Cytotoxic effects of butanolic extract from Pfaffia paniculata (Brazilian Ginseng) on cultured human breast cancer cell line MCF-7

Roots of Pfaffia paniculata have been well documented for multifarious therapeutic values and have also been used for cancer therapy in folk medicine. This study has been performed in a human breast tumor cell line, the MCF-7 cells. These are the most commonly used model of estrogen-positive breast cancer, and it has been originally established in 1973 at the Michigan Cancer Foundation from a pleural effusion taken from a woman with metastatic breast cancer. Butanolic extract of the roots of P. paniculata showed cytotoxic effect MCF-7 cell line. as determined with crystal violet assay, cellular death with acridine orange/ethidium bromide staining, and cell proliferation with immunocytochemistry of bromodeoxyuridine (BrdU). Subcellular alterations were evaluated by electron microscopy. Cells treated With butanolic extract showed degeneration of cytoplasmic components and profound morphological and nuclear alterations. The results show that this butanolic extract indeed presents cytotoxic substances, and its fractions merit further investigations. (C) 2008 Elsevier GmbH. All rights reserved.

An orthotopic xenograft model of human nonseminomatous germ cell tumour

We have established the first example of an orthotopic xenograft model of human nonseminomatous germ cell tumour (NSGCT). This reproducible model exhibits many clinically relevant features including metastases to the retroperitoneal lymph nodes and lungs, making it an ideal tool for research into the development and progression of testicular germ cell tumours.

Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Longitudinal analysis of tumor marker CEA of breast cancer patients from Braga's hospital

Allied to an epidemiological study of population of the Senology Unit of Braga’s Hospital that have been diagnosed with malignant breast cancer, we describe the progression in time of repeated measurements of tumor marker Carcinoembryonic antigen (CEA). Our main purpose is to describe the progression of this tumor marker as a function of possible risk factors and, hence, to understand how these risk factors influences that progression. The response variable, values of CEA, was analyzed making use of longitudinal models, testing for different correlation structures. The same covariates used in a previous survival analysis were considered in the longitudinal model. The reference time used was time from diagnose until death from breast cancer. For diagnostic of the models fitted we have used empirical and theoretical variograms. To evaluate the fixed term of the longitudinal model we have tested for a changing point on the effect of time on the tumor marker progression. A longitudinal model was also fitted only to the subset of patients that died from breast cancer, using the reference time as time from date of death until blood test.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

Joint modelling of longitudinal and survival data on breast cancer

Tese de Doutoramento em Ciências (Especialidade em Matemática)

Longitudinal analysis of tumor marker CEA of breast cancer patients from Braga's hospital

Allied to an epidemiological study of population of the Senology Unit of Braga’s Hospital that have been diagnosed with malignant breast cancer, we describe the progression in time of repeated measurements of tumor marker Carcinoembryonic antigen (CEA). Our main purpose is to describe the progression of this tumor marker as a function of possible risk factors and, hence, to understand how these risk factors influences that progression. The response variable, values of CEA, was analyzed making use of longitudinal models, testing for different correlation structures. The same covariates used in a previous survival analysis were considered in the longitudinal model. The reference time used was time from diagnose until death from breast cancer. For diagnostic of the models fitted we have used empirical and theoretical variograms. To evaluate the fixed term of the longitudinal model we have tested for a changing point on the effect of time on the tumor marker progression. A longitudinal model was also fitted only to the subset of patients that died from breast cancer, using the reference time as time from date of death until blood test.

Stage at presentation of breast cancer in Luanda, Angola - a retrospective study

Background: It is expected that, by 2020, 15 million new cases of cancer will occur every year in the world, one million of them in Africa. Knowledge of cancer trends in African countries is far from adequate, and improvements in cancer prevention efforts are urgently needed. The aim of this study was to characterize breast cancer clinically and pathologically at presentation in Luanda, Angola; we additionally provide quality information that will be useful for breast cancer care planning in the country. Methods: Data on breast cancer cases were retrieved from the Angolan Institute of Cancer Control, from 2006 to 2014. For women diagnosed in 2009 (5-years of follow-up), demographic, clinical and pathological information, at presentation, was collected, namely age at diagnosis, parity, methods used for pathological diagnoses, tumor pathological characteristics, stage of disease and treatment. Descriptive statistics were performed. Results: The median age of women diagnosed with breast cancer in 2009 was 47 years old (range 25–89). The most frequent clinical presentation was breast swelling with axillary lymph nodes metastasis (44.9 %), followed by a mass larger than 5 cm (14.2 %) and lump (12.9 %). Invasive ductal carcinoma was the main histologic type (81.8 %). Only 10.1 % of cancer cases had a well differentiated histological grade. Cancers were diagnosed mostly at advanced stages (66.7 % in stage III and 11.1 % in stage IV). Discussion: In this study, breast cancer was diagnosed at a very advanced stage. Although it reports data from a single cancer center in Luanda, Angola it reinforces the need for early diagnosis and increasing awareness. According to the main challenges related to breast cancer diagnosis and treatment herein presented, we propose a realistic framework that would allow for the implementation of a breast cancer care program, built under a strong network based on cooperation, teaching, audit, good practices and the organization of health services. Conclusion: Angola needs urgently a program for early diagnosis of breast cancer.

Clinical benefit of fulvestrant in postmenopausal women with advanced breast cancer and primary or acquired resistance to aromatase inhibitors: final results of phase II Swiss Group for Clinical Cancer Research Trial (SAKK 21/00).

BACKGROUND: The aim of this study was to evaluate the efficacy and tolerability of fulvestrant, an estrogen receptor antagonist, in postmenopausal women with hormone-responsive tumors progressing after aromatase inhibitor (AI) treatment. PATIENTS AND METHODS: This is a phase II, open, multicenter, noncomparative study. Two patient groups were prospectively considered: group A (n=70) with AI-responsive disease and group B (n=20) with AI-resistant disease. Fulvestrant 250 mg was administered as intramuscular injection every 28 (+/-3) days. RESULTS: All patients were pretreated with AI and 84% also with tamoxifen or toremifene; 67% had bone metastases and 45% liver metastases. Fulvestrant administration was well tolerated and yielded a clinical benefit (CB; defined as objective response or stable disease [SD] for >or=24 weeks) in 28% (90% confidence interval [CI] 19% to 39%) of patients in group A and 37% (90% CI 19% to 58%) of patients in group B. Median time to progression (TTP) was 3.6 (95% CI 3.0 to 4.8) months in group A and 3.4 (95% CI 2.5 to 6.7) months in group B. CONCLUSIONS: Overall, 30% of patients who had progressed following prior AI treatment gained CB with fulvestrant, thereby delaying indication to start chemotherapy. Prior response to an AI did not appear to be predictive for benefit with fulvestrant.

Variation d'expression des récepteurs hormonaux et d'HER-2 dans l'évolution du cancer du sein : quelles implications en pratique clinique [Hormone receptors and HER-2 changes during breast cancer progression: clinical implications].

Breast cancer remains a major public health problem. Even if there is an increase in this cancer curability, metastatic breast cancer remains a lethal disease in the vast majority of cases. Therapeutic advances in the chemotherapeutic and targeted therapies fields induced an increase in survival, however the proportion of long survivors remains low. Phenotypic instability, an early process initiated during tumour progression, and continued on the metastatic stage of the disease, can be one of the putative hypotheses explaining these results. An increasing amount of scientific data are pledging for a reanalysis of the phenotypic profile regarding hormone receptors and HER-2 status of metastatic lesions in order to identify drugable targets and allow individualisation of the treatment of these metastatic breast cancer patients. Phenotypic changes between the primary tumour and the paired metastatic lymph nodes are a challenging pitfall, raising the question of which site has to be assessed in the adjuvant treatment decision process. This article presents a comprehensive analysis of the frequency of theses phenotypic changes altogether with new modalities to evaluate this phenotypic status.

Fragment N2, a caspase-3-generated RasGAP fragment, inhibits breast cancer metastatic progression

The p120 RasGAP protein negatively regulates Ras via its GAP domain. RasGAP carries several other domains that modulate several signaling molecules such as Rho. RasGAP is also a caspase-3 substrate. One of the caspase-3-generated RasGAP fragments, corresponding to amino acids 158-455 and called fragment N2, was previously reported to specifically sensitize cancer cells to death induced by various anticancer agents. Here, we show that fragment N2 inhibits migration in vitro and that it impairs metastatic progression of breast cancer to the lung. Hence, stress-activated caspase-3 might contribute to the suppression of metastasis through the generation of fragment N2. These results indicate that the activity borne by fragment N2 has a potential therapeutic relevance to counteract the metastatic process.

Toxicity at three years with and without irradiation of the internal mammary and medial supraclavicular lymph node chain in stage I to III breast cancer (EORTC trial 22922/10925).

INTRODUCTION: The EORTC 22922/10925 trial investigated the potential survival benefit and toxicity of elective irradiation of the internal mammary and medial supraclavicular (IM-MS) nodes Accrual completed in January 2004 and first results are expected in 2012. We present the toxicity reported until year 3 after treatment. PATIENTS AND METHODS: At each visit, toxicity was reported but severity was not graded routinely. Toxicity rates and performance status (PS) changes at three years were compared by chi(2) tests and logistic regression models in all the 3,866 of 4,004 patients eligible to the trial who received the allocated treatment. RESULTS: Only lung (fibrosis; dyspnoea; pneumonitis; any lung toxicities) (4.3% vs. 1.3%; p < 0.0001) but not cardiac toxicity (0.3% vs. 0.4%; p = 0.55) significantly increased with IM-MS treatment. No significant worsening of the PS was observed (p = 0.79), suggesting that treatment-related toxicity does not impair patient's daily activities. CONCLUSIONS: IM-MS irradiation seems well tolerated and does not significantly impair WHO PS at three years. A follow-up period of at least 10 years is needed to determine whether cardiac toxicity is increased after radiotherapy.

Breast cancer incidence and overdiagnosis in Catalonia (Spain)

Early detection of breast cancer (BC) with mammography may cause overdiagnosis andovertreatment, detecting tumors which would remain undiagnosed during a lifetime. The aims of this study were: first, to model invasive BC incidence trends in Catalonia (Spain) taking into account reproductive and screening data; and second, to quantify the extent of BC overdiagnosis. We modeled the incidence of invasive BC using a Poisson regression model. Explanatory variables were:age at diagnosis and cohort characteristics (completed fertility rate, percentage of women that use mammography at age 50, and year of birth). This model also was used to estimate the background incidence in the absence of screening. We used a probabilistic model to estimate the expected BC incidence if women in the population usedmammography as reported in health surveys. The difference between the observed and expected cumulative incidences provided an estimate of overdiagnosis.Incidence of invasive BC increased, especially in cohorts born from 1940 to 1955. The biggest increase was observed in these cohorts between the ages of 50 to 65 years, where the final BC incidence rates more than doubled the initial ones. Dissemination of mammography was significantly associated with BC incidence and overdiagnosis. Our estimates of overdiagnosis ranged from 0.4% to 46.6%, for women born around 1935 and 1950, respectively.Our results support the existence of overdiagnosis in Catalonia attributed to mammography usage, and the limited malignant potential of some tumors may play an important role. Women should be better informed about this risk. Research should be oriented towards personalized screening and risk assessment tools

Radiation induced apoptosis and initial DNA damage are inversely related in locally advanced breast cancer patients.

Background. DNA-damage assays, quantifying the initial number of DNA double-strand breaks induced by radiation, have been proposed as a predictive test for radiation-induced toxicity. Determination of radiation-induced apoptosis in peripheral blood lymphocytes by flow cytometry analysis has also been proposed as an approach for predicting normal tissue responses following radiotherapy. The aim of the present study was to explore the association between initial DNA damage, estimated by the number of double-strand breaks induced by a given radiation dose, and the radio-induced apoptosis rates observed. Methods. Peripheral blood lymphocytes were taken from 26 consecutive patients with locally advanced breast carcinoma. Radiosensitivity of lymphocytes was quantified as the initial number of DNA double-strand breaks induced per Gy and per DNA unit (200 Mbp). Radio-induced apoptosis at 1, 2 and 8 Gy was measured by flow cytometry using annexin V/propidium iodide. Results. Radiation-induced apoptosis increased in order to radiation dose and data fitted to a semi logarithmic mathematical model. A positive correlation was found among radio-induced apoptosis values at different radiation doses: 1, 2 and 8 Gy (p < 0.0001 in all cases). Mean DSB/Gy/DNA unit obtained was 1.70 ± 0.83 (range 0.63-4.08; median, 1.46). A statistically significant inverse correlation was found between initial damage to DNA and radio-induced apoptosis at 1 Gy (p = 0.034). A trend toward 2 Gy (p = 0.057) and 8 Gy (p = 0.067) was observed after 24 hours of incubation. Conclusions. An inverse association was observed for the first time between these variables, both considered as predictive factors to radiation toxicity.