Gene expression correlates of clinical prostate cancer behavior

Prostate tumors are among the most heterogeneous of cancers, both histologically and clinically. Microarray expression analysis was used to determine whether global biological differences underlie common pathological features of prostate cancer and to identify genes that might anticipate the clinical behavior of this disease. While no expression correlates of age, serum prostate specific antigen (PSA), and measures of local invasion were found, a set of genes was identified that strongly correlated with the state of tumor differentiation as measured by Gleason score. Moreover, a model using gene expression data alone accurately predicted patient outcome following prostatectomy. These results support the notion that the clinical behavior of prostate cancer is linked to underlying gene expression differences that are detectable at the time of diagnosis.     

Lymphography in clinically localized prostate cancer

Lymphography demonstrates the size, position, and internal architecture of the external iliac, common iliac, para-aortic, and paracaval lymph nodes. Importantly, the "surgical obturator" nodes are also routinely opacified because they are part of the external iliac chain. Analysis of the internal architecture permits detection of metastases in nodes of normal size, an advantage over cross-sectional imaging techniques. In a prospective study of 89 unselected, previously untreated patients with carcinoma limited to the prostate or periprostatic bed, lymphography was compared with histology of lymph nodes removed at surgical staging. The sensitivity was 53% (17 of 32), specificity 93% (53 of 57), accuracy 79% (70 of 89), and positive and negative predictive values were 81% (17 of 21) and 78% (53 of 68), respectively.     

Brachytherapy for clinically localized prostate cancer

Prostate brachytherapy is an effective treatment option for clinically organ-confined prostate carcinoma. Observed 5- and 10-year follow-up have documented prostate-specific antigen (PSA) levels that were comparable to published radical prostatectomy series and were better than several published external-beam radiation series. Between January 1987 and June 1988, a total of 152 consecutive patients with Stage T1 to T3 low to high Gleason grade prostate cancer were studied at Northwest Hospital in Seattle, Washington. Patients' median age was 70 years (range, 53 to 92 years). All patients received Iodine-125 prostate brachytherapy with or without a 45 Gy dose of external-beam radiation. The average preoperative PSA, clinical stage, and prostate needle biopsy Gleason sum were 11 ng/ml, T2, and (5), respectively, and were known in all but five patients. PSA follow-up, clinical examination, and biopsy results judged disease-free survival at 5 and 10 postoperative years. Elevation of PSA above 0.5 ng/ml or a positive biopsy or a positive bone scan was considered treatment failure. The authors provide an historical review of prostate brachytherapy in conjunction with up-to-date implant techniques and long-term outcome results.     

Gene expression profiling of 30 cancer cell lines predicts resistance towards 11 anticancer drugs at clinically achieved concentrations

Cancer patients with tumors of similar grading, staging and histogenesis can have markedly different treatment responses to different chemotherapy agents. So far, individual markers have failed to correctly predict resistance against anticancer agents. We tested 30 cancer cell lines for sensitivity to 5-fluorouracil, cisplatin, cyclophosphamide, doxorubicin, etoposide, methotrexate, mitomycin C, mitoxantrone, paclitaxel, topotecan and vinblastine at drug concentrations that can be systemically achieved in patients. The resistance index was determined to designate the cell lines as sensitive or resistant, and then, the subset of resistant vs. sensitive cell lines for each drug was compared. Gene expression signatures for all cell lines were obtained by interrogating Affymetrix U133A arrays. Prediction Analysis of Microarrays was applied for feature selection. An individual prediction profile for the resistance against each chemotherapy agent was constructed, containing 42-297 genes. The overall accuracy of the predictions in a leave-one-out cross validation was 86%. A list of the top 67 multidrug resistance candidate genes that were associated with the resistance against at least 4 anticancer agents was identified. Moreover, the differential expressions of 46 selected genes were also measured by quantitative RT-PCR using a TaqMan micro fluidic card system. As a single gene can be correlated with resistance against several agents, associations with resistance were detected all together for 76 genes and resistance phenotypes, respectively. This study focuses on the resistance at the in vivo concentrations, making future clinical cancer response prediction feasible. The TaqMan-validated gene expression patterns provide new gene candidates for multidrug resistance.     

Factors associated with initial therapy for clinically localized prostate cancer: prostate cancer outcomes study.

BACKGROUND: Because of the lack of results from randomized clinical trials comparing the efficacy of aggressive therapies with that of more conservative therapies for clinically localized prostate cancer, men and their physicians may select treatments based on other criteria. We examined the association of sociodemographic and clinical characteristics with four management options: radical prostatectomy, radiation therapy, hormonal therapy, and watchful waiting. METHODS: We studied 3073 participants of the Prostate Cancer Outcomes Study diagnosed from October 1, 1994, through October 31, 1995, with clinically localized disease (T1 or T2). Participants completed a baseline survey, and diagnostic and treatment information was abstracted from medical records. Multiple logistic regression analysis identified factors associated with initial treatment. All statistical tests were two-sided. RESULTS: Patients with clinically localized disease received the following treatments: radical prostatectomy (47.6%), radiation therapy (23.4%), hormonal therapy (10.5%), or watchful waiting (18.5%). Men aged 75 years or older more often received conservative treatment (i.e., hormonal therapy alone or watchful waiting; 57.9% of men aged 75-79 years and 82.1% of men aged 80 years and older) than aggressive treatment (i.e., radical prostatectomy or radiation therapy) (for all age groups, P相似文献   

Nomograms for clinically localized prostate cancer. Part II: radiation therapy

Prostate cancer can be effectively treated with either external beam radiation techniques or with brachytherapy. This study was designed to address the methodology that is used to assess outcome data in the current radiation literature and to evaluate available nomograms that can be used to predict outcomes. A literature search was performed and 12 articles reviewed. Risk stratification was the most frequently used methodology to analyze data. This method encompasses disease-specific variables: the pretreatment prostate-specific antigen (PSA) value and the Gleason score are classified by using cut points into low, intermediate, and high-risk groups. Another methodology uses nomograms to predict outcome. The nomogram uses continuous values of each variable so that the outcome probability for a specific set of parameters is quite specific. The advantage of nomogram analysis over risk stratification analysis is presented. In conclusion, only 3 reports were identified in the radiation literature that used a nomogram to predict outcome. One of the nomograms is proprietary and difficult to interpret. The other 2 nomograms, 1 for 3-dimensional radiation and the other for brachytherapy, have been incorporated into hand-held devices that can be used at consultation with the patient to discuss outcome probabilities to assist in treatment decisions.     

Nomograms for clinically localized prostate cancer. Part I: radical prostatectomy

Many nomograms are currently available for patients' and physicians' use for prediction of pathologic stage based on preoperative parameters, such as prostate-specific antigen (PSA) level, clinical stage (tumor, node, metastasis), and Gleason score from prostate biopsy specimen. Based on the probability of final pathologic stage as well as patient comorbidity and life expectancy, patients and physicians can decide whether definitive local therapy, systemic therapy, or palliative therapy would be most appropriate. Nomograms have also been developed based on preoperative parameters for prediction of biochemical recurrence-free survival outcome following surgery. These nomograms can help patients understand the long-term cancer cure rates after radical prostatectomy.     

MicroRNA expression profiling in prostate cancer

MicroRNAs (miRNA) are small, endogenously expressed noncoding RNAs that negatively regulate expression of protein-coding genes at the translational level. Accumulating evidence, such as aberrant expression of miRNAs, suggests that they are involved in the development of cancer. They have been identified in various tumor types, showing that different sets of miRNAs are usually deregulated in different cancers. To identify the miRNA signature specific for prostate cancer, miRNA expression profiling of 6 prostate cancer cell lines, 9 prostate cancer xenografts samples, 4 benign prostatic hyperplasia (BPH), and 9 prostate carcinoma samples was carried out by using an oligonucleotide array hybridization method. Differential expression of 51 individual miRNAs between benign tumors and carcinoma tumors was detected, 37 of them showing down-regulation and 14 up-regulation in carcinoma samples, thus identifying those miRNAs that could be significant in prostate cancer development and/or growth. There was a significant trend (P=0.029) between the expression of miRNAs and miRNA locus copy number determined by array comparative genomic hybridization, indicating that genetic aberrations may target miRNAs. Hierarchical clustering of the tumor samples by their miRNA expression accurately separated the carcinomas from the BPH samples and also further classified the carcinoma tumors according to their androgen dependence (hormone naive versus hormone refractory), indicating the potential of miRNAs as a novel diagnostic and prognostic tool for prostate cancer.     

Heat shock protein expression independently predicts clinical outcome in prostate cancer

Heat shock proteins (hsps) occupy a central role in the regulation of intracellular homeostasis, and differential expression of individual hsps occurs in a broad range of neoplastic processes. This study was performed to test the hypothesis that the particular patterns by which individual hsps become specifically modulated in human prostate cancers are correlated with behavioral phenotype and hence may be of value in determining the most appropriate clinical management of individual patients. Monoclonal antibodies specific for each hsp protein were used to assess expression of hsp27, hsp60, and hsp70 in formalin-fixed, paraffin wax-embedded, archival tissue specimens of early prostatic adenocarcinomas (pT1-2N0M0) removed at radical prostatectomy (n = 25) and in advanced cancers (n = 95) identified at transurethral resection of prostate (TURP). These findings were compared with similar data from control prostates (n = 10) removed at primary cystectomy for urinary bladder neoplasia not involving the prostate and also at TURP for benign prostatic hyperplasia (n = 50). Western blotting of whole cell lysates derived from established human prostatic epithelial cell lines PNT2, LNCaP, DU145, and PC3 was compared with expression of hsps by the primary human tissues. This study found that early in situ neoplastic transformation of normal prostatic epithelium was consistently associated with loss of hsp27 expression and that the level of hsp27 expression by individual prostate cancers was correlated with their Gleason grade. In advanced cancers, hsp27 expression was invariably associated with poor clinical outcome (P = 0.0001). Data from cell lines supported the primary tissue findings, with elevated hsp27 expression only in aggressive malignant cell lines and androgen-insensitive cell lines. Expression of hsp60 was significantly increased in both early and advanced prostate cancer when compared with nonneoplastic prostatic epithelium (P < 0.0001), as well as in malignant prostate cancer cell lines. Expression of hsp70 was unaltered in early prostate cancers when compared with nonneoplastic prostatic epithelium but showed a diminished expression in morphologically advanced cancers (P = 0.0029). No consistent correlation was found between levels of hsp60 or hsp70 expression and phenotypic behavior of individual primary prostatic cancers. Thus, patterns of hsp expression have been confirmed to be specifically and consistently modulated in both early and advanced human prostate cancers. Whereas absence of hsp27 is a reliable objective marker of early prostatic neoplasia, reexpression of this protein by an individual invasive prostatic carcinoma invariably heralds poor clinical prognosis. Because this protein has been shown to alter the balance between proliferation and apoptosis, understanding the mechanism(s) by which individual hsps regulate intracellular homeostasis may assist in explaining some key processes that occur during evolution of human prostate cancers. We suggest that hsp27 expression provides novel diagnostic and prognostic information on individual patient survival which, if obtained at the time of primary diagnosis, would assist in determining tumor-specific management strategies. Development of techniques to therapeutically modulate hsp27 expression raises the possibility of novel targeted approaches to regulate this homeostatic mechanism, thus allowing better control over tumor cell proliferation and hence patient survival.     

Gene expression profiling of gliomas strongly predicts survival

In current clinical practice, histology-based grading of diffuse infiltrative gliomas is the best predictor of patient survival time. Yet histology provides little insight into the underlying biology of gliomas and is limited in its ability to identify and guide new molecularly targeted therapies. We have performed large-scale gene expression analysis using the Affymetrix HG U133 oligonucleotide arrays on 85 diffuse infiltrating gliomas of all histologic types to assess whether a gene expression-based, histology-independent classifier is predictive of survival and to determine whether gene expression signatures provide insight into the biology of gliomas. We found that gene expression-based grouping of tumors is a more powerful survival predictor than histologic grade or age. The poor prognosis samples could be grouped into three different poor prognosis groups, each with distinct molecular signatures. We further describe a list of 44 genes whose expression patterns reliably classify gliomas into previously unrecognized biological and prognostic groups: these genes are outstanding candidates for use in histology-independent classification of high-grade gliomas. The ability of the large scale and 44 gene set expression signatures to group tumors into strong survival groups was validated with an additional external and independent data set from another institution composed of 50 additional gliomas. This demonstrates that large-scale gene expression analysis and subset analysis of gliomas reveals unrecognized heterogeneity of tumors and is efficient at selecting prognosis-related gene expression differences which are able to be applied across institutions.     

Gene expression profiling: Decoding breast cancer

Gene expression assays that are used in daily clinical practice for treating early breast cancer patients have been introduced in the clinic only recently. This review discusses the development of these arrays, summarizes the validation of those that are commercially available and indicates how the information provided by these assays can help in the care of patients. The review also provides an extensive overview of commercially available assays focusing on MammaPrint, the first and only assay for breast cancer management that has been cleared by the FDA.     

Gene expression profiling in breast cancer

PURPOSE OF REVIEW: Gene expression profiling has highlighted the biologic heterogeneity of breast cancer and has begun to influence the ability of the medical community to individualize patient therapy. The review is intended to highlight the most important advances in the field over recent years with an emphasis on those most relevant to the practicing oncologist. RECENT FINDINGS: Two prognostic profiling assays, the Mammaprint and Oncotype Dx, are in phase III clinical trials designed to evaluate their contribution to therapeutic decision making. Predictive profiles for both chemotherapy and targeted therapy are also in development. In addition, application of genetic profiling techniques to a variety of tumor types is starting to identify those processes, like proliferation, that are integral to carcinogenesis as a whole. SUMMARY: The biologic heterogeneity of breast cancer has become clearer through genome-wide profiling technologies. Validation of the clinical utility of prognostic profiles may enable oncologists to better identify those patients whose prognosis justifies more intensive therapy, while predictive profiles may soon be able to determine which type of chemotherapy a patient should receive. In addition, profiling is starting to identify new therapeutic targets which will point the field of breast cancer oncology in new directions.     

Gene expression profiling in cancer research

Gene expression profiling is increasingly used in cancer research. For each patient, the expression of thousands of genes in the tumour can be measured simultaneously on a microarray. Microarray studies aim at classifying patients based on two types of classification schemes: unsupervised classification, which uses clustering in order to identify homogeneous subtypes of a disease on the basis of gene expression, or supervised classification, which principally aims at the identification of genes or set of genes differentially expressed between tumours with different characteristics (molecular signature), for instance between a group of patients with bad and good prognosis. The data consists of a small number of patients and a large number of variables, raising serious methodological problems. We will use published results on breast cancer in order both to study the power of the experiments and to illustrate the problems in interpretation and validity of their results. We recommend rigorous evaluation of this new technology.