Todd Boren

Somatic LKB1 mutations promote cervical cancer progression.

Human Papilloma Virus (HPV) is the etiologic agent for cervical cancer. Yet, infection with HPV is not sufficient to cause cervical cancer, because most infected women develop transient epithelial dysplasias that spontaneously regress. Progression to invasive cancer has been attributed to diverse host factors such as immune or hormonal status, as no recurrent genetic alterations have been identified in cervical cancers. Thus, the pressing question as to the biological basis of cervical cancer progression has remained unresolved, hampering the development of novel therapies and prognostic tests. Here we show that at least 20% of cervical cancers harbor somatically-acquired mutations in the LKB1 tumor suppressor. Approximately one-half of tumors with mutations harbored single nucleotide substitutions or microdeletions identifiable by exon sequencing, while the other half harbored larger monoallelic or biallelic deletions detectable by multiplex ligation probe amplification (MLPA). Biallelic mutations were identified in most cervical cancer cell lines; HeLa, the first human cell line, harbors a homozygous 25 kb deletion that occurred in vivo. LKB1 inactivation in primary tumors was associated with accelerated disease progression. Median survival was only 13 months for patients with LKB1-deficient tumors, but >100 months for patients with LKB1-wild type tumors (P = 0.015, log rank test; hazard ratio = 0.25, 95% CI = 0.083 to 0.77). LKB1 is thus a major cervical tumor suppressor, demonstrating that acquired genetic alterations drive progression of HPV-induced dysplasias to invasive, lethal cancers. Furthermore, LKB1 status can be exploited clinically to predict disease recurrence.

MicroRNAs and their target messenger RNAs associated with endometrial carcinogenesis.

OBJECTIVE Recent advances in gene expression technology have provided insights into global messenger RNA (mRNA) expression changes associated with endometrial cancer development. However, the post-transcriptional events that may also have phenotypic consequences remain to be completely delineated. MicroRNAs (miRNAs) are small non-coding RNA transcripts, that influence cell function via modulation of post-transcriptional activity of multiple target mRNA genes. Although recent reports suggest that miRNAs may influence human cancer development, their role in endometrial carcinogenesis remains to be described. METHODS We measured expression of 335 unique human miRNAs in 61 fresh-frozen endometrial specimens, including 37 endometrial cancers, 20 normal endometrium, and 4 complex atypical hyperplasia samples. In parallel, expression of 22,000 mRNA genes was analyzed using the Affymetrix Human U133A GeneChips in 29 of the endometrial samples, including 20 endometrial carcinomas and 9 normal endometrial samples. Differentially expressed mRNAs, miRNAs, and predicted miRNA-mRNA targets were integrated and evaluated for representation of relevant functional biologic pathways. RESULTS Thirteen miRNAs (p<0.02) and 90 mRNAs (FDR; 0%) were identified to be associated with endometrial cancer development. Twenty-six of the 90 (29%) differentially expressed mRNAs are Sangar-database predicted mRNA targets of the 13 miRNAs. Pathway analysis demonstrates significant involvement of these 26 mRNA genes in processes including cell death, growth, proliferation, and carcinogenesis. CONCLUSION We have identified miRNAs and mRNAs associated with endometrial cancer development. Further, our strategy of integrating miRNA/mRNA data may also aid in the identification of important biologic pathways and additional unique genes that have importance in endometrial pathogenesis.

MicroRNAs and their target messenger RNAs associated with ovarian cancer response to chemotherapy

OBJECTIVE Few successful therapeutic options exist for patients with recurrent ovarian cancer (OVCA). This is due in part to an incomplete understanding of the molecular determinants of chemotherapy-response. Recently, it has been shown that microRNAs (miRNAs) influence messenger-RNA (mRNA) post-transcriptional control and can contribute to human carcinogenesis. The objective of the current study was to explore the role of miRNAs, and their predicted mRNA targets, in OVCA in-vitro response to chemotherapy. METHODS The expression of 335 unique miRNAs was measured in 16 OVCA cell lines. In parallel, the sensitivity of these cell lines to 6 commonly used chemotherapeutic agents (cisplatin, doxorubicin, topotecan, paclitaxel, docetaxel, and gemcitabine) was evaluated by in-vitro cell proliferation assay. MiRNAs associated with cell line drug response were identified by linear regression analysis, and their predicted mRNA targets subject to functional biologic pathway analyses. RESULTS Twenty-seven miRNAs were found to be associated with response to the one or more of the 6 salvage chemotherapies tested (p<0.05). Predicted targets of these miRNAs included 52 mRNAs, previously reported to be associated with chemo-responsiveness, and which are also involved in functional biologic pathways that influence cancer cell cytotoxicity, carcinogenesis, cell mitosis, p53 signaling, and tumor cell growth and invasion. CONCLUSION We have identified miRNAs and their predicted target mRNAs associated with ovarian cancer cell response to chemotherapeutic agents. Our strategy of integrating miRNA and mRNA data may aid in the characterization of important molecular pathways associated with OVCA chemo-response.

Microarray analysis of early stage serous ovarian cancers shows profiles predictive of favorable outcome.

Purpose: Although few women with advanced serous ovarian cancer are cured, detection of the disease at an early stage is associated with a much higher likelihood of survival. We previously used gene expression array analysis to distinguish subsets of advanced cancers based on disease outcome. In the present study, we report on gene expression of early-stage cancers and validate our prognostic model for advanced-stage cancers. Experimental Design: Frozen specimens from 39 stage I/II, 42 stage III/IV, and 20 low malignant potential cancers were obtained from four different sites. A linear discriminant model was used to predict survival based upon array data. Results: We validated the late-stage survival model and show that three of the most differentially expressed genes continue to be predictive of outcome. Most early-stage cancers (38 of 39 invasive, 15 of 20 low malignant potential) were classified as long-term survivors (median probabilities 0.97 and 0.86). MAL, the most differentially expressed gene, was further validated at the protein level and found to be an independent predictor of poor survival in an unselected group of advanced serous cancers (P = 0.0004). Conclusions: These data suggest that serous ovarian cancers detected at an early stage generally have a favorable underlying biology similar to advanced-stage cases that are long-term survivors. Conversely, most late-stage ovarian cancers seem to have a more virulent biology. This insight suggests that if screening approaches are to succeed it will be necessary to develop approaches that are able to detect these virulent cancers at an early stage.

A new feature selection algorithm for two-class classification problems and application to endometrial cancer

In this paper, we introduce a new algorithm for feature selection for two-class classification problems, called ℓ1-StaR. The algorithm consists of first extracting the statistically relevant features using the Student t-test, and then passing the reduced feature set to an ℓ1-norm support vector machine (SVM) with recursive feature elimination (RFE). The final number of features chosen by the ℓ1-StaR algorithm can be smaller than the number of samples, unlike with ℓ1-norm regression where the final number of features is bounded below by the number of samples. The algorithm is illustrated by applying it to the problem of determining which endometrial cancer patients are at risk of having the cancer spreading to their lymph nodes. The data consisted of 1,428 micro-RNAs measured on a data set of 94 patient samples (divided evenly between those with lymph node metastasis and those without). Using the algorithm, we identified a subset of just 15 micro-RNAs and a linear classifier based on these, that achieved two-fold cross validation accuracies in excess of 80%, and combined accuracy, sensitivity and specificity in excess of 93%.

Lymph node metastasis in endometrioid adenocarcinomas of the uterine corpus with occult cervical involvement

OBJECTIVE Surgical-pathologic studies have defined the risk of lymphatic metastasis in clinical stage I endometrial cancers. However, data on the risk of lymph node metastasis in endometrial cancers involving the uterine cervix are less robust. The aim of this study was to determine the risk of lymphatic metastasis in patients with endometrial cancers with occult tumor extension to the uterine cervix. METHODS Our institutional tumor registry identified all patients with endometrioid endometrial cancers who underwent comprehensive surgical staging. Patients with gross involvement of the cervix and patients with extra-uterine disease were excluded. The risk of lymphatic metastasis associated with cervical involvement was analyzed in the context of known uterine risk factors for lymphatic metastasis such as age, depth of invasion, grade, and lymphovascular space invasion (LVSI). RESULTS We identified 169 patients who met inclusion and exclusion criteria. Univariate analyses revealed that LVSI (p<0.01), tumor grade (p<0.01), depth of myometrial invasion (p<0.01), tumor free distance (p<0.01), tumor size (p=0.02), and cervical involvement (p<0.01) were associated with lymphatic metastasis while age at diagnosis (p=0.85) was not. Multivariate analyses revealed that only LVSI (p<0.01), tumor grade (p=0.02), and depth of myometrial invasion (p=0.03) were independently associated with lymphatic metastasis. CONCLUSION Cervical involvement is not an independent predictor of lymphatic metastasis in endometrial cancer. In an unstaged patient, decisions regarding adjuvant treatment or additional diagnostic procedures such as lymphadenectomy should be based on uterine factors.

Sparse feature selection for classification and prediction of metastasis in endometrial cancer

BackgroundMetastasis via pelvic and/or para-aortic lymph nodes is a major risk factor for endometrial cancer. Lymph-node resection ameliorates risk but is associated with significant co-morbidities. Incidence in patients with stage I disease is 4–22% but no mechanism exists to accurately predict it. Therefore, national guidelines for primary staging surgery include pelvic and para-aortic lymph node dissection for all patients whose tumor exceeds 2cm in diameter. We sought to identify a robust molecular signature that can accurately classify risk of lymph node metastasis in endometrial cancer patients. 86 tumors matched for age and race, and evenly distributed between lymph node-positive and lymph node-negative cases, were selected as a training cohort. Genomic micro-RNA expression was profiled for each sample to serve as the predictive feature matrix. An independent set of 28 tumor samples was collected and similarly characterized to serve as a test cohort.ResultsA feature selection algorithm was designed for applications where the number of samples is far smaller than the number of measured features per sample. A predictive miRNA expression signature was developed using this algorithm, which was then used to predict the metastatic status of the independent test cohort. A weighted classifier, using 18 micro-RNAs, achieved 100% accuracy on the training cohort. When applied to the testing cohort, the classifier correctly predicted 90% of node-positive cases, and 80% of node-negative cases (FDR = 6.25%).ConclusionResults indicate that the evaluation of the quantitative sparse-feature classifier proposed here in clinical trials may lead to significant improvement in the prediction of lymphatic metastases in endometrial cancer patients.

Genomic-directed targeted therapy increases endometrial cancer cell sensitivity to doxorubicin

OBJECTIVE We aimed to utilize genome-wide expression analysis to identify molecular pathways that may contribute to endometrial cancer resistance to doxorubicin (DOX) and that also represent therapeutic targets to increase DOX sensitivity. STUDY DESIGN Ten endometrial cancer cell lines were subjected to gene expression analysis. Sensitivity of each endometrial cell line to DOX was quantified by dimethylthiazoldiphenyltetrazoliumbromide cell proliferation assay. Pearsons correlation test was used to identify genes associated with response to DOX. Genes associated with DOX responsiveness were analyzed, and identified pathways were subjected to targeted inhibition. RESULTS Pearsons correlation analysis identified 2871 genes associated with DOX resistance (P < .05), which included members of the Src pathway. Targeted inhibition of the Src pathway increased DOX sensitivity in RL 95-2 (P < .0001), HEC 1B (P < .001), MEF 296 (P < .05), and MEF 280 (P = .14) cell lines. CONCLUSION Genomic analysis can identify therapeutic targets such as the Src pathway that may influence endometrial cancer DOX sensitivity.

Correlation of cone biopsy with findings at radical hysterectomy and use of adjuvant radiation therapy

OBJECTIVE To determine if pathologic findings in cone biopsy specimens correlate with residual invasive disease in radical hysterectomy specimens and the need for adjuvant chemo-radiation therapy. STUDY DESIGN We identified 65 patients who underwent a cone biopsy and subsequent radical hysterectomy. Clinico-pathologic parameters in the cone specimens were correlated with the presence of residual invasive disease in the radical hysterectomy specimens and the need for adjuvant chemo-radiation. RESULTS A positive endocervical margin, a positive deep margin, a positive post-cone ECC, and positive LVSI were significantly associated with the presence of residual disease in the radical hysterectomy specimen, while positive LVSI, a positive ECC, a positive deep cone margin, and greater than 1 positive margin were significantly associated with the use of adjuvant chemo-radiation therapy. CONCLUSION Pathologic parameters in cone biopsy specimens can estimate the risk of residual invasive disease in radical hysterectomy specimens and the use of adjuvant chemo-radiation.