Differential expression of TGFbeta-stimulated clone 22 in normal prostate and prostate cancer

The transforming growth factor-beta (TGFbeta) superfamily and its downstream effector genes are key regulators of epithelial homeostasis. Altered expression of these genes may be associated with malignant transformation of the prostate gland. The cDNA array analysis of differential expression of the TGFbeta superfamily and functionally related genes between patient-matched noncancerous prostate (NP) and prostate cancer (PC) bulk tissue specimens highlighted two genes, namely TGFbeta-stimulated clone-22 (TSC-22) and Id4. Verification of their mRNA expression by real-time PCR in patient-matched NP and PC bulk tissue, in laser-captured pure epithelial and cancer cells and in NP and PC cell lines confirmed TSC-22 underexpression, but not Id4 overexpression, in PC and in human PC cell lines. Immunohistochemical analysis showed that TSC-22 protein expression in NP is restricted to the basal cells and colocalizes with the basal cell marker cytokeratin 5. In contrast, all matched PC samples lack TSC-22 immunoreactivity. Likewise, PC cell lines do not show detectable TSC-22 protein expression as shown by immunoblotting. TSC-22 should be considered as a novel basal cell marker, potentially useful for studying lineage determination within the epithelial compartment of the prostate. Conversely, lack of TSC-22 seems to be a hallmark of malignant transformation of the prostate epithelium. Accordingly, TSC-22 immunohistochemistry may prove to be a diagnostic tool for discriminating benign lesions from malignant ones of the prostate. The suggested tumour suppressor function of TSC-22 warrants further investigation on its role in prostate carcinogenesis and on the TSC-22 pathway as a candidate therapeutic target in PC.

Cellular differentiation determines the expression of the hypoxia-inducible protein NDRG1 in pancreatic cancer

N-myc downstream-regulated gene-1 (NDRG1) is a recently described hypoxia-inducible protein that is upregulated in various human cancers. Pancreatic ductal adenocarcinoma, called pancreatic cancer, is a highly aggressive cancer that is characterised by its avascular structure, which results in a severe hypoxic environment. In this study, we investigated whether NDRG1 is upregulated in these tumours, thus providing a novel marker for malignant cells in the pancreas. By immunohistochemistry, we observed that NDRG1 was highly expressed in well-differentiated cells of pancreatic cancer, whereas the poorly differentiated tumour cells were negative. In addition, hyperplastic islets and ducts of nonquiescent pancreatic tissue were positive. To further explore its selective expression in tumours, two well-established pancreatic cancer cell lines of unequal differentiation status were exposed to 2% oxygen. NDRG1 mRNA and protein were upregulated by hypoxia in the moderately differentiated Capan-1 cells; however, its levels remained unchanged in the poorly differentiated Panc-1 cell line. Taken together, our data suggest that NDRG1 will not serve as a reliable marker of tumour cells in the pancreas, but may serve as a marker of differentiation. Furthermore, we present the novel finding that cellular differentiation may be an important factor that determines the hypoxia-induced regulation of NDRG1.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.

Efficacy and tolerability of capecitabine with weekly paclitaxel for patients with metastatic breast cancer: a phase II report of the SAKK

BACKGROUND: Paclitaxel and capecitabine have proven activity in the treatment of metastatic breast cancer (MBC). Paclitaxel increases the expression of thymidine phosphorylase, the enzyme that activates capecitabine. The purpose of this study was to evaluate the efficacy and tolerability of capecitabine in combination with weekly paclitaxel largely as first-line therapy in patients with MBC. PATIENTS AND METHODS: From April 2002 to September 2004, 19 patients with MBC received oral capecitabine (1,000 mg/m(2) twice daily on days 1-14) plus i.v. paclitaxel (80 mg/m(2) on days 1, 8 and 15) in a 21-day cycle for a maximum of 6 cycles. RESULTS: After a median follow-up of 19.3 months the overall response rate was 63% with 1 complete response (5%) and 11 partial responses (58%). Disease was stabilized in 1 patient (5%) and 3 patients had progressive disease (16%). Three patients were unable to be assessed for response to treatment. Median time to progression was 3.3 months, median time to treatment failure 3.0 months and median overall survival 13.8 months. A substantial number of patients experienced major side effects. The most common treatment-related adverse events were hand-foot syndrome (53%; grade 3: 37%), alopecia (42%; grade 3: 26%), diarrhea (32%; grade 3: 11%) and neurotoxicity (32%; grade 3: 16%). Hematologic toxicities were uncommon. CONCLUSION: The combination of capecitabine and paclitaxel appears to be active in MBC but the safety profile with the dosages used in this trial was unacceptably high and led to a short time to treatment failure. However, based on the efficacy data alternative schedules deserve further evaluation.

Prognostic factors affecting long-term outcomes in patients with resected stage IIIA pN2 non-small-cell lung cancer: 5-year follow-up of a phase II study

The aim was to investigate the efficacy of neoadjuvant docetaxel-cisplatin and identify prognostic factors for outcome in locally advanced stage IIIA (pN2 by mediastinoscopy) non-small-cell lung cancer (NSCLC) patients. In all, 75 patients (from 90 enrolled) underwent tumour resection after three 3-week cycles of docetaxel 85 mg m-2 (day 1) plus cisplatin 40 or 50 mg m-2 (days 1 and 2). Therapy was well tolerated (overall grade 3 toxicity occurred in 48% patients; no grade 4 nonhaematological toxicity was reported), with no observed late toxicities. Median overall survival (OS) and event-free survival (EFS) times were 35 and 15 months, respectively, in the 75 patients who underwent surgery; corresponding figures for all 90 patients enrolled were 28 and 12 months. At 3 years after initiating trial therapy, 27 out of 75 patients (36%) were alive and tumour free. At 5-year follow-up, 60 and 65% of patients had local relapse and distant metastases, respectively. The most common sites of distant metastases were the lung (24%) and brain (17%). Factors associated with OS, EFS and risk of local relapse and distant metastases were complete tumour resection and chemotherapy activity (clinical response, pathologic response, mediastinal downstaging). Neoadjuvant docetaxel-cisplatin was effective and tolerable in stage IIIA pN2 NSCLC, with chemotherapy contributing significantly to outcomes.

Nonparametric Estimation of the Bivariate Recurrence Time Distribution

This paper considers statistical models in which two different types of events, such as the diagnosis of a disease and the remission of the disease, occur alternately over time and are observed subject to right censoring. We propose nonparametric estimators for the joint distribution of bivariate recurrence times and the marginal distribution of the first recurrence time. In general, the marginal distribution of the second recurrence time cannot be estimated due to an identifiability problem, but a conditional distribution of the second recurrence time can be estimated non-parametrically. In literature, statistical methods have been developed to estimate the joint distribution of bivariate recurrence times based on data of the first pair of censored bivariate recurrence times. These methods are efficient in the current model because recurrence times of higher orders are not used. Asymptotic properties of the estimators are established. Numerical studies demonstrate the estimator performs well with practical sample sizes. We apply the proposed method to a Denmark psychiatric case register data set for illustration of the methods and theory.

An open-label, noncomparative phase II trial to evaluate the efficacy and safety of docetaxel in combination with gefitinib in patients with hormone-refractory metastatic prostate cancer

BACKGROUND: Prostate cancer is the most common type of cancer in men, however, therapeutic options are limited. 50-90% of hormone-refractory prostate cancer cells show an overexpression of epidermal growth factor receptor (EGFR), which may contribute to uncontrolled proliferation and resistance to chemotherapy. In vitro, gefitinib, an orally administered tyrosine kinase inhibitor, has shown a significant increase in antitumor activity when combined with chemotherapy. PATIENTS AND METHODS: In this phase II study, the safety and efficacy of gefitinib in combination with docetaxel, a chemotherapeutic agent commonly used for prostate cancer, was investigated in patients with hormone-refractory prostate cancer (HRPC). 37 patients with HRPC were treated continuously with gefitinib 250 mg once daily and docetaxel 35 mg/m2 i.v. for up to 6 cycles. PSA response, defined as a =50% decrease in serum PSA compared with trial entry, was the primary efficacy parameter. PSA levels were measured at prescribed intervals. RESULTS: The response rate and duration of response were consistent with those seen with docetaxel monotherapy. The combination of docetaxel and gefitinib was reasonably well tolerated in this study. CONCLUSION: Future studies should investigate whether patients with specific tumor characteristics, e.g. EGFR protein overexpression, respond better to gefitinib than patients without, leading to a more customized therapy option.

Incidence of childhood cancer in Switzerland: the Swiss Childhood Cancer Registry

BACKGROUND: This report describes the incidence of childhood cancer in Switzerland, based on the data from the Swiss Childhood Cancer Registry (SCCR), a national hospital-based cancer registry with very high coverage, founded in 1976 by the Swiss Paediatric Oncology Group (SPOG). PROCEDURE: Malignancies were coded according to the International Classification of Childhood Cancer (ICCC-3). Incidence rates per 100,000 person-years were calculated for all malignancies and groups of malignancies in Swiss residents less than 15 years of age for the decade 1995-2004. RESULTS: The SCCR annually registered on average 174 new cases of cancer in Swiss residents aged <15 years, with a median age at diagnosis of 5.6 years. The crude incidence of childhood cancer in children aged <15 years was 13.5, higher for boys (15.0 per 100,000) than for girls (12.1 per 100,000), and was nearly twice as high in the first 5 years of life (19.3 per 100,000) than in the age group 5 to 14 years (10.8 per 100,000). CONCLUSION: Incidence of childhood cancers in the SCCR was similar to neighbouring countries and to data published by regional cancer registries in Switzerland for the same period, suggesting good completeness of registration. This makes the SCCR a valuable resource for national and international research on childhood cancer.

Quality of life and quality-adjusted survival (Q-TWiST) in patients receiving dose-intensive or standard dose chemotherapy for high-risk primary breast cancer

Quality of life (QL) is an important consideration when comparing adjuvant therapies for early breast cancer, especially if they differ substantially in toxicity. We evaluated QL and Q-TWiST among patients randomised to adjuvant dose-intensive epirubicin and cyclophosphamide administered with filgrastim and progenitor cell support (DI-EC) or standard-dose anthracycline-based chemotherapy (SD-CT). We estimated the duration of chemotherapy toxicity (TOX), time without disease symptoms and toxicity (TWiST), and time following relapse (REL). Patients scored QL indicators. Mean durations for the three transition times were weighted with patient reported utilities to obtain mean Q-TWiST. Patients receiving DI-EC reported worse QL during TOX, especially treatment burden (month 3: P<0.01), but a faster recovery 3 months following chemotherapy than patients receiving SD-CT, for example, less coping effort (P<0.01). Average Q-TWiST was 1.8 months longer for patients receiving DI-EC (95% CI, -2.5 to 6.1). Q-TWiST favoured DI-EC for most values of utilities attached to TOX and REL. Despite greater initial toxicity, quality-adjusted survival was similar or better with dose-intensive treatment as compared to standard treatment. Thus, QL considerations should not be prohibitive if future intensive therapies show superior efficacy.

Toward an early diagnosis of lung cancer: an autoantibody signature for squamous cell lung carcinoma

Serum-based diagnosis offers the prospect of early lung carcinoma detection and of differentiation between benign and malignant nodules identified by CT. One major challenge toward a future blood-based diagnostic consists in showing that seroreactivity patterns allow for discriminating lung cancer patients not only from normal controls but also from patients with non-tumor lung pathologies. We addressed this question for squamous cell lung cancer, one of the most common lung tumor types. Using a panel of 82 phage-peptide clones, which express potential autoantigens, we performed serological spot assay. We screened 108 sera, including 39 sera from squamous cell lung cancer patients, 29 sera from patients with other non-tumor lung pathologies, and 40 sera from volunteers without known disease. To classify the serum groups, we employed the standard Naïve Bayesian method combined with a subset selection approach. We were able to separate squamous cell lung carcinoma and normal sera with an accuracy of 93%. Low-grade squamous cell lung carcinoma were separated from normal sera with an accuracy of 92.9%. We were able to distinguish squamous cell lung carcinoma from non-tumor lung pathologies with an accuracy of 83%. Three phage-peptide clones with sequence homology to ROCK1, PRKCB1 and KIAA0376 reacted with more than 15% of the cancer sera, but neither with normal nor with non-tumor lung pathology sera. Our study demonstrates that seroreactivity profiles combined with statistical classification methods have great potential for discriminating patients with squamous cell lung carcinoma not only from normal controls but also from patients with non-tumor lung pathologies.

Alternative splicing of pre-mRNA in cancer: focus on G protein-coupled peptide hormone receptors

Through alternative splicing, multiple different transcripts can be generated from a single gene. Alternative splicing represents an important molecular mechanism of gene regulation in physiological processes such as developmental programming as well as in disease. In cancer, splicing is significantly altered. Tumors express a different collection of alternative spliceoforms than normal tissues. Many tumor-associated splice variants arise from genes with an established role in carcinogenesis or tumor progression, and their functions can be oncogenic. This raises the possibility that products of alternative splicing play a pathogenic role in cancer. Moreover, cancer-associated spliceoforms represent potential diagnostic biomarkers and therapeutic targets. G protein-coupled peptide hormone receptors provide a good illustration of alternative splicing in cancer. The wild-type forms of these receptors have long been known to be expressed in cancer and to modulate tumor cell functions. They are also recognized as attractive clinical targets. Recently, splice variants of these receptors have been increasingly identified in various types of cancer. In particular, alternative cholecystokinin type 2, secretin, and growth hormone-releasing hormone receptor spliceoforms are expressed in tumors. Peptide hormone receptor splice variants can fundamentally differ from their wild-type receptor counterparts in pharmacological and functional characteristics, in their distribution in normal and malignant tissues, and in their potential use for clinical applications.

Acetaldehyde as an underestimated risk factor for cancer development: role of genetics in ethanol metabolism

Chronic ethanol consumption is a strong risk factor for the development of certain types of cancer including those of the upper aerodigestive tract, the liver, the large intestine and the female breast. Multiple mechanisms are involved in alcohol-mediated carcinogenesis. Among those the action of acetaldehyde (AA), the first metabolite of ethanol oxidation is of particular interest. AA is toxic, mutagenic and carcinogenic in animal experiments. AA binds to DNA and forms carcinogenic adducts. Direct evidence of the role of AA in alcohol-associated carcinogenesis derived from genetic linkage studies in alcoholics. Polymorphisms or mutations of genes coding for AA generation or detoxifying enzymes resulting in elevated AA concentrations are associated with increased cancer risk. Approximately 40% of Japanese, Koreans or Chinese carry the AA dehydrogenase 2*2 (ALDH2*2) allele in its heterozygous form. This allele codes for an ALDH2 enzyme with little activity leading to high AA concentrations after the consumption of even small amounts of alcohol. When individuals with this allele consume ethanol chronically, a significant increased risk for upper alimentary tract and colorectal cancer is noted. In Caucasians, alcohol dehydrogenase 1C*1 (ADH1C*1) allele encodes for an ADH isoenzyme which produces 2.5 times more AA than the corresponding allele ADH1C*2. In studies with moderate to high alcohol intake, ADH1C*1 allele frequency and rate of homozygosity was found to be significantly associated with an increased risk for cancer of the upper aerodigestive tract, the liver, the colon and the female breast. These studies underline the important role of acetaldehyde in ethanol-mediated carcinogenesis.

Novel functional profiling approach combining reverse phase protein microarrays and human 3-D ex vivo tissue cultures: expression of apoptosis-related proteins in human colon cancer

Cancer is caused by a complex pattern of molecular perturbations. To understand the biology of cancer, it is thus important to look at the activation state of key proteins and signaling networks. The limited amount of available sample material from patients and the complexity of protein expression patterns make the use of traditional protein analysis methods particularly difficult. In addition, the only approach that is currently available for performing functional studies is the use of serial biopsies, which is limited by ethical constraints and patient acceptance. The goal of this work was to establish a 3-D ex vivo culture technique in combination with reverse-phase protein microarrays (RPPM) as a novel experimental tool for use in cancer research. The RPPM platform allows the parallel profiling of large numbers of protein analytes to determine their relative abundance and activation level. Cancer tissue and the respective corresponding normal tissue controls from patients with colorectal cancer were cultured ex vivo. At various time points, the cultured samples were processed into lysates and analyzed on RPPM to assess the expression of carcinoembryonic antigen (CEA) and 24 proteins involved in the regulation of apoptosis. The methodology displayed good robustness and low system noise. As a proof of concept, CEA expression was significantly higher in tumor compared with normal tissue (p<0.0001). The caspase 9 expression signal was lower in tumor tissue than in normal tissue (p<0.001). Cleaved Caspase 8 (p=0.014), Bad (p=0.007), Bim (p=0.007), p73 (p=0.005), PARP (p<0.001), and cleaved PARP (p=0.007) were differentially expressed in normal liver and normal colon tissue. We demonstrate here the feasibility of using RPPM technology with 3-D ex vivo cultured samples. This approach is useful for investigating complex patterns of protein expression and modification over time. It should allow functional proteomics in patient samples with various applications such as pharmacodynamic analyses in drug development.