tissues are increasingly used for analysis of gene expression. However, a large proportion of archival fixed histologic specimens including spare paraffin sections and stained slides, as well as archival cytologic materials, have not been investigated for their suitability for RNA-based analysis. The current study addressed this issue by reverse transcription and polymerase chain reaction (RT-PCR) of the glucose-6-phosphate dehydrogenase (G6PD) transcript in a series of archival histologic and cytologic specimens. The histologic specimens included freshly prepared paraffin sections, spare paraffin sections, hematoxylin and eosin-stained slides, immunostained slides, and decalcified bone marrow trephines. The cytologic specimens comprised cervical smears and various stained and unstained needle aspirates and cell sediments. The G6PD was amplified for five different fragment sizes ranging from 67 bp to 453 bp. It was found that the majority of archival materials were amenable to RT-PCR of small fragments with the overall success rates of 95% and 79% for 67 bp and 151 bp of the G6PD mRNA, respectively. Neither staining nor prolonged storage up to 15 years had major negative effects on RT-PCR, although fine-needle aspirates showed a higher rate of RT-PCR of 242-bp fragment than other types of cytologic specimens and so did Papanicolaou-stained samples than May Grounwald and Giemsa-stained samples. RT-PCR of minute cell populations microdissected from immunostained sections of tonsils and t(11;18)-positive mucosa-associated lymphoid tissue lymphomas showed that as few as 100 cells were adequate for RT-PCR of G6PD and translocation-associated fusion transcript as long as the target fragment was limited to less than 150 bp. Our results demonstrate that archival fixed histologic and cytologic specimens are valuable resources for RT-PCR-based molecular investigations.