Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

Microwave imaging of the axilla to aid breast cancer diagnosis

Breast cancer is the most common type of cancer among women all over the world. An important issue that is not commonly addressed in breast cancer imaging literature is the importance of imaging the underarm region—where up to 80% of breast cancer cells can metastasise to. The first axillary lymph nodes to receive drainage from the primary tumour in the breast are called Sentinel Node. If cancer cells are found in the Sentinel Node, there is an increased risk of metastatic breast cancer which makes this evaluation crucial to decide what follow-up exams and therapy to follow. However, non-invasive detection of cancer cells in the lymph nodes is often inconclusive, leading to the surgical removal of too many nodes which causes adverse side-effects for patients. Microwave Imaging is one of the most promising non-invasive imaging modalities for breast cancer early screening and monitoring. This novel study tests the feasibility of imaging the axilla region by means of the simulation of an Ultra-Wideband Microwave Imaging system. Simulations of such system are completed in several 2D underarm models that mimic the axilla. Initial imaging results are obtained by means of processing the simulated backscattered signals by eliminating artefacts caused by the skin and beamforming the processed signals in order to time-align all the signals recorded at each antenna. In this dissertation several image formation algorithms are implemented and compared by visual inspection of the resulting images and through a range of performance metrics, such as Signal-to-Clutter Ratio and FullWidth Half Maximum calculations. The results in this study showed that Microwave Imaging is a promising technique that might allow to identify the presence and location of metastasised cancer cells in axillary lymph nodes, enabling the non-invasive evaluation of breast cancer staging.

Breast and cervical cancer screening programme implementation in 16 countries.

OBJECTIVES: There is a continuing need to monitor and evaluate the impact of organized screening programmes on cancer incidence and mortality. We report results from a programme assessment conducted within the International Cancer Screening Network (ICSN) to understand the characteristics of cervical screening programmes within countries that have established population-based breast cancer screening programmes. METHODS: In 2007-2008, we asked 26 ICSN country representatives to complete a web-based survey that included questions on breast and cervical cancer screening programmes. We summarized information from 16 countries with both types of organized programmes. RESULTS: In 63% of these countries, the organization of the cervical cancer screening programme was similar to that of the breast cancer screening programme in the same country. There were differences in programme characteristics, including year established (1962-2003 cervical; 1986-2002 breast) and ages covered (15-70+ cervical; 40-75+ breast). Adoption of new screening technologies was evident (44% liquid-based Pap tests; 13% human papillomavirus (HPV)-triage tests cervical; 56% digital mammography breast). There was wide variation in participation rates for both programme types (<4-80% cervical; 12-88% breast), and participation rates tended to be higher for cervical (70-80%) than for breast (60-70%) cancer screening programmes. Eleven ICSN member countries had approved the HPV vaccine and five more were considering its use in their organized programmes. CONCLUSION: Overall, there were similarities and differences in the organization of breast and cervical cancer screening programmes among ICSN countries. This assessment can assist established and new screening programmes in understanding the organization and structure of cancer screening programmes.

Tumor architecture exerts no bias on nuclear grading in breast cancer diagnosis.

We recently reported that nuclear grading in prostate cancer is subject to a strong confirmation bias induced by the tumor architecture. We now wondered whether a similar bias governs nuclear grading in breast carcinoma. An unannounced test was performed at a pathology conference. Pathologists were asked to grade nuclei in a PowerPoint presentation. Circular high power fields of 27 invasive ductal carcinomas were shown, superimposed over low power background images of either tubule-rich or tubule-poor carcinomas. We found (a) that diagnostic reproducibility of nuclear grades was poor to moderate (weighed kappa values between 0.07 and 0.54, 27 cases, 44 graders), but (b) that nuclear grades were not affected by the tumor architecture. We speculate that the categorized grading in breast cancer, separating tubule formation, nuclear pleomorphism, and mitotic figure counts in a combined three tier score, prevents the bias that architecture exerts on nuclear grades in less well-controlled situations.

Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series.

PURPOSE: Recently, a 76-gene prognostic signature able to predict distant metastases in lymph node-negative (N(-)) breast cancer patients was reported. The aims of this study conducted by TRANSBIG were to independently validate these results and to compare the outcome with clinical risk assessment. EXPERIMENTAL DESIGN: Gene expression profiling of frozen samples from 198 N(-) systemically untreated patients was done at the Bordet Institute, blinded to clinical data and independent of Veridex. Genomic risk was defined by Veridex, blinded to clinical data. Survival analyses, done by an independent statistician, were done with the genomic risk and adjusted for the clinical risk, defined by Adjuvant! Online. RESULTS: The actual 5- and 10-year time to distant metastasis were 98% (88-100%) and 94% (83-98%), respectively, for the good profile group and 76% (68-82%) and 73% (65-79%), respectively, for the poor profile group. The actual 5- and 10-year overall survival were 98% (88-100%) and 87% (73-94%), respectively, for the good profile group and 84% (77-89%) and 72% (63-78%), respectively, for the poor profile group. We observed a strong time dependence of this signature, leading to an adjusted hazard ratio of 13.58 (1.85-99.63) and 8.20 (1.10-60.90) at 5 years and 5.11 (1.57-16.67) and 2.55 (1.07-6.10) at 10 years for time to distant metastasis and overall survival, respectively. CONCLUSION: This independent validation confirmed the performance of the 76-gene signature and adds to the growing evidence that gene expression signatures are of clinical relevance, especially for identifying patients at high risk of early distant metastases.

Cancer du sein et obésité, une liaison dangereuse [Breast cancer and obesity, a dangerous relation].

Obesity is associated with different cancers including breast cancer, whose incidence is increased in postmenopausal women. It has an adverse impact on the prognosis of the patients, regardless of their menopausal status. The fact of receiving a systemic adjuvant therapy does not neutralize the prognostic role of obesity. Moderate weight loss after cancer diagnosis could improve the outcome of the patients, while a weight gain during treatment seems without significant effect. Currently available data are still too incomplete to justify systematic programs to lose weight with an oncologic therapeutic aim. However, it is worth to encourage and support our patients to have an optimal diet, physical activity, and to lose weight as promotion of general health.

Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures.

INTRODUCTION: Breast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to one another nor did it examine the contribution of well-known biological processes of breast cancer tumorigenesis to their prognostic performance. METHOD: To address the above issues and to further validate these initial findings, we performed the largest meta-analysis of publicly available breast cancer gene expression and clinical data, which are comprised of 2,833 breast tumors. Gene coexpression modules of three key biological processes in breast cancer (namely, proliferation, estrogen receptor [ER], and HER2 signaling) were used to dissect the role of constituent genes of nine prognostic signatures. RESULTS: Using a meta-analytical approach, we consolidated the signatures associated with ER signaling, ERBB2 amplification, and proliferation. Previously published expression-based nomenclature of breast cancer 'intrinsic' subtypes can be mapped to the three modules, namely, the ER-/HER2- (basal-like), the HER2+ (HER2-like), and the low- and high-proliferation ER+/HER2- subtypes (luminal A and B). We showed that all nine prognostic signatures exhibited a similar prognostic performance in the entire dataset. Their prognostic abilities are due mostly to the detection of proliferation activity. Although ER- status (basal-like) and ERBB2+ expression status correspond to bad outcome, they seem to act through elevated expression of proliferation genes and thus contain only indirect information about prognosis. Clinical variables measuring the extent of tumor progression, such as tumor size and nodal status, still add independent prognostic information to proliferation genes. CONCLUSION: This meta-analysis unifies various results of previous gene expression studies in breast cancer. It reveals connections between traditional prognostic factors, expression-based subtyping, and prognostic signatures, highlighting the important role of proliferation in breast cancer prognosis.

Centres du sein: caprice ou nécessité [Breast Centers: whim or necessity?].

In order to prevent disparities in the management of breast cancer having a direct impact on the prognosis of patients, to promote early detection and optimal treatment while considering the quality of life of patients, Breast Centers are being set up in Switzerland on the basis of existing models in Europe. The centers provide also follow-up of patients and are submitted to certification criteria established by the Swiss Society of Senology and the Swiss Cancer League. These criteria include in particular the expertise of specialists based on a sufficient volume of activity and training, compliance with recommendations of clinical practice, integration of supportive care and timeliness of care. The certification process is voluntary. A database enables the regular assessment of the provided care and of the compliance with standards. The aim and the modalities of the creation of the Breast Centers are discussed.

Comparing interval breast cancer rates in Norway and North Carolina: results and challenges.

OBJECTIVE: To compare interval breast cancer rates (ICR) between a biennial organized screening programme in Norway and annual opportunistic screening in North Carolina (NC) for different conceptualizations of interval cancer. SETTING: Two regions with different screening practices and performance. METHODS: 620,145 subsequent screens (1996-2002) performed in women aged 50-69 and 1280 interval cancers were analysed. Various definitions and quantification methods for interval cancers were compared. RESULTS: ICR for one year follow-up were lower in Norway compared with NC both when the rate was based on all screens (0.54 versus 1.29 per 1000 screens), negative final assessments (0.54 versus 1.29 per 1000 screens), and negative screening assessments (0.53 versus 1.28 per 1000 screens). The rate of ductal carcinoma in situ was significantly lower in Norway than in NC for cases diagnosed in both the first and second year after screening. The distributions of histopathological tumour size and lymph node involvement in invasive cases did not differ between the two regions for interval cancers diagnosed during the first year after screening. In contrast, in the second year after screening, tumour characteristics remained stable in Norway but became prognostically more favorable in NC. CONCLUSION: Even when applying a common set of definitions of interval cancer, the ICR was lower in Norway than in NC. Different definitions of interval cancer did not influence the ICR within Norway or NC. Organization of screening and screening performance might be major contributors to the differences in ICR between Norway and NC.

A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer.

To better understand the relationship between tumor-host interactions and the efficacy of chemotherapy, we have developed an analytical approach to quantify several biological processes observed in gene expression data sets. We tested the approach on tumor biopsies from individuals with estrogen receptor-negative breast cancer treated with chemotherapy. We report that increased stromal gene expression predicts resistance to preoperative chemotherapy with 5-fluorouracil, epirubicin and cyclophosphamide (FEC) in subjects in the EORTC 10994/BIG 00-01 trial. The predictive value of the stromal signature was successfully validated in two independent cohorts of subjects who received chemotherapy but not in an untreated control group, indicating that the signature is predictive rather than prognostic. The genes in the signature are expressed in reactive stroma, according to reanalysis of data from microdissected breast tumor samples. These findings identify a previously undescribed resistance mechanism to FEC treatment and suggest that antistromal agents may offer new ways to overcome resistance to chemotherapy.

Quantitative ultrasound imaging during shear wave propagation for application related to breast cancer diagnosis

Dans le contexte de la caractérisation des tissus mammaires, on peut se demander ce que l’examen d’un attribut en échographie quantitative (« quantitative ultrasound » - QUS) d’un milieu diffusant (tel un tissu biologique mou) pendant la propagation d’une onde de cisaillement ajoute à son pouvoir discriminant. Ce travail présente une étude du comportement variable temporel de trois paramètres statistiques (l’intensité moyenne, le paramètre de structure et le paramètre de regroupement des diffuseurs) d’un modèle général pour l’enveloppe écho de l’onde ultrasonore rétrodiffusée (c.-à-d., la K-distribution homodyne) sous la propagation des ondes de cisaillement. Des ondes de cisaillement transitoires ont été générés en utilisant la mèthode d’ imagerie de cisaillement supersonique ( «supersonic shear imaging » - SSI) dans trois fantômes in-vitro macroscopiquement homogènes imitant le sein avec des propriétés mécaniques différentes, et deux fantômes ex-vivo hétérogénes avec tumeurs de souris incluses dans un milieu environnant d’agargélatine. Une comparaison de l’étendue des trois paramètres de la K-distribution homodyne avec et sans propagation d’ondes de cisaillement a montré que les paramètres étaient significativement (p < 0,001) affectès par la propagation d’ondes de cisaillement dans les expériences in-vitro et ex-vivo. Les résultats ont également démontré que la plage dynamique des paramétres statistiques au cours de la propagation des ondes de cisaillement peut aider à discriminer (avec p < 0,001) les trois fantômes homogènes in-vitro les uns des autres, ainsi que les tumeurs de souris de leur milieu environnant dans les fantômes hétérogénes ex-vivo. De plus, un modéle de régression linéaire a été appliqué pour corréler la plage de l’intensité moyenne sous la propagation des ondes de cisaillement avec l’amplitude maximale de déplacement du « speckle » ultrasonore. La régression linéaire obtenue a été significative : fantômes in vitro : R2 = 0.98, p < 0,001 ; tumeurs ex-vivo : R2 = 0,56, p = 0,013 ; milieu environnant ex-vivo : R2 = 0,59, p = 0,009. En revanche, la régression linéaire n’a pas été aussi significative entre l’intensité moyenne sans propagation d’ondes de cisaillement et les propriétés mécaniques du milieu : fantômes in vitro : R2 = 0,07, p = 0,328, tumeurs ex-vivo : R2 = 0,55, p = 0,022 ; milieu environnant ex-vivo : R2 = 0,45, p = 0,047. Cette nouvelle approche peut fournir des informations supplémentaires à l’échographie quantitative statistique traditionnellement réalisée dans un cadre statique (c.-à-d., sans propagation d’ondes de cisaillement), par exemple, dans le contexte de l’imagerie ultrasonore en vue de la classification du cancer du sein.

Solid phase microextraction, mass spectrometry and metabolomic approaches for detection of potential urinary cancer biomarkers: a powerful strategy for breast cancer diagnosis

A sensitive assay to identify volatile organic metabolites (VOMs) as biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. Therefore the aim of this study was to establish the urinary metabolomic profile of breast cancer patients and healthy individuals (control group) and to explore the VOMs as potential biomarkers in breast cancer diagnosis at early stage. Solid-phase microextraction (SPME) using CAR/PDMS sorbent combined with gas chromatography–mass spectrometry was applied to obtain metabolomic information patterns of 26 breast cancer patients and 21 healthy individuals (controls). A total of seventy-nine VOMs, belonging to distinct chemical classes, were detected and identified in control and breast cancer groups. Ketones and sulfur compounds were the chemical classes with highest contribution for both groups. Results showed that excretion values of 6 VOMs among the total of 79 detected were found to be statistically different (p < 0.05). A significant increase in the peak area of (−)-4-carene, 3-heptanone, 1,2,4-trimethylbenzene, 2-methoxythiophene and phenol, in VOMs of cancer patients relatively to controls was observed. Statiscally significant lower abundances of dimethyl disulfide were found in cancer patients. Bioanalytical data were submitted to multivariate statistics [principal component analysis (PCA)], in order to visualize clusters of cases and to detect the VOMs that are able to differentiate cancer patients from healthy individuals. Very good discrimination within breast cancer and control groups was achieved. Nevertheless, a deep study using a larger number of patients must be carried out to confirm the results.