Colorectal Cancer Classification and Cell Heterogeneity: A Systems Oncology Approach.

Colorectal cancer is a heterogeneous disease that manifests through diverse clinical scenarios. During many years, our knowledge about the variability of colorectal tumors was limited to the histopathological analysis from which generic classifications associated with different clinical expectations are derived. However, currently we are beginning to understand that under the intense pathological and clinical variability of these tumors there underlies strong genetic and biological heterogeneity. Thus, with the increasing available information of inter-tumor and intra-tumor heterogeneity, the classical pathological approach is being displaced in favor of novel molecular classifications. In the present article, we summarize the most relevant proposals of molecular classifications obtained from the analysis of colorectal tumors using powerful high throughput techniques and devices. We also discuss the role that cancer systems biology may play in the integration and interpretation of the high amount of data generated and the challenges to be addressed in the future development of precision oncology. In addition, we review the current state of implementation of these novel tools in the pathological laboratory and in clinical practice.

A colorectal cancer classification system that associates cellular phenotype and responses to therapy.

Colorectal cancer (CRC) is a major cause of cancer mortality. Whereas some patients respond well to therapy, others do not, and thus more precise, individualized treatment strategies are needed. To that end, we analyzed gene expression profiles from 1,290 CRC tumors using consensus-based unsupervised clustering. The resultant clusters were then associated with therapeutic response data to the epidermal growth factor receptor-targeted drug cetuximab in 80 patients. The results of these studies define six clinically relevant CRC subtypes. Each subtype shares similarities to distinct cell types within the normal colon crypt and shows differing degrees of 'stemness' and Wnt signaling. Subtype-specific gene signatures are proposed to identify these subtypes. Three subtypes have markedly better disease-free survival (DFS) after surgical resection, suggesting these patients might be spared from the adverse effects of chemotherapy when they have localized disease. One of these three subtypes, identified by filamin A expression, does not respond to cetuximab but may respond to cMET receptor tyrosine kinase inhibitors in the metastatic setting. Two other subtypes, with poor and intermediate DFS, associate with improved response to the chemotherapy regimen FOLFIRI in adjuvant or metastatic settings. Development of clinically deployable assays for these subtypes and of subtype-specific therapies may contribute to more effective management of this challenging disease.

Cancer classification using the Immunoscore: a worldwide task force

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Prognostic implications of the seventh edition of the international union against cancer classification for patients with gastric cancer: the Western experience of patients treated in a single-center European institution

PURPOSE Validity of the seventh edition of the American Joint Committee on Cancer/International Union Against Cancer (AJCC/UICC) staging systems for gastric cancer has been evaluated in several studies, mostly in Asian patient populations. Only few data are available on the prognostic implications of the new classification system on a Western population. Therefore, we investigated its prognostic ability based on a German patient cohort. PATIENTS AND METHODS Data from a single-center cohort of 1,767 consecutive patients surgically treated for gastric cancer were classified according to the seventh edition and were compared using the previous TNM/UICC classification. Kaplan-Meier analyses were performed for all TNM stages and UICC stages in a comparative manner. Additional survival receiver operating characteristic analyses and bootstrap-based goodness-of-fit comparisons via Bayesian information criterion (BIC) were performed to assess and compare prognostic performance of the competing classification systems. RESULTS We identified the UICC pT/pN stages according to the seventh edition of the AJCC/UICC guidelines as well as resection status, age, Lauren histotype, lymph-node ratio, and tumor grade as independent prognostic factors in gastric cancer, which is consistent with data from previous Asian studies. Overall survival rates according to the new edition were significantly different for each individual's pT, pN, and UICC stage. However, BIC analysis revealed that, owing to higher complexity, the new staging system might not significantly alter predictability for overall survival compared with the old system within the analyzed cohort from a statistical point of view. CONCLUSION The seventh edition of the AJCC/UICC classification was found to be valid with distinctive prognosis for each stage. However, the AJCC/UICC classification has become more complex without improving predictability for overall survival in a Western population. Therefore, simplification with better predictability of overall survival of patients with gastric cancer should be considered when revising the seventh edition.

Breast cancer prognostic classification in the molecular era: the role of histological grade.

Breast cancer is a heterogeneous disease with varied morphological appearances, molecular features, behavior, and response to therapy. Current routine clinical management of breast cancer relies on the availability of robust clinical and pathological prognostic and predictive factors to support clinical and patient decision making in which potentially suitable treatment options are increasingly available. One of the best-established prognostic factors in breast cancer is histological grade, which represents the morphological assessment of tumor biological characteristics and has been shown to be able to generate important information related to the clinical behavior of breast cancers. Genome-wide microarray-based expression profiling studies have unraveled several characteristics of breast cancer biology and have provided further evidence that the biological features captured by histological grade are important in determining tumor behavior. Also, expression profiling studies have generated clinically useful data that have significantly improved our understanding of the biology of breast cancer, and these studies are undergoing evaluation as improved prognostic and predictive tools in clinical practice. Clinical acceptance of these molecular assays will require them to be more than expensive surrogates of established traditional factors such as histological grade. It is essential that they provide additional prognostic or predictive information above and beyond that offered by current parameters. Here, we present an analysis of the validity of histological grade as a prognostic factor and a consensus view on the significance of histological grade and its role in breast cancer classification and staging systems in this era of emerging clinical use of molecular classifiers.

Evolution of colorectal cancer: Change of pace and change of direction

This review compiles evidence for an alternative to the classical adenoma-carcinoma sequence in the evolution of colorectal cancer. It is suggested that between 30 and 50% of colorectal cancers are not initiated by mutation of the tumor suppressor gene APC, but through the epigenetic silencing of genes implicated in the control of differentiation, cell cycle control and DNA repair proficiency. The precursor polyps are often characterized by a serrated architecture, and include hyperplastic polyps, admixed polyps and serrated adenomas. The alternative pathway is heterogeneous and may culminate in cancers showing low or high level DNA microsatellite instability (MSI-L and MSI-H, respectively), and in cancers that are microsatellite stable (MSS). Cancers showing DNA MSI may be characterized by an accelerated evolution. Cancers in hereditary non-polyposis colorectal cancer show features of both classical (adenoma and APC mutation) and alternative pathways (rapid evolution, MSI-H and lack of chromosomal instability). (C) 2001 Blackwell Science Asia Pty Ltd.

Axillary Lymph Node Dissection for Sentinel Lymph Node Micrometastases May Be Safely Omitted in Early-Stage Breast Cancer Patients: Long-Term Outcomes of a Prospective Study.

OBJECTIVES: To evaluate the long-term disease-free and overall survival of patients with sentinel lymph node (SLN) micrometastases, in whom a completion axillary lymph node dissection (ALND) was systematically omitted. BACKGROUND: The use of step sectioning and immunohistochemistry for SLN analysis results in a more accurate histopathologic examination and a higher detection rate of micrometastases. However, the clinical relevance and therapeutic implications of SLN micrometastases remain a matter of debate. METHODS: In this prospective study, 236 SLN biopsies were performed in 234 consecutive early-stage breast cancer patients (T1, T2 </= 3 cm, cN0 M0) between 1998 and 2002. The SLN were examined by step sectioning and stained with hematoxylin and eosin and immunohistochemistry. None of the patients with negative SLN or SLN micrometastases (International Union Against Cancer classification, >.2 mm to </=2 mm) underwent a completion ALND or radiation to the axilla. Long-term overall and disease-free survivals were compared between patients with negative SLN and those with SLN micrometastases by log rank tests. RESULTS: The SLN was negative in 55% of patients (123 of 224). SLN micrometastases were detected in 27 patients (27 of 224, 12%). After a median follow-up of 77 months (range, 24-106 months), neither locoregional recurrences nor distant metastases occurred in any of the 27 patients with SLN micrometastases. There were no statistically significant differences for overall (P = .656), locoregional (P = .174), and axillary and distant disease-free survival (P = .15) between patients with negative SLN and SLN micrometastases. CONCLUSIONS: This analysis of unselected patients provides evidence that a completion level I and II ALND may be safely omitted in early-stage breast cancer patients with SLN micrometastases.

Identification of molecular subtypes and gene expression patterns of breast cancer analysing RNA-seq data

Breast cancer is the most common diagnosed cancer and the leading cause of cancer death among females worldwide. It is considered a highly heterogeneous disease and it must be classified into more homogeneous groups. Hence, the purpose of this study was to classify breast tumors based on variations in gene expression patterns derived from RNA sequencing by using different class discovery methods. 42 breast tumors paired-samples were sequenced by Illumine Genome Analyzer and the data was analyzed and prepared by TopHat2 and htseq-count. As reported previously, breast cancer could be grouped into five main groups known as basal epithelial-like group, HER2 group, normal breast-like group and two Luminal groups with a distinctive expression profile. Classifying breast tumor samples by using PAM50 method, the most common subtype was Luminal B and was significantly associated with ESR1 and ERBB2 high expression. Luminal A subtype had ESR1 and SLC39A6 significant high expression, whereas HER2 subtype had a high expression of ERBB2 and CNNE1 genes and low luminal epithelial gene expression. Basal-like and normal-like subtypes were associated with low expression of ESR1, PgR and HER2, and had significant high expression of cytokeratins 5 and 17. Our results were similar compared with TGCA breast cancer data results and with known studies related with breast cancer classification. Classifying breast tumors could add significant prognostic and predictive information to standard parameters, and moreover, identify marker genes for each subtype to find a better therapy for patients with breast cancer.

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.

Classification of Mammograms and DW T based Detection of Microcalcification

Cancer treatment is most effective when it is detected early and the progress in treatment will be closely related to the ability to reduce the proportion of misses in the cancer detection task. The effectiveness of algorithms for detecting cancers can be greatly increased if these algorithms work synergistically with those for characterizing normal mammograms. This research work combines computerized image analysis techniques and neural networks to separate out some fraction of the normal mammograms with extremely high reliability, based on normal tissue identification and removal. The presence of clustered microcalcifications is one of the most important and sometimes the only sign of cancer on a mammogram. 60% to 70% of non-palpable breast carcinoma demonstrates microcalcifications on mammograms [44], [45], [46].WT based techniques are applied on the remaining mammograms, those are obviously abnormal, to detect possible microcalcifications. The goal of this work is to improve the detection performance and throughput of screening-mammography, thus providing a ‘second opinion ‘ to the radiologists. The state-of- the- art DWT computation algorithms are not suitable for practical applications with memory and delay constraints, as it is not a block transfonn. Hence in this work, the development of a Block DWT (BDWT) computational structure having low processing memory requirement has also been taken up.

Proliferating cell nuclear antigen (PCNA) in non-Hodgkin's lymphomas: Correlation with working formulation and Kiel classification in formalin-fixed paraffin-embedded material

PCNA is a 36-KD proliferating cell nuclear antigen associated with the cell cycle. The immunocytochemical detection of PCNA represents a useful tool for the study of tumor proliferation activity. This study documents the detection of PCNA, using antibody PC 10 in formalin-fixed, paraffin-embedded tissue, and correlates the proliferative activity of the non-Hodgkin's lymphomas (NHL) with histological grading assessed by the International Working Formulation (WF) and Kiel classification. In 92 cases of NHLs we found a strong correlation between the PCNA index and lymphoma grading. Statistically significant differences were also found between the proliferative index (PI) in low and high grade lymphomas according to the Kiel classification (t = 9.519; p < 0.001) and between low, intermediate and high grade lymphomas according to the WF classification (F = 79.01; p < 0.001). In the Kiel classification the mean of low grade lymphomas was 39.5% and of high grade 75.7%. In the WF the average of low grade lymphomas was 29.7%, intermediate 53.1% and high 75.1%. Although the differences among the groups had been significant, we found variations inside each histological subgroup in both classifications. The intermediate lymphomas were the most heterogeneous group, with PI inside the same histologic subtypes coincident with low and high grade lymphomas. Since PCNA may be used as a marker of cell proliferation in clinical studies to estimate the biological aggressiveness of lymphomas, its determination in intermediate grade NHL could be very useful to evaluate individual cases in this group and determine prognosis and probably the appropriate therapy.

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

Trends in dermatomyositis- and polymyositis-related mortality in the state of Sao Paulo, Brazil, 1985-2007: multiple cause-of-death analysis

Background: Dermatomyositis (DM) and polymyositis (PM) are rare systemic autoimmune rheumatic diseases with high fatality rates. There have been few population-based mortality studies of dermatomyositis and polymyositis in the world, and none have been conducted in Brazil. The objective of the present study was to employ multiple-cause of-death methodology in the analysis of trends in mortality related to dermatomyositis and polymyositis in the state of Sao Paulo, Brazil, between 1985 and 2007. Methods: We analyzed mortality data from the Sao Paulo State Data Analysis System, selecting all death certificates on which DM or PM was listed as a cause of death. The variables sex, age and underlying, associated or total mentions of causes of death were studied using mortality rates, proportions and historical trends. Statistical analysis were performed by chi-square and H Kruskal-Wallis tests, variance analysis and linear regression. A p value less than 0.05 was regarded as significant. Results: Over a 23-year period, there were 318 DM-related deaths and 316 PM-related deaths. Overall, DM/PM was designated as an underlying cause in 55.2% and as an associated cause in 44.8%; among 634 total deaths females accounted for 71.5%. During the study period, age-and gender-adjusted DM mortality rates did not change significantly, although PM as an underlying cause and total mentions of PM trended lower (p < 0.05). The mean ages at death were 47.76 +/- 20.81 years for DM and 54.24 +/- 17.94 years for PM (p = 0.0003). For DM/PM, respectively, as underlying causes, the principal associated causes of death were as follows: pneumonia (in 43.8%/33.5%); respiratory failure (in 34.4%/32.3%); interstitial pulmonary diseases and other pulmonary conditions (in 28.9%/17.6%); and septicemia (in 22.8%/15.9%). For DM/PM, respectively, as associated causes, the following were the principal underlying causes of death: respiratory disorders (in 28.3%/26.0%); circulatory disorders (in 17.4%/20.5%); neoplasms (in 16.7%/13.7%); infectious and parasitic diseases (in 11.6%/9.6%); and gastrointestinal disorders (in 8.0%/4.8%). Of the 318 DM-related deaths, 36 involved neoplasms, compared with 20 of the 316 PM-related deaths (p = 0.03). Conclusions: Our study using multiple cause of deaths found that DM/PM were identified as the underlying cause of death in only 55.2% of the deaths, indicating that both diseases were underestimated in the primary mortality statistics. We observed a predominance of deaths in women and in older individuals, as well as a trend toward stability in the mortality rates. We have confirmed that the risk of death is greater when either disease is accompanied by neoplasm, albeit to lesser degree in individuals with PM. The investigation of the underlying and associated causes of death related to DM/PM broaden the knowledge of the natural history of both diseases and could help integrate mortality data for use in the evaluation of control measures for DM/PM.

Early Complication Rates in a Single-Surgeon Series of 2500 Robotic-Assisted Radical Prostatectomies: Report Applying a Standardized Grading System

Background: Perioperative complications following robotic-assisted radical prostatectomy (RARP) have been previously reported in recent series. Few studies, however, have used standardized systems to classify surgical complications, and that inconsistency has hampered accurate comparisons between different series or surgical approaches. Objective: To assess trends in the incidence and to classify perioperative surgical complications following RARP in 2500 consecutive patients. Design, setting, and participants: We analyzed 2500 patients who underwent RARP for treatment of clinically localized prostate cancer (PCa) from August 2002 to February 2009. Data were prospectively collected in a customized database and retrospectively analyzed. Intervention: All patients underwent RARP performed by a single surgeon. Measurements: The data were collected prospectively in a customized database. Complications were classified using the Clavien grading system. To evaluate trends regarding complications and radiologic anastomotic leaks, we compared eight groups of 300 patients each, categorized according the surgeon`s experience (number of cases). Results and limitations: Our median operative time was 90 min (interquartile range [IQR]: 75-100 min). The median estimated blood loss was 100 ml (IQR: 100-150 ml). Our conversion rate was 0.08%, comprising two procedures converted to standard laparoscopy due to robot malfunction. One hundred and forty complications were observed in 127 patients (5.08%). The following percentages of patients presented graded complications: grade 1, 2.24%; grade 2, 1.8%; grade 3a, 0.08%; grade 3b, 0.48%; grade 4a, 0.40%. There were no cases of multiple organ dysfunction or death (grades 4b and 5). There were significant decreases in the overall complication rates (p = 0.0034) and in the number of anastomotic leaks (p < 0.001) as the surgeon`s experience increased. Conclusions: RARP is a safe option for treatment of clinically localized PCa, presenting low complication rates in experienced hands. Although the robotic system provides the surgeon with enhanced vision and dexterity, proficiency is only accomplished with consistent surgical volume; complication rates demonstrated a tendency to decrease as the surgeon`s experience increased. (C) 2010 European Association of Urology. Published by Elsevier B. V. All rights reserved.