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At least 325 records · Page 18Linked to original sources
PubMed2006

Can pT0 stage of prostate cancer be predicted before radical prostatectomy?

OBJECTIVES: To report our experience with biopsy-proven pT0 prostate cancer over the last 10 yr. METHODS: We retrospectively analysed a series of 1950 consecutive patients treated with radical prostatectomy (RP) for clinically localized prostate cancer between 1996 and 2005 at our institution. The patients without residual tumour on RP specimen were defined as pT0 patients. The group of pT0 patients was compared with a control group of 295 patients operated consecutively during the same period. RESULTS: Overall, 11 (0.5%) patients were classified as pT0 on pathologic examination of the RP specimen. There was no pT0 tumour in the control group. Among the pT0 patients, five characteristics were particularly frequent: T1c clinical stage (90.9%), prostate-specific antigen (PSA) or=60 g (100%). All these characteristics were present in 8 of the 11 (72.7%) pT0 patients, while they were present in only 12 of the 295 (4.1%) controls. These parameters, when combined together, had a sensitivity of 72%, a specificity of 96%, and an accuracy of 99% for the prediction of pT0 stage. With a mean follow-up of 30 months after RP, no pT0 patient had clinical or biologic evidence of prostate cancer. CONCLUSIONS: In our experience, the rate of pT0 tumours after RP is 0.5%. The combination of clinical stage, preoperative PSA, number of positive biopsy cores, Gleason score, and prostate weight could help to predict pT0 stage after RP.

Aged↗
PubMed1998

Relationship between cancer patients' predictions of prognosis and their treatment preferences.

CONTEXT: Previous studies have documented that cancer patients tend to overestimate the probability of long-term survival. If patient preferences about the trade-offs between the risks and benefits associated with alternative treatment strategies are based on inaccurate perceptions of prognosis, then treatment choices may not reflect each patient's true values. OBJECTIVE: To test the hypothesis that among terminally ill cancer patients an accurate understanding of prognosis is associated with a preference for therapy that focuses on comfort over attempts at life extension. DESIGN: Prospective cohort study. SETTING: Five teaching hospitals in the United States. PATIENTS: A total of 917 adults hospitalized with stage III or IV non-small cell lung cancer or colon cancer metastatic to liver in phases 1 and 2 of the Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments (SUPPORT). MAIN OUTCOME MEASURES: Proportion of patients favoring life-extending therapy over therapy focusing on relief of pain and discomfort, patient and physician estimates of the probability of 6-month survival, and actual 6-month survival. RESULTS: Patients who thought they were going to live for at least 6 months were more likely (odds ratio [OR], 2.6; 95% confidence interval [CI], 1.8-3.7) to favor life-extending therapy over comfort care compared with patients who thought there was at least a 10% chance that they would not live 6 months. This OR was highest (8.5; 95% CI, 3.0-24.0) among patients who estimated their 6-month survival probability at greater than 90% but whose physicians estimated it at 10% or less. Patients overestimated their chances of surviving 6 months, while physicians estimated prognosis quite accurately. Patients who preferred life-extending therapy were more likely to undergo aggressive treatment, but controlling for known prognostic factors, their 6-month survival was no better. CONCLUSIONS: Patients with metastatic colon and lung cancer overestimate their survival probabilities and these estimates may influence their preferences about medical therapies.

Adult↗
PubMed2006

Genetic profiling of stage I and II colorectal cancer may predict metastatic relapse.

A substantial number of patients with early-stage colorectal cancer relapse from metastatic disease. Identification of these patients by genetic profiling of their primary tumours may allow more informed follow-up and tailored administration of adjuvant therapy. Primary tumours from 70 patients with early-stage and largely microsatellite-stable colorectal cancer were profiled using metaphase-based comparative genomic hybridization (CGH) and the aberrations confirmed independently in a subset of patients using microarray-based CGH. Of the 70 cancers, 61 were amenable to CGH, and follow-up data was available from 56 patients. Genomic aberrations were correlated with patients' survival using univariate, multivariate and Kaplan-Meier survival curves. Metastatic primary tumours exhibited more complex genomic aberrations than non-metastatic primary tumours. Loss of chromosome 4p was an independent prognostic factor in early-stage colorectal cancer using multivariate analysis (Hazard ratio, 9.6; 95% CI, 3.3-28; P = 0.0001). Loss of both chromosome arms 8p and 18q had a statistically significant negative effect on disease-free survival. Moreover, primary tumours with loss of both chromosomes 4 and 14q bestowed poorer prognosis than tumours with loss of any one of the two chromosomes (P<0.0001). Genetic profiling of primary tumours of patients with early-stage colorectal cancer is of significant value in identifying the subset of patients who may relapse with metastatic disease. Accordingly, the molecular genetic features of primary tumours should be considered in the mainstream management of patients with this specific stage of the disease.

Aged↗
PubMed2000

Molecular markers for predicting prostate cancer stage and survival.

OBJECTIVE: To assess several molecular markers (detected by immunohistochemistry, IHC) to determine whether they can be used to improve the prognostic value of histological grade alone in predicting the behaviour of prostate cancer. PATIENTS AND METHODS: Tumour tissue was retrieved from 156 men in whom tumour grade, stage and survival were known. The outcome measures were: (i) local stage (T-stage, organ-confined vs extraprostatic); (ii) metastatic status (M-stage, bone metastasis vs no bone metastasis); and (iii) survival. The IHC markers used were chosen to provide a broad representation of various aspects of tumour biology, i.e. the androgen receptor (AR) and oestrogen receptor (ER), adhesion molecules (E-cadherin), proliferation markers (MIB-1), tumour-suppressor genes (TP53 and the retinoblastoma gene product, Rb) and other novel cancer-related proteins (cyclin D1 and the breast cancer susceptibility gene product, BRCA2). All factors were assessed using logistic regression and Cox proportional-hazards survival models for predictive value, after adjusting for effects. RESULTS: MIB-1, ER, cyclin D1 and E-cadherin all showed close statistically significant univariate associations with histological grade. Univariate analysis also identified close statistically significant associations between T-stage and both MIB-1 and E-cadherin. Likewise, there were close univariate associations for both M-stage and survival, and MIB-1, cyclin D1 and ER. Logistic regression modelling identified MIB-1, cyclin D1 and ER as statistically significant predictors of M-stage and, once MIB-1 was entered into the model, the effects of grade no longer made a significant contribution. MIB-1 was a significant predictor for T-stage, but the effects of grade remained significant in this model. Cox proportional-hazards modelling identified MIB-1, cyclin D1 and ER as being statistically significant predictors of survival, after adjusting for grade. After adjusting for both grade and MIB-1, the effects of cyclin D1 and ER were no longer statistically significant. Excess MIB-1, cyclin D1 or ER expression tended to be present within the most poorly differentiated and advanced-stage lesions; this provides an inherent instability to the models described. TP53, Rb, AR and BRCA2 were of limited prognostic value. CONCLUSIONS: MIB-1, ER and cyclin D1 provide prognostic information that is clearly independent of grade. However, their true clinical value is probably limited because they are expressed mainly in the most advanced lesions. Nevertheless, MIB-1 expression is of sufficient value to warrant inclusion in future prognostic models. Furthermore, the expression of cyclin D1 and ER may reflect aspects of tumour biology that individually are worthy of further investigation. However, none of the IHC markers used in this study can be recommended for use in routine histological preparations.

Adult↗
PubMedDate not supplied

Predictive factors for irresectability in advanced ovarian cancer.

Despite advances in surgical modalities and chemotherapeutic agents, the 5-year survival for patients with advanced ovarian cancer is barely 40-50%. At the moment, optimally cytoreductive primary surgery is the best option for patients with advanced ovarian cancer. Predictive factors of primary optimum reduction surgery have been described based on imaging studies and tumor markers and based on the premise to know a priori the weight and tumor volume, with promising results. A retrospective study was conducted based on the hypothesis that it is feasible to identify those patients not susceptible of undergoing optimum primary cytoreductive surgery. The variables associated with a lesser probability of success in this study are the presence of palpable abdominal tumor on physical examination, the presence of tumor in Douglas' cul-de-sac on vaginal exploration, the presence of ascites in any quantity, elevation of CA-125 above 1000 U/l, and the presence of pulmonary and liver metastases. The success rate for cytoreduction was 62% when none or one of these variables was present and 32% when two or more variables were present.

Adolescent↗
PubMed2005

Ensemble dependence model for classification and prediction of cancer and normal gene expression data.

MOTIVATION: DNA microarray technologies make it possible to simultaneously monitor thousands of genes' expression levels. A topic of great interest is to study the different expression profiles between microarray samples from cancer patients and normal subjects, by classifying them at gene expression levels. Currently, various clustering methods have been proposed in the literature to classify cancer and normal samples based on microarray data, and they are predominantly data-driven approaches. In this paper, we propose an alternative approach, a model-driven approach, which can reveal the relationship between the global gene expression profile and the subject's health status, and thus is promising in predicting the early development of cancer. RESULTS: In this work, we propose an ensemble dependence model, aimed at exploring the group dependence relationship of gene clusters. Under the framework of hypothesis-testing, we employ genes' dependence relationship as a feature to model and classify cancer and normal samples. The proposed classification scheme is applied to several real cancer datasets, including cDNA, Affymetrix microarray and proteomic data. It is noted that the proposed method yields very promising performance. We further investigate the eigenvalue pattern of the proposed method, and we discover different patterns between cancer and normal samples. Moreover, the transition between cancer and normal patterns suggests that the eigenvalue pattern of the proposed models may have potential to predict the early stage of cancer development. In addition, we examine the effects of possible model mismatch on the proposed scheme.

Algorithms↗
PubMed2002

Higher expression of human kallikrein 10 in breast cancer tissue predicts tamoxifen resistance.

The human tissue kallikreins are secreted serine proteases, encoded by a group of homologous genes clustered in tandem on chromosome 19q13.3-4. Human kallikrein 6 and human kallikrein 10 are two new members of this family. Recently, we developed highly sensitive and specific immunofluorometric assays for human kallikrein 6 and human kallikrein 10, which allow for their quantification in tissue extracts and biological fluids. Both human kallikrein 6 and human kallikrein 10 are found to be down-regulated in breast cancer cell lines, suggesting that they may be involved in breast cancer pathogenesis and progression. In this study, we investigated the potential value of human kallikrein 6 and human kallikrein 10 as prognostic and predictive factors in breast cancer. We quantified human kallikrein 6 and human kallikrein 10 protein levels in 749 breast tumour cytosolic extracts and correlated this data with various clinicopathological variables and patient outcomes. Human kallikrein 6 and human kallikrein 10 are positively correlated with each other. Higher human kallikrein 6 and human kallikrein 10 protein levels are associated with younger age, pre-menopausal, status and tumours which are negative for oestrogen and progesterone receptors. No correlation was found between human kallikrein 6 and human kallikrein 10 levels and tumour size, grade, and nodal status. Survival analysis showed that neither human kallikrein 6 nor human kallikrein 10 are related to the rate of relapse-free and overall survival. In the analysis with respect to response to tamoxifen therapy, although human kallikrein 6 levels were not associated with tamoxifen responsiveness, higher levels of human kallikrein 10 were significantly associated with a poor response rate. This association remained significant in the multivariate analysis. Furthermore, higher human kallikrein 10 levels were significantly related with a short progression-free and post-relapse overall survival after start of tamoxifen treatment for advanced disease. Taken together, our results suggest that although human kallikrein 6 and human kallikrein 10 are not prognostic markers for breast cancer, human kallikrein 10 is an independent predictive marker for response of tamoxifen therapy.

Adult↗
PubMed2004

Combination of endometrial thickness and time since menopause in predicting endometrial cancer in women with postmenopausal bleeding.

PURPOSE: This study was conducted to assess the combination of endometrial thickness, as measured by transvaginal sonography, and time since menopause, in predicting the presence of endometrial cancer in women with postmenopausal bleeding. METHODS: The study group consisted of 95 women with postmenopausal bleeding who underwent sonographic measurement of endometrial thickness followed by endometrial biopsy. No patient had ever received hormone replacement therapy. RESULTS: The mean endometrial thickness was significantly lower in the absence of endometrial carcinoma (6.9 +/- 4.3 mm) than in its presence (13.5 +/- 7.7 mm) (p < 0.005). The incidence of endometrial carcinoma increased with increases in endometrial thickness and the number of years since menopause. No patient had carcinoma when the endometrium was less than 5 mm thick, but 18.5% did when the thickness exceeded 9 mm. The incidence of cancer was 2.6% in women who had undergone menopause less than 5 years earlier but was 21.4% in women who had undergone menopause more than 15 years prior. Multiple logistic regression analysis showed that time since menopause and endometrial thickness were statistically significant predictors of endometrial carcinoma. CONCLUSIONS: Time since menopause and endometrial thickness together define cutoff points for the diagnostic biopsy of tissue samples for endometrial carcinoma; that is, within a particular time interval, sampling should not be performed if the thickness is below a given value. When using cutoff points of 6 mm of endometrial thickness for women experiencing menopause 5-15 years prior and 5 mm in those going through menopause 15 or more years prior, approximately 60% of invasive procedures may be avoided. In addition, models derived by multiple logistic regression can be used to calculate a patient's risk of cancer based on her age and endometrial thickness.

Aged↗
PubMed2026

Plasma signals of lung tumor promotion for molecular cancer prevention.

Predicting lung cancer risk would enhance prevention trials. Although the Canakinumab Anti-inflammatory Thrombosis Outcome Study (CANTOS) trial demonstrated reduced lung cancer incidence with interleukin (IL)-1&#x3b2; inhibition, the high number needed to treat (NNT) to prevent lung cancer limits its use in unselected populations. Using machine learning, we identified a 14-protein plasma signature predicting lung cancer more than 5 years before diagnosis. The signature, validated across eight cohorts, was elevated in current smokers and individuals exposed to particulate matter (PM) and linked to lung myeloid and alveolar cells. In epidermal growth factor receptor (EGFR)-driven lung adenocarcinoma, diverse epithelial lineages converged on a keratin8+/claudin4+ alveolar transitional state (KAC), whose transcriptional programs correlated with signature emergence. Components of the signature were induced by PM, oncogenic EGFR, or IL-1&#x3b2;, whereas IL-1&#x3b2; inhibition restrained PM-driven KAC expansion and early tumorigenesis. In CANTOS, the signature identified individuals who seemed to benefit more from anti-IL-1&#x3b2; therapy, lowering the NNT threshold and nominating circulating signals of tumor promotion for prevention.

Humans↗
PubMed2004

Lung cancer mortality predictions for Ireland 2001-2015 and current trends in North Western Europe.

UNLABELLED: PURPOSE AND METHODOLOGY: Poisson regression models of Irish lung cancer mortality data for the years 1954-2000 were used to predict European age standardized mortality rates (EASMRs) and numbers of deaths for the period 2001-2015. Predictions for the whole population and for the age group 0-64 years were the main focus of this analysis. The models employed in this analysis were written for the STATA 6.0 STATISTICAL PACKAGE FOR WINDOWS. Linear models were applied, in general, to upward trends and log-linear models to downward trends. RESULTS: For males of all ages, EASMRs are expected to fall significantly from 59.7 per 100,000 person years (100,000 PY(-1)) in 2000 to 47.2 in the period 2011-2015. Female EASMRs are expected to fall from 28.3 100,000 PY(-1) in 2000 to 27.8 in 2011-2015. The EASMR for males under 65 years of age is predicted to continue its decline from 20.6 100,000 PY(-1) in 2000 to 11.7 in 2011-2015. The rate for females in this same age group is predicted to decline from 10.7 100,000 PY(-1) in 2000 to 7.0 in 2001-2015. Recent lung cancer trends In Ireland were also compared to other countries in North Western Europe.

Adolescent↗
PubMed2004

Preoperative neural network using combined magnetic resonance imaging variables, prostate-specific antigen, and gleason score for predicting prostate cancer biochemical recurrence after radical prostatectomy.

OBJECTIVES: To develop and test an artificial neural network (ANN) for predicting biochemical recurrence based on the combined use of pelvic coil magnetic resonance imaging (pMRI), prostate-specific antigen (PSA) measurement, and biopsy Gleason score, after radical prostatectomy and to investigate whether it is more accurate than logistic regression analysis (LRA) in men with clinically localized prostate cancer. METHODS: We evaluated 191 consecutive men who had undergone retropubic radical prostatectomy for clinically localized prostate cancer. None of the men had lymph node metastasis as determined by adequate follow-up and pathologic criteria. The preoperative predictive variables included clinical TNM stage, serum PSA level, biopsy Gleason score, and pMRI findings. The predicted result was biochemical failure (PSA level of 0.1 ng/mL or greater). The patient data were randomly split into four cross-validation sets and used to develop and validate the LRA and ANN models. The predictive ability of the ANN was compared with that of LRA, Han tables, and the Kattan nomogram using area under the receiver operating characteristic curve (AUROC) analysis. RESULTS: Of the 191 patients, 57 (30%) developed disease progression at a median follow-up of 64 months (mean 61, range 2 to 86). Using all the input variables, the AUROC of the ANN was significantly greater (P <0.05) than the AUROC of LRA, Han tables, or the Kattan nomogram for the prediction of PSA recurrence 5 years after radical prostatectomy (0.897 +/- 0.063 versus 0.785 +/- 0.060, 0.733 +/- 0.061, and 0.737 +/- 0.071, respectively). Removing the pMRI findings from the previous models, the AUROC of the ANN decreased statistically significantly (P <0.05) and was comparable to the AUROC of conventional predictive tools (P >0.05). CONCLUSIONS: Using the pMRI findings, the ANN was superior to LRA, predictive tables, and nomograms to predict biochemical recurrence accurately. Confirmatory studies are warranted.

Adult↗
PubMed2004

Isolated tumor cells in bone marrow three years after diagnosis in disease-free breast cancer patients predict unfavorable clinical outcome.

PURPOSE: The aim of the study was to explore the value of analyzing bone marrow (BM) for the presence of isolated tumor cell(s) (ITCs) in disease-free breast cancer patients 3 years after diagnosis. EXPERIMENTAL DESIGN: ITCs in BM at operation was found to be an independent prognostic factor in 817 breast cancer patients. Among these, 356 disease-free patients were analyzed with a second BM after 3 years follow-up (median 40 months, SD 3 months, range 29-52). ITC was detected by immunocytochemistry with anticytokeratine antibodies (AE1/AE3). RESULTS: The population consisted of 70% T1 and 72% node-negative patients. ITC in BM was detected in 15%. At a median of 25 months since the second BM aspiration (66 months since diagnosis), 32 patients had developed relapse, 12 local and 20 systemic. Of the patients with ITC in BM, 21% relapsed compared with 7% of the ITC-negative patients (P < 0.001). Ten patients died of breast cancer. Survival analyses showed that ITC in BM predicted reduced distant disease-free survival (DDFS) and breast cancer specific survival (BCSS; P < 0.001, log-rank test). Uni-and multivariate analyses of the prognostic value of N, T, estrogen receptor/progesterone receptor, and BM status, histological grade, vascular invasion, p53-, c-erb-B2-, and cathepsin D expression were performed. BM status was the only independent prognostic factor for both DDFS and BCSS, whereas c-erbB-2 and N status were independent for BCSS and vascular invasion and T status for DDFS. CONCLUSIONS: ITC in BM 3 years after diagnosis in disease-free breast cancer patients is an independent prognostic factor. Detection of residual disease by BM analysis at follow-up may unravel insufficient adjuvant treatment. The clinical implications should be further explored.

Biopsy, Needle↗
PubMed2003

Early change in patient-reported health during lung cancer chemotherapy predicts clinical outcomes beyond those predicted by baseline report: results from Eastern Cooperative Oncology Group Study 5592.

PURPOSE: To determine the ability of longitudinal patient-reported health (PRH) scores to enhance prediction of clinical outcomes beyond baseline scores. PATIENTS AND METHODS: In 573 advanced non-small-cell lung cancer patients enrolled in a phase III clinical trial, we used baseline and 6-week follow-up PRH scores to predict best response to treatment, disease progression, and survival. Using regression analyses, we tested the predictive ability of the five subscales of the Functional Assessment of Cancer Therapy-Lung (physical, functional, social/family, emotional well-being, and the lung cancer subscale) as well as the trial outcome index (TOI) aggregate score. RESULTS: After clinical factors were controlled for, baseline physical well-being (PWB) and TOI scores predicted all three clinical outcomes. A higher baseline PWB score was associated with a better response to treatment (odds ratio, 1.09; P <.001) and lower risk of death (risk ratio, 0.95; P <.001). Higher baseline TOI score was associated with a lower risk of disease progression (risk ratio, 0.98; P <.001). These two baseline predictors (PWB and TOI) were then used along with 6-week change scores to classify patients into four groups: low baseline-declined, low baseline-improved, high baseline-declined, and high baseline-improved. Patients with low baseline-declined PWB scores showed the worst responses to treatment and survived the shortest duration. Patients with low baseline-declined TOI scores had the shortest time to progression. CONCLUSION: The physical aspects of baseline PRH and PRH change during chemotherapy are significant predictors of clinical outcomes in lung cancer. This has implications for patient stratification in clinical trials and may aid decision-making in clinical practice.

Adult↗
PubMed1980

Breast thermography and cancer risk prediction.

Thermography makes a significant contribution to the evaluation of patients suspected of having breast cancer. The obviously abnormal thermogram carries with it a high risk of cancer. This report summarizes the results of patients with questionable or stage Th III thermograms. From approximately 58,000 patients, most of whom had breast complaints, examined between August 1965 and June 1977, the conditions or a group of 1,245 women were diagnosed at initial examination as either normal or benign disease by conventional means, including physical examination, mammography, ultrasonography, and fine needle aspiration or biopsy, when indicated, but nevertheless categorized as stage Th III indicating a questionable thermal anomaly. Within five years, more than a third of the group had histologically confirmed cancers. The more rapidly growing lesions with shorter doubling times usually show progressive thermographic abnormalities consistent with the increased metabolic heat production associated with such cancers. Thermography is useful not only as a predictor of risk factor for cancer but also to assess the more rapidly growing neoplasms.

Adult↗
PubMed1999

Molecular detection of neoplastic cells in lymph nodes of metastatic colorectal cancer patients predicts recurrence.

Disseminated disease, especially to the liver, constitutes the major risk of recurrence for colorectal cancer patients. However, successful resection can still be achieved in 25-35% of colorectal cancer patients with isolated metastases. To evaluate the clinical value of occult micrometastatic disease detection in lymph nodes, we tested genetic (K-ras and p53 gene mutations) and epigenetic (p16 promoter hypermethylation) molecular markers in the perihepatic lymph nodes from colorectal cancer patients with isolated liver metastases. DNA was extracted from 21 paraffin-embedded liver metastases and 80 lymph nodes from 21 colorectal cancer patients. K-ras and p53 gene mutations were identified in DNA from liver metastases by PCR amplification followed by cycle sequencing. A sensitive oligonucleotide-mediated mismatch ligation assay was used to search for the presence of K-ras and p53 mutations to detect occult disease in 68 lymph nodes from tumors positive for these gene mutations. Promoter hypermethylation at the p16 tumor suppressor gene was examined in both liver lesions and lymph nodes by methylation-specific PCR. Sixteen of the 21 (76%) liver metastases harbored either gene point mutations or p16 promoter hypermethylation. Twelve of the 68 lymph nodes were positive for tumor cells by molecular evaluation and negative for tumor cells by histopathology and cytokeratin immunohistochemistry, whereas none were positive for tumor cells by histopathology or negative for tumor cells by molecular analysis (P = 0.0005, McNemar's test). Moreover, in three patients with lymph nodes that were histologically negative at all sites, molecular screening detected tumor DNA at one or more lymph nodes. Survival analysis showed a median survival of 1056 days for patients without evidence of lymph node involvement by molecular analysis and 165 days for patients with positive lymph nodes by this approach (P = 0.0005). These results indicate that lymph node metastasis screening in colorectal cancer patients by molecular-based techniques increases the sensitivity of tumor cell detection and can be a good predictor of recurrence in colorectal cancer patients with resectable liver metastases.

Colorectal Neoplasms↗
PubMed2006

A repressive epigenetic domino effect confers susceptibility to breast epithelial cell transformation: implications for predicting breast cancer risk.

Retinoic acid (RA) is a master epigenetic regulator that plays a pivotal role in both breast morphogenesis and development. Here, we show for the first time that RA, via the RA receptor alpha (RARalpha), epigenetically regulates in a concerted fashion the transcription of two RA-responsive genes, the RA receptor beta2 (RARbeta2) and the cellular retinol-binding protein 1 (CRBP1). Specifically, an impaired RA signal through RARalpha in human breast epithelial cells triggers a repressive epigenetic domino effect, involving first RARbeta2 and second CRBP1. The phenotype acquired by breast epithelial cells clearly implies that the resistance to RA-mediated growth inhibition precedes the acquisition of morphological epithelial transformation, thus supporting the occurrence of sequential transcriptional silencing of first RARbeta2 and second CRBP1. The identification of this epigenetic network mechanistically linking RARbeta2 and CRBP1 transcription provides the basis for devising more accurate epigenetic tests for the prediction of breast cancer risk.

Breast↗
PubMed1999

Long-term chemical carcinogenesis bioassays predict human cancer hazards. Issues, controversies, and uncertainties.

Long-term carcinogenesis bioassays are the most valued and predictive means for identifying potential carcinogenic hazards of various agents to humans. Agents may be chemicals, chemical mixtures, multiple chemicals, combinations of chemicals, residues and contaminants, commercial products and formulations, and various exposure circumstances. Life-styles, dietary factors, and occupational exposure circumstances are very difficult, but not totally impossible, to evaluate experimentally. Historically, the first chemical bioassay took place in the early part of this century: Yamagiwa and Ichikawa in 1915, showed that coal tar applied experimentally to rabbit ears caused skin carcinomas. Since then, nearly 1500-2000 bioassays of one sort or another have been carried out. Importantly, however, some of these bioassays must be considered inadequate for judging the absence of carcinogenicity, since there were various limitations on the way they were performed: too few animals, too short a duration, too low exposure concentrations, too limited pathology, as examples. Thus, each bioassay must be critically evaluated, especially those reported to be negative, because "false negatives" are certainly more hazardous to human health than are "false positives". Likewise, one must be careful not to discount bioassay results simply because a target organ in rodents may not have a direct counterpart in humans (e.g., Zymbal glands), or because an organ site in rodents may not be a major site of cancers in humans (e.g., mouse liver). The design and conduct of a bioassay is not simple, however, and one must be fully aware of possible pitfalls as well as viable and often necessary alternatives. Similarly, evaluating results and interpreting findings must be approached with the utmost objectivity and consistency. These and other select issues, controversies, and uncertainties possibly encountered in long-term bioassays are covered in this paper. One fact remains abundantly clear: for every known human carcinogen that has been tested adequately in laboratory animals, the findings of carcinogenicity are concordant.

Animals↗
PubMed2006

Stage II colon cancer prognosis prediction by tumor gene expression profiling.

PURPOSE: This study mainly aimed to identify and assess the performance of a microarray-based prognosis predictor (PP) for stage II colon cancer. A previously suggested 23-gene prognosis signature (PS) was also evaluated. PATIENTS AND METHODS: Tumor mRNA samples from 50 patients were profiled using oligonucleotide microarrays. PPs were built and assessed by random divisions of patients into training and validation sets (TSs and VSs, respectively). For each TS/VS split, a 30-gene PP, identified on the TS by selecting the 30 most differentially expressed genes and applying diagonal linear discriminant analysis, was used to predict the prognoses of VS patients. Two schemes were considered: single-split validation, based on a single random split of patients into two groups of equal size (group 1 and group 2), and Monte Carlo cross validation (MCCV), whereby patients were repeatedly and randomly divided into TS and VS of various sizes. RESULTS: The 30-gene PP, identified from group 1 patients, yielded an 80% prognosis prediction accuracy on group 2 patients. MCCV yielded the following average prognosis prediction performance measures: 76.3% accuracy, 85.1% sensitivity, and 67.5% specificity. Improvements in prognosis prediction were observed with increasing TS size. The 30-gene PS were found to be highly-variable across TS/VS splits. Assessed on the same random splits of patients, the previously suggested 23-gene PS yielded a 67.7% mean prognosis prediction accuracy. CONCLUSION: Microarray gene expression profiling is able to predict the prognosis of stage II colon cancer patients. The present study also illustrates the usefulness of resampling techniques for honest performance assessment of microarray-based PPs.

Aged↗