PCR bias toward the wild-type k-ras and p53 sequences: Implications for PCR detection of mutations and cancer diagnosis

PCR-based cancer diagnosis requires detection of rare mutations in k-ras, p53 or other genes. The assumption has been that mutant and wild-type sequences amplify with near equal efficiency, so that they are eventually present in proportions representative of the starting material. Work factor IX suggests that this assumption is invalid for one case of near-sequence identity To test the generality of this phenomenon and its relevance to cancer diagnosis, primers distant from point mutations in p53 and k-ras were used to amplify, wild-type and mutant sequences from these genes. A substantial bias against PCR amplification of mutants was observed for two regions of the p53 gene and one region of k-ras. For kras and p53, bias was observed when the wild-type and mutant sequences were amplified separately or when mixed in equal proportions before PCR. Bias was present with proofreading and non-proofreading polymerases. Mutant and wild-type segments of the factor V cystic fibrosis transmembrane conductance regulator and prothrombin genes were amplified and did not exhibit PCR bias. Therefore, the assumption of equal PCR efficiency for point mutant and wild-type sequences is invalid in several systems. Quantitative or diagnostic PCR will require validation for each locus, and enrichment strategies may be needed to optimize detection of mutants.

The Role of Prostate Specific Membrane Antigen and Pepsinogen C Tissue Expression as an Adjunctive Method to Prostate Cancer Diagnosis

Purpose: The diagnosis of prostate cancer in men with persistently increased prostate specific antigen after a negative prostate biopsy has become a great challenge for urologists and pathologists. We analyzed the diagnostic value of 6 genes in the tissue of patients with prostate cancer. Materials and Methods: The study was comprised of 50 patients with localized disease who underwent radical prostatectomy. Gene selection was based on a previous microarray analysis. Among 4,147 genes with different expressions between 2 pools of patients 6 genes (PSMA, TMEFF2, GREB1, TH1L, IgH3 and PGC) were selected. These genes were tested for diagnostic value using the quantitative reverse transcription polymerase chain reaction method. Initially malignant tissue samples from 33 patients were analyzed and in the second part of the study we analyzed benign tissue samples from the other 17 patients with prostate cancer. The control group was comprised of tissue samples of patients with benign prostatic hyperplasia. Results: Analysis of malignant prostatic tissue demonstrated that prostate specific membrane antigen was over expressed (mean 9 times) and pepsinogen C was under expressed (mean 1.3 X 10(-4) times) in all cases compared to benign prostatic hyperplasia. The other 4 tested genes showed a variable expression pattern not allowing for differentiation between benign and malignant cases. When we tested these results in the benign prostate tissues from patients with cancer, pepsinogen C maintained the expression pattern. In terms of prostate specific membrane antigen, despite over expression in most cases (mean 12 times), 2 cases (12%) presented with under expression. Conclusions: Pepsinogen C tissue expression may constitute a powerful adjunctive method to prostate biopsy in the diagnosis of prostate cancer cases.

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.

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.

Risk of prostate, breast and colorectal cancer after skin cancer diagnosis.

Ultraviolet radiation is the major cause of skin cancer, but promotes vitamin D synthesis, and vitamin D has been inversely related to the risk of several common cancers including prostate, breast and colorectum. We therefore computed the incidence of prostate, breast and colorectal cancer following skin cancer using the datasets of the Swiss cancer Registries of Vaud and Neuchâtel. Between 1974 and 2005, 6,985 histologically confirmed squamous cell skin cancers, 21,046 basal cell carcinomas and 3,346 cutaneous malignant melanomas were registered, and followed up to the end of 2005 for the occurrence of second primary cancer of the prostate, breast and colorectum. Overall, 680 prostate cancers were observed versus 568.3 expected (standardized incidence ratio (SIR) = 1.20; 95% confidence interval (CI): 1.11-1.29), 440 breast cancers were observed versus 371.5 expected (SIR = 1.18; 95% CI: 1.08-1.30) and 535 colorectal cancers were observed versus 464.6 expected (SIR = 1.15; 95% CI: 1.06-1.25). When basal cell, squamous cell and skin melanoma were considered separately, all the SIRs for prostate, breast and colorectal cancers were around or slightly above unity. Likewise, the results were consistent across strata of age at skin cancer diagnosis and location (head and neck versus others), and for male and female colorectal cancers. These findings, based on a population with a long tradition of systematic histologic examination of all surgically treated skin lesions, do not support the hypothesis that prostate, breast and colorectal cancer risk is decreased following skin cancer.

L'immunoscintigraphie par les anticorps monoclonaux radiomarqués. Evolution d'une méthode de diagnostic du cancer et espoir d'une nouvelle forme de thérapie [Immunoscintigraphy using radio-labeled monoclonal antibodies. Development of a method of cancer diagnosis and hopes for a new form of therapy].

Personal results are presented to illustrate the development of immunoscintigraphy for the detection of cancer over the last 12 years, from the early experimental results in nude mice grafted with human colon carcinoma to the most modern form of immunoscintigraphy applied to patients, using I123 labeled Fab fragments from monoclonal anti-CEA antibodies detected by single photon emission computerized tomography (SPECT). The first generation of immunoscintigraphy used I131 labeled, immunoadsorbent purified, polyclonal anti-CEA antibodies and planar scintigraphy, as the detection system. The second generation used I131 labeled monoclonal anti-CEA antibodies and SPECT, while the third generation employed I123 labeled fragments of monoclonal antibodies and SPECT. The improvement in the precision of tumor images with the most recent forms of immunoscintigraphy is obvious. However, we think the usefulness of immunoscintigraphy for routine cancer management has not yet been entirely demonstrated. Further prospective trials are still necessary to determine the precise clinical role of immunoscintigraphy. A case report is presented on a patient with two liver metastases from a sigmoid carcinoma, who received through the hepatic artery a therapeutic dose (100 mCi) of I131 coupled to 40 mg of a mixture of two high affinity anti-CEA monoclonal antibodies. Excellent localisation in the metastases of the I131 labeled antibodies was demonstrated by SPECT and the treatment was well tolerated. The irradiation dose to the tumor, however, was too low at 4300 rads (with 1075 rads to the normal liver and 88 rads to the bone marrow), and no evidence of tumor regression was obtained. Different approaches for increasing the irradiation dose delivered to the tumor by the antibodies are considered.

Estimation of lung cancer diagnosis and treatment costs based on a patient-level analysis in Catalonia (Spain)

Background: Assessing of the costs of treating disease is necessary to demonstrate cost-effectiveness and to estimate the budget impact of new interventions and therapeutic innovations. However, there are few comprehensive studies on resource use and costs associated with lung cancer patients in clinical practice in Spain or internationally. The aim of this paper was to assess the hospital cost associated with lung cancer diagnosis and treatment by histology, type of cost and stage at diagnosis in the Spanish National Health Service. Methods: A retrospective, descriptive analysis on resource use and a direct medical cost analysis were performed. Resource utilisation data were collected by means of patient files from nine teaching hospitals. From a hospital budget impact perspective, the aggregate and mean costs per patient were calculated over the first three years following diagnosis or up to death. Both aggregate and mean costs per patient were analysed by histology, stage at diagnosis and cost type. Results: A total of 232 cases of lung cancer were analysed, of which 74.1% corresponded to non-small cell lung cancer (NSCLC) and 11.2% to small cell lung cancer (SCLC); 14.7% had no cytohistologic confirmation. The mean cost per patient in NSCLC ranged from 13,218 Euros in Stage III to 16,120 Euros in Stage II. The main cost components were chemotherapy (29.5%) and surgery (22.8%). Advanced disease stages were associated with a decrease in the relative weight of surgical and inpatient care costs but an increase in chemotherapy costs. In SCLC patients, the mean cost per patient was 15,418 Euros for limited disease and 12,482 Euros for extensive disease. The main cost components were chemotherapy (36.1%) and other inpatient costs (28.7%). In both groups, the Kruskall-Wallis test did not show statistically significant differences in mean cost per patient between stages. Conclusions: This study provides the costs of lung cancer treatment based on patient file reviews, with chemotherapy and surgery accounting for the major components of costs. This cost analysis is a baseline study that will provide a useful source of information for future studies on cost-effectiveness and on the budget impact of different therapeutic innovations in Spain.

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.

Accuracy of Tc-99m-sestamibi scintimammography for breast cancer diagnosis

Scintimammography using Tc-99m-sestamibi is a noninvasive and painless diagnostic imaging method that is used to detect breast cancer when mammography is inconclusive Because of the advantages of labeling v '7,ith Tc-99m-sestamibi and its high efficiency in detecting carcinomas, it is the most widespread agent for this purpose Its accumulation in the tumor has multifactorial causes and does not depend on the presence of architectural distortion or local or diffuse density variation in the breast The objective of tfiis study was to evaluate the accuracy of scintimammography 1 for detecting breast cancer One hundred and fifty-seven patients presenting 158 palpable and non-palpable breast nodules were evaluated Three patients were male and 154 were female, aged between 14 and 81 years All patients underwent scintimammography, and the nodule was subjected i to cytological or histological study, i e, the gold standard for diagnosing cancer One hundred and eleven malignant and 47 benign nodules were detected, with predominance of ductal carcinomas (n=94) and fibroadenoma/fibrocysiic condition (n=11/n=11), respectively The mean size was 3 11 cm (7-10 cm) among the malignant nodules and 2 07 cm among the benign nodules (0 5-10 cm) The sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 89, 89, 95, 78 and 89%, respectively Analysis on the histological types showed that the technique was more effective on tumors that were more aggressive, such as ductal carcinoma In this study, Tc-99m-sestamibi scintim immography was shown to be an important tool for diagnosing breast cancer when mammography was inconclusive

Surface-enhanced Raman scattering (SERS) applied to cancer diagnosis and detection of pesticides, explosives, and drugs

The inelastic scattering of light, Raman scattering, presents a very low cross section. However, the signal can be amplified by several orders of magnitude, leading to the so-called surface-enhanced Raman scattering (SERS) phenomenon. Basically, the SERS effect is achieved when the target molecule (analyte) is adsorbed onto metallic nanoparticles, usually noble metals. This article presents an overview of the applications of SERS to cancer diagnosis and the detection of pesticides, explosives, and drugs (illicit and pharmacological). SERS is routinely applied nowadays to detect and identify analytes at very low concentrations, including for single-molecule detection. However, the application of SERS as an analytical tool requires reliable and reproducible SERS substrates, in terms of enhancement factors, which depends on the size, shape, and aggregation of the metallic nanoparticles. Therefore, the production of reliable and reproducible SERS substrates is a challenge in the field. Besides, the metallic nanoparticles can also induce changes in the system by possible interactions with the analyte under investigation, which must be taken into account. This review will present work in which, under certain specific experimental conditions, SERS has been analytically applied.

Longitudinal patterns in survival, comorbidity, healthcare utilization and quality of care among older women following breast cancer diagnosis

OBJECTIVES To compare longitudinal patterns of health care utilization and quality of care for other health conditions between breast cancer-surviving older women and a matched cohort without breast cancer. DESIGN Prospective five-year longitudinal comparison of cases and matched controls. SUBJECTS Newly identified breast cancer patients recruited during 1997–1999 from four geographic regions (Los Angeles, CA; Minnesota; North Carolina; and Rhode Island; N = 422) were matched by age, race, baseline comorbidity and zip code location with up to four non-breast-cancer controls (N = 1,656). OUTCOMES Survival; numbers of hospitalized days and physician visits; total inpatient and outpatient Medicare payments; guideline monitoring for patients with cardiovascular disease and diabetes, and bone density testing and colorectal cancer screening. RESULTS Five-year survival was similar for cases and controls (80% and 82%, respectively; p = 0.18). In the first follow-up year, comorbidity burden and health care utilization were higher for cases (p < 0.01), with most differences diminishing over time. However, the number of physician visits was higher for cases (p < 0.01) in every year, driven partly by more cancer and surgical specialist visits. Cases and controls adhered similarly to recommended bone density testing, and monitoring of cardiovascular disease and diabetes; adherence to recommended colorectal cancer screening was better among cases. CONCLUSION Breast cancer survivors’ health care utilization and disease burden return to pre-diagnosis levels after one year, yet their greater use of outpatient care persists at least five years. Quality of care for other chronic health problems is similar for cases and controls.