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At least 343 records · Page 19Linked to original sources
PubMed2006

Surgical pathology stage by American Joint Commission on Cancer criteria predicts patient survival after preoperative chemoradiation for localized gastric carcinoma.

BACKGROUND: Preoperative chemoradiation for localized gastric cancer can modify baseline stage, as determined by surgical pathology stage. Therefore, the authors hypothesized that surgical pathology stage would be a better prognosticator of overall survival (OS) than baseline stage. METHODS: Patient populations were combined from 2 prospectively conducted, preoperative chemoradiation trials that used the same therapeutic strategy. Patients must have had localized gastric adenocarcinoma and were staged extensively, including endoscopic ultrasonography and laparoscopy. Patients had to be fit for surgery medically with a technically resectable cancer. All patients provided written informed consent. Patients first received induction chemotherapy for up to 2 months followed by chemoradiation (45 grays) and an attempted surgery. OS was correlated with pretreatment and posttreatment parameters, including surgical pathology stage according to American Joint Commission on Cancer criteria. RESULTS: Of 74 patients who were registered, 69 patients (93%) had undergone surgery. Nineteen patients (26%) had a pathologic complete response (pathCR), and 55 patients (81%) had a curative (R0) resection. None of the pretreatment parameters correlated with OS; however, longer OS correlated with lower pathologic stage (P < .0001), R0 resection (P < .001), clinical response noted prior to surgery (P = .002), pathCR (P = .004), lower pathologic lymph node classification (P = .006), and lower pathologic tumor classification (P = .03). Pathologic stage and R0 resection were independent prognostic factors for OS (multivariate Cox model; both P = .05). CONCLUSIONS: When preoperative chemoradiation strategy was employed for gastric cancer, the surgical pathology stage, a reflection of cancer's biologic heterogeneity, was a better prognosticator of OS than the baseline clinical stage. Surgical pathology stage, in this setting, may serve as an intermediate endpoint for Phase II/III trials.

Adult↗
PubMed1998

Expression of metastasis-related genes in surgical specimens of human gastric cancer can predict disease recurrence.

It was determined whether the expression level of several genes that regulate different steps of metastasis in formalin-fixed paraffin-embedded archival specimens of human gastric cancers correlated with disease recurrence and metastasis. The steady-state mRNA expression level for epidermal growth factor receptor (EGF-R), basic fibroblast growth factor (bFGF), E-cadherin, type IV collagenase and multidrug resistance (MDR-1) were examined by a colorimetric in situ hybridisation (ISH) technique, concentrating on reactivity at the periphery of the lesions. All patients were operated on for cure. 15 cases were disease-free and 10 had disease recurrence by 4.5 years after resection of the primary tumours. The expression of EGF-R and bFGF type IV collagenase was higher and expression of E-cadherin was lower in the disease-recurrence cases than in the disease-free cases. The ratio between the expression level of collagenase type IV and E-cadherin at the periphery of the surgical specimens differed significantly between the disease-free cases and the recurrent-metastatic cases. These data show that multiparametric ISH analysis for several metastasis-related genes may allow prediction of disease recurrence of gastric cancer.

Cadherins↗
PubMedDate not supplied

Progesterone binding cyst protein in hormone receptor positive breast cancer; a predictive factor for effect of adjuvant tamoxifen treatment.

Progesterone binding cyst protein (PBCP) was measured in breast cancer cytosols from 128 pre- and post-menopausal women with operable node positive (pN+) breast cancer Stage II. All patients were included in a national multicenter study on the effect of adjuvant tamoxifen treatment in hormone sensitive breast cancer, i.e. estrogen receptor content of at least 10 pmol/g cytosol protein. Patients were randomised to receive adjuvant tamoxifen 20 mg once daily for two years or no endocrine treatment. At a median follow-up of 60 months, we found PBCP content in the primary tumor to be an important factor with regard to the effect of adjuvant tamoxifen treatment. The benefit of adjuvant tamoxifen treatment on relapse-free survival and overall survival was confined to the subpopulation of patients with PBCP negative tumors. PBCP should be further evaluated as a predictive factor for the effect of tamoxifen treatment.

Adult↗
PubMed2003

Measurements using the alkaline comet assay predict bladder cancer cell radiosensitivity.

In the UK, the two main treatments of invasive bladder cancer are radiotherapy or cystectomy. However, approximately 50% of patients undergoing radiotherapy fail to respond. If tumour radiosensitivity could be predicted in advance, it may be possible to improve control rates significantly by selecting for radiotherapy those patients whose tumours are radiosensitive. Additionally, patients who would benefit from surgery would be identified earlier. The alkaline comet assay (ACA) is a sensitive method for the detection of DNA strand break damage in cells. In the present study, using six bladder cancer cell lines of differing radiosensitivities, cell survival was compared to the manifestation of radiogenic DNA damage as assessed by ACA. For all the cell lines, the extent of comet formation strongly correlates with cell killing (R2>0.96), with a greater response being noted in radiosensitive cells. In repair studies, measures of residual damage correlate with survival fraction at 2 Gy (R2>0.96), but for only five of the cell lines. Finally, cells from human bladder tumour biopsies reveal a wide range of predicted radiosensitivies as determined by ACA. Overall, these studies demonstrate ACA to be a good predictive measure of bladder cancer cell radiosensitivity at low dose, with potential clinical application.

Carcinoma, Transitional Cell↗
PubMed2006

MR-determined metabolic phenotype of breast cancer in prediction of lymphatic spread, grade, and hormone status.

The purpose of the study was to evaluate the use of metabolic phenotype, described by high-resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS), as a tool for prediction of histological grade, hormone status, and axillary lymphatic spread in breast cancer patients. Biopsies from breast cancer (n = 91) and adjacent non-involved tissue (n = 48) were excised from patients (n = 77) during surgery. HR MAS MR spectra of intact samples were acquired. Multivariate models relating spectral data to histological grade, lymphatic spread, and hormone status were designed. The multivariate methods applied were variable reduction by principal component analysis (PCA) or partial least-squares regression-uninformative variable elimination (PLS-UVE), and modelling by PLS, probabilistic neural network (PNN), or cascade correlation neural network. In the end, model verification by prediction of blind samples (n = 12) was performed. Validation of PNN training resulted in sensitivity and specificity ranging from 83 to 100% for all predictions. Verification of models by blind sample testing showed that hormone status was well predicted by both PNN and PLS (11 of 12 correct), lymphatic spread was best predicted by PLS (8 of 12), whereas PLS-UVE PNN was the best approach for predicting grade (9 of 12 correct). MR-determined metabolic phenotype may have a future role as a supplement for clinical decision-making-concerning adjuvant treatment and the adaptation to more individualised treatment protocols.

Adult↗
PubMed2003

Evaluation of bone marrow in breast cancer patients: prediction of clinical outcome and response to therapy.

Blood-borne distant metastasis is the leading cause of cancer-related death in breast cancer. The onset of this fundamental process can now be assessed in cancer patients by using ultrasensitive immunocytochemical and molecular assays able to detect even single metastatic cells. To date, clinical studies with large study populations, validated immunoassays, and adequate follow-up time provide evidence for the independent prognostic value of the presence of disseminated tumor cells in the bone marrow. At present, bone marrow evaluation may therefore be considered a diagnostic tool for improved risk assessment with regard to distant relapse and death, especially among potentially curable breast cancer patients. Except for promising pilot studies, no data are available to support the immediate use of bone marrow evaluation for treatment monitoring in order to enable the prediction of response to adjuvant therapy.

Bone Marrow↗
PubMed2006

Risk of colon cancer in hereditary non-polyposis colorectal cancer patients as predicted by fuzzy modeling: Influence of smoking.

AIM: To investigate whether a fuzzy logic model could predict colorectal cancer (CRC) risk engendered by smoking in hereditary non-polyposis colorectal cancer (HNPCC) patients. METHODS: Three hundred and forty HNPCC mismatch repair (MMR) mutation carriers from the Creighton University Hereditary Cancer Institute Registry were selected for modeling. Age-dependent curves were generated to elucidate the joint effects between gene mutation (hMLH1 or hMSH2), gender, and smoking status on the probability of developing CRC. RESULTS: Smoking significantly increased CRC risk in male hMSH2 mutation carriers (P < 0.05). hMLH1 mutations augmented CRC risk relative to hMSH2 mutation carriers for males (P < 0.05). Males had a significantly higher risk of CRC than females for hMLH1 non smokers (P < 0.05), hMLH1 smokers (P < 0.1) and hMSH2 smokers (P < 0.1). Smoking promoted CRC in a dose-dependent manner in hMSH2 in males (P < 0.05). Females with hMSH2 mutations and both sexes with the hMLH1 groups only demonstrated a smoking effect after an extensive smoking history (P < 0.05). CONCLUSION: CRC promotion by smoking in HNPCC patients is dependent on gene mutation, gender and age. These data demonstrate that fuzzy modeling may enable formulation of clinical risk scores, thereby allowing individualization of CRC prevention strategies.

Adaptor Proteins, Signal Transducing↗
PubMed2004

Coping responses following breast cancer diagnosis predict psychological adjustment three years later.

The relationship between coping responses and psychological adjustment to a breast cancer diagnosis is well documented for time periods close to diagnosis. The purpose of the present study was to assess the long term association between these two variables. Fifty-five women completed measures of coping response, decisional control, frustration expression, and psychological adjustment within six months of receiving their breast cancer diagnosis. These women were contacted three years later and their psychological adjustment-as measured by the profile of mood states (POMS)-was reassessed. Univariate and multivariate analyses were performed. The results showed that women who were depressed at time of treatment planning, and who responded to their cancer diagnosis with cognitive avoidance, i.e. acceptance/resignation, had significantly worse psychological adjustment three years later. Poor adjustment was significantly associated with cognitive avoidance and minimal use of approach-based coping responses. The findings suggest that women who respond to their breast cancer diagnosis with passive acceptance and resignation are at significant risk for poor long term psychological adjustment. Psychological interventions for these women should address cognitive avoidance, with the aim of fostering approach-based coping and positive well-being.

Adaptation, Psychological↗
PubMed2005

APE1 and XRCC1 protein expression levels predict cancer-specific survival following radical radiotherapy in bladder cancer.

INTRODUCTION: Radiotherapy offers the potential of bladder preservation in muscle-invasive bladder cancer, but only a proportion of tumors respond, and there are no accurate predictive methods. The ability of tumor cells to repair DNA damage induced by ionizing radiation influences radiosensitivity. We therefore investigated the prognostic value of the DNA repair proteins APE1 and XRCC1 in patients with muscle-invasive bladder cancer treated by radical radiotherapy. MATERIALS AND METHODS: The tumors of 90 patients with muscle-invasive transitional cell carcinoma and known clinical outcomes were immunostained with APE1 and XRCC1 antibodies. Levels of protein expression were assessed as a percentage of tumor cells with positive nuclear staining (1,000 cells per tumor). RESULTS: The median percentage of nuclear staining for APE1 was 98.7% (range, 42.2-100%) and for XRCC1 was 96.5% (range, 0.6-99.6%). High expression levels of APE1 or XRCC1 (> or = 95% positivity) were associated with improved patient cancer-specific survival (log-rank, P = 0.02 and 0.006, respectively). In a multivariate Cox regression model, APE1 and XRCC1 expression and hydronephrosis were the only independent predictors of patient survival. CONCLUSIONS: Expression levels of both APE1 and XRCC1 proteins were strongly associated with patient outcome following radiotherapy, separating patients with good outcome from the 50% with poor outcome (82% and 44%, 3-year cause-specific survival, respectively). If prospectively validated, this simple test could be incorporated into clinical practice to select patients likely to respond to radiotherapy and consider alternative forms of therapy for those unlikely to respond.

Adult↗
PubMed1992

Approaches to the prediction of human cancer risk.

Epidemiological studies provide the only direct means of measuring the risk of cancer in humans and for investigating effects directly avoiding interspecies extrapolation. Epidemiology is, however, too insensitive to detect small increases in risk. Furthermore, traditional epidemiology cannot be used prospectively to indicate future problems nor to explore the current exposure situation. Ideally, cancer hazards should be identified before humans are exposed. For the foreseeable future, therefore, identification of carcinogens will necessarily depend heavily on data derived from studies in experimental animals. Emerging molecular biological techniques, if used critically, hold great promise for resolving many contemporary puzzles in cancer risk prediction.

Animals↗
PubMed2006

Mechanisms of egfr gene transcription modulation: relationship to cancer risk and therapy response.

The epidermal growth factor receptor (EGFR) plays a crucial role in growth, differentiation, and motility of normal as well as cancer cells. For predictive cancer diagnostics and therapeutic targeting of EGFR, it is important to know how the expression level of EGFR is controlled and related to receptor signaling. A novel transcriptional regulation mechanism has been described that depends on the length of a CA repeat in intron 1 [CA simple sequence repeat 1 (CA SSR I)] of the EGFR gene. Thereby, the number of CA repeats is inversely correlated to pre-mRNA synthesis. Indirect evidence for the importance of this mechanism includes the preferential occurrence of amplifications in cancer tissue harboring short CA repeats in this sequence and the discovery of distinct alleles in young breast cancer patients with a family history of the disease and in Japanese breast cancer patients. It can be postulated that the length of the CA repeat influences DNA bendability and, in consequence, the binding of repressor proteins. In summary, it seems that the CA SSR I represents an inherited variable for response to anti-EGFR therapies that could be determined before therapy. Moreover, the potential for synergistic effects with other polymorphism [e.g., EGFR R497K (HER-1 497K) and CCND1 A870G] leading to a simultaneous increase of EGFR signaling activity and expression should be investigated. From a practical perspective, assessment of the CA SSR I number of CA dinucleotide repeats as a predictor for clinical outcome is very attractive because it is a constant feature that does not change over time and can be easily measured in normal and cancer tissues (blood cells, skin, and tumor biopsies) in an assay that is technically simple, objective, and even quantitative.

Breast Neoplasms↗
PubMed1999

Naive Bayesian-based nomogram for prediction of prostate cancer recurrence.

This paper introduces a schema with naive-Bayesian classifier and patient weighting technique to develop a prostate cancer recurrence prediction model from patient data. We propose the graphical presentation of naive-Bayesian classifier with a nomogram, which can be used both for prediction or can provide means to data analysis. The resulting model was experimentally evaluated; the results were favorable both in terms of interpretability and predictive accuracy.

Bayes Theorem↗
PubMed1998

[Reflections on screening tests for lung cancer].

Screening for lung cancer is a controversial issue. Much needs to be done in the area of primary prevention of lung cancer. Predictions of lung cancer mortality in Europe indicate further increases in the coming 20 years, due to the extensive number of individuals having long periods of exposure to carcinogens. The treatment of lung cancer is not solved, either, and the global epidemiological situation of lung cancer raises great concerns. Due to these reasons, it seems to be necessary to revise the issue of lung cancer screening. In Hungary, annual minimal mass roentgen screening has been done for decades. The data of more than 4.3 million individuals were analysed in 1996. Out of the symptomless patients detected, 21.4% fell into oncological stage 1, 33.7% into stage 2 and 29% into stage 3. Those patients who were not screened, but who presented with symptoms and were detected as such, can be classified into stages as follows: Stage 1: 8.7%, stage 2: 21.5% and stage 3: 36.3%. The resection rate in the screened group versus non-screened group was 34.3% and 13.7% respectively. Minimal mass roentgen screening allows the detection of lung cancer patients in an earlier stage; with improved treatment possibilities, survival rates and patients' quality of life will shift to a positive direction. It is suggested that the effectiveness of minimal mass roentgen screening of lung cancer should be revised.

Female↗
PubMed2003

Towards integrated clinico-genomic models for personalized medicine: combining gene expression signatures and clinical factors in breast cancer outcomes prediction.

Genomic data, particularly genome-scale measures of gene expression derived from DNA microarray studies, has the potential for adding enormous information to the analysis of biological phenotypes. Perhaps the most successful application of this data has been in the characterization of human cancers, including the ability to predict clinical outcomes. Nevertheless, most analyses have used gene expression profiles to define broad group distinctions, similar to the use of traditional clinical risk factors. As a result, there remains considerable heterogeneity within the broadly defined groups and thus predictions fall short of providing accurate predictions for individual patients. One strategy to resolve this heterogeneity is to make use of multiple gene expression patterns that are more powerful in defining individual characteristics and predicting outcomes than any single gene expression pattern. Statistical tree-based classification systems provide a framework for assessing multiple patterns, that we term metagenes, selecting those that are most capable of resolving the biological heterogeneity. Moreover, this framework provides a mechanism to combine multiple forms of data, both genomic and clinical, to most effectively characterize individual patients and achieve the goal of personalized predictions of clinical outcomes.

Breast Neoplasms↗
PubMed1998

Image analysis of androgen receptor immunostaining in prostate cancer accurately predicts response to hormonal therapy.

PURPOSE: Immunostaining for androgen receptor in prostate tumor specimens has revealed that the majority of primary and advanced stage cancers are positive for this regulatory transcription factor. Consequently, its use as a marker for tumor behavior and therapeutic response has been discounted. However, past reports have noted significant heterogeneity of androgen receptor immunostaining between prostate tumor cells in contrast to staining homogeneity in normal epithelium, which indicates that variability in androgen receptor content may exist within certain tumor specimens. To analyze this phenomenon more thoroughly and to determine whether this variability possesses clinical correlates, androgen receptor immunostaining profiles within androgen receptor positive prostate tumor specimens were categorized using an image analysis based system. MATERIALS AND METHODS: Tumor specimens were obtained before hormone therapy from 44 patients with advanced stage prostate cancer and 4 with early stage disease who later had progression. Response to antiandrogen therapy and survival was monitored. Paraffin embedded tumor sections were processed for immunocytochemistry and stained for androgen receptor. A Quantimet image analysis system was used to analyze nuclear immunostaining for androgen receptor and Receptogram patterns were established for each specimen based on univariate distributions of nuclear receptor content and concentration. RESULTS: Data revealed that 17 of 18 responders to hormone therapy possessed type 1 (15) or type 3 (2) Receptograms, which are characterized by a unimodal peak or multimodal peaks within a narrow concentration range. Of the 17 cases that stabilized following therapy 16 had type 3 Receptograms and 1 was characterized as type 1. In contrast, all 13 patients in whom endocrine treatment failed had either type 2 or 4 Receptograms, which are characterized by a highly skewed or bimodal androgen receptor distribution. Positive and negative predictive values for this assay were 100 and 93%, respectively. In addition, the type 1/3 Receptogram patterns were correlated with longer mean survival. CONCLUSIONS: Image analysis of prostate cancer androgen receptor immunostaining with a pattern oriented approach for response is capable of accurately predicting response to hormone therapy in patients with advanced stage disease. Application of this analytic scheme may assist the clinician with therapeutic management of advanced prostate cancer.

Adenocarcinoma↗
PubMed1998

Applications of neural networks in urologic oncology.

Artificial neural networks are computer-based statistical models that can be used to imitate biologic neural processes. They have been applied to a variety of problems in medicine, including diagnosis and outcomes predictions. In the area of urologic oncology, these neural networks have been used to assist in the diagnosis of prostate cancer, predicting response to therapy and recurrence in prostate cancer, predicting the presence of renal cell carcinoma in cystic renal lesions, and predicting the presence of occult metastatic disease in nonseminomatous testicular germ cell tumors. This article reviews the basic concepts of artificial neural networks and summarizes their application in urologic oncology. Neural network technology remains in its infancy in urologic oncology, and many more retrospective and prospective studies are needed to determine its clinical utility.

Computer Simulation↗
PubMed1995

Predicting endometrial cancer among older women who present with abnormal vaginal bleeding.

We studied 203 women ages 49 or over who presented with abnormal vaginal bleeding and who underwent either endometrial biopsy or dilation and curettage at the Brigham and Women's Hospital. Using information from the clinical history, we predicted their risk for endometrial cancer (36 patients) or complex endometrial hyperplasia (16 patients). Factors independently associated with endometrial cancer/complex hyperplasia included age 70 or older (OR = 9.1, P = 0.0001), diabetes (OR = 3.7, P = 0.02), and nulliparity (OR = 2.7, P = 0.02). After adjusting for age, menopause was borderline significant (OR = 2.6, P = 0.07). Our data estimated a risk of endometrial cancer/complex hyperplasia of 87% for a woman possessing all of these factors, and a risk of less than 3% if she had none of them. Our model provides an inexpensive, simple means for assessing the risk of endometrial cancer and complex hyperplasia in the post- or perimenopausal woman with abnormal bleeding.

Age Factors↗
PubMed1999

Increased chromosome-type chromosome aberration frequencies as biomarkers of cancer risk in a blackfoot endemic area.

To examine whether biomarkers such as sister chromatid exchanges (SCEs) and chromosome aberrations (CAs) can predict cancer development, a nested case-control study was performed in a blackfoot endemic area with a known high cancer risk. A cohort of 686 residents was recruited from three villages in the blackfoot endemic area. Personal characteristics were collected, and venous blood was drawn for lymphocyte culture and stored in a refrigerator. The vital status and cancer development were followed using the National Death Registry, Cancer Registry, and Blackfoot Disease Registry. The follow-up period was from August 1991 to July 1995. During this 4-year period, 31 residents developed various types of cancer. Blood culture samples from nine of these subjects were unsuitable for experiments due to improper storage. Finally, a total of 22 cancer cases had cytogenetic samples that could be analyzed. Twenty-two control subjects were selected from those who did not develop cancer in the study period, and these subjects were matched to cases by sex, age, smoking habits, and residential area. The results showed that there was no significant difference in the frequencies of SCE and chromatid-type CAs between the case and control groups. However, the frequencies of chromosome-type CAs, e.g., chromosome-type gaps, chromosome-type breaks, chromosome-type breaks plus exchanges, total chromosome-type aberrations, and total frequencies of CAs in the case group, were significantly higher than those in the control group (P < 0.05). The odds ratio of cancer risk in subjects with more than zero chromosome-type breaks was 5.0 (95% confidence interval = 1.09-22.82) compared to those with zero chromosomal breaks. The odds ratios for more than zero chromosome-type breaks plus exchanges and a frequency of total chromosome-type aberrations of >1.007% were 11.0 and 12.0, respectively (P < 0.05). Subjects with a total CA frequency of >4.023% had a 9-fold increase for cancer risk. These results indicate that chromosome-type CAs are good biomarkers for the prediction of cancer development, whereas SCEs and chromatid-type CAs cannot predict cancer risk.

Adult↗