How many molecular subtypes? Implications of the unique tumor principle in personalized medicine

Review Article: The Role of Molecular Pathological Epidemiology in the Study of Neoplastic and Non-neoplastic Diseases in the Era of Precision Medicine

Molecular pathology diagnostics to subclassify diseases based on pathogenesis are increasingly common in clinical translational medicine. Molecular pathological epidemiology (MPE) is an integrative transdisciplinary science based on the unique disease principle and the disease continuum theory. While it has been most commonly applied to research on breast, lung, and colorectal cancers, MPE can investigate etiologic heterogeneity in non-neoplastic diseases, such as cardiovascular diseases, obesity, diabetes mellitus, drug toxicity, and immunity-related and infectious diseases. This science can enhance causal inference by linking putative etiologic factors to specific molecular biomarkers as outcomes. Technological advances increasingly enable analyses of various -omics, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, microbiome, immunomics, interactomics, etc. Challenges in MPE include sample size limitations (depending on availability of biospecimens or biomedical/radiological imaging), need for rigorous validation of molecular assays and study findings, and paucities of interdisciplinary experts, education programs, international forums, and standardized guidelines. To address these challenges, there are ongoing efforts such as multidisciplinary consortium pooling projects, the International Molecular Pathological Epidemiology Meeting Series, and the Strengthening the Reporting of Observational Studies in Epidemiology-MPE guideline project. Efforts should be made to build biorepository and biobank networks, and worldwide population-based MPE databases. These activities match with the purposes of the Big Data to Knowledge (BD2K), Genetic Associations and Mechanisms in Oncology (GAME-ON), and Precision Medicine Initiatives of the United States National Institute of Health. Given advances in biotechnology, bioinformatics, and computational/systems biology, there are wide open opportunities in MPE to contribute to public health.

Four Principles Regarding an Effective Treatment of Aging

The question whether aging is a disease or not, has been asked by many professionals who are involved in the study of age-related degeneration. However, not only an agreement on this remains elusive, but also effective clinical treatments against human aging have not been forthcoming. In this Opinion paper I suggest that the complexity involved in aging is such that we need to remodel our thinking to involve a much more 'systems-oriented' approach. I explore four main principles which should be employed by those who are working on finding treatments against agerelated degeneration. First, I discuss the problems encountered in translating laboratory research into effective therapies for humans. Second, I propose that a 'systems-thinking' method needs to be more extensively employed, instead of relying exclusively on the current reductionist one. Third, it is submitted that we must learn from the history of life-extension research, and not blindly follow contemporary paradigms, which may lead us into yet more 'dead ends' with regards to therapies. Finally, I suggest that, we may need to employ certain universal notions and use these in order to gain insights into the mechanics of a possible therapy against age-related degeneration. Examples may be the principle of hormesis, those of degeneracy, exaptation, and others from cybernetic or systems science domains. By using this four-pronged approach we liberate our thinking from the shackles of existing common mistakes and fallacies, and we open the way for a fresh approach that may lead us towards entirely new paradigms for providing clinically effective therapies against agerelated degeneration.

Challenges and Opportunities in Studying the Epidemiology of Ovarian Cancer Subtypes

PURPOSE OF REVIEW

Only recently has it become clear that epithelial ovarian cancer (EOC) is comprised of such distinct histotypes--with different cells of origin, morphology, molecular features, epidemiologic factors, clinical features, and survival patterns-that they can be thought of as different diseases sharing an anatomical location. Herein, we review opportunities and challenges in studying EOC heterogeneity.

RECENT FINDINGS

The 2014 World Health Organization diagnostic guidelines incorporate accumulated evidence that high- and low-grade serous tumors have different underlying pathogenesis, and that, on the basis of shared molecular features, most high grade tumors, including some previously classified as endometrioid, are now considered to be high-grade serous. At the same time, several studies have reported that high-grade serous EOC, which is the most common histotype, is itself made up of reproducible subtypes discernable by gene expression patterns.

SUMMARY

These major advances in understanding set the stage for a new era of research on EOC risk and clinical outcomes with the potential to reduce morbidity and mortality. We highlight the need for multidisciplinary studies with pathology review using the current guidelines, further molecular characterization of the histotypes and subtypes, inclusion of women of diverse racial/ethnic and socioeconomic backgrounds, and updated epidemiologic and clinical data relevant to current generations of women at risk of EOC.

Challenges and Opportunities in Studying the Epidemiology of Ovarian Cancer Subtypes

Purpose of review

Only recently has it become clear that epithelial ovarian cancer (EOC) is comprised of such distinct histotypes--with different cells of origin, morphology, molecular features, epidemiologic factors, clinical features, and survival patterns-that they can be thought of as different diseases sharing an anatomical location. Herein, we review opportunities and challenges in studying EOC heterogeneity.

Recent findings

The 2014 World Health Organization diagnostic guidelines incorporate accumulated evidence that high- and low-grade serous tumors have different underlying pathogenesis, and that, on the basis of shared molecular features, most high grade tumors, including some previously classified as endometrioid, are now considered to be high-grade serous. At the same time, several studies have reported that high-grade serous EOC, which is the most common histotype, is itself made up of reproducible subtypes discernable by gene expression patterns.

Summary

These major advances in understanding set the stage for a new era of research on EOC risk and clinical outcomes with the potential to reduce morbidity and mortality. We highlight the need for multidisciplinary studies with pathology review using the current guidelines, further molecular characterization of the histotypes and subtypes, inclusion of women of diverse racial/ethnic and socioeconomic backgrounds, and updated epidemiologic and clinical data relevant to current generations of women at risk of EOC.

Heterogeneity Aware Random Forest for Drug Sensitivity Prediction

Samples collected in pharmacogenomics databases typically belong to various cancer types. For designing a drug sensitivity predictive model from such a database, a natural question arises whether a model trained on diverse inter-tumor heterogeneous samples will perform similar to a predictive model that takes into consideration the heterogeneity of the samples in model training and prediction. We explore this hypothesis and observe that ensemble model predictions obtained when cancer type is known out-perform predictions when that information is withheld even when the samples sizes for the former is considerably lower than the combined sample size. To incorporate the heterogeneity idea in the commonly used ensemble based predictive model of Random Forests, we propose Heterogeneity Aware Random Forests (HARF) that assigns weights to the trees based on the category of the sample. We treat heterogeneity as a latent class allocation problem and present a covariate free class allocation approach based on the distribution of leaf nodes of the model ensemble. Applications on CCLE and GDSC databases show that HARF outperforms traditional Random Forest when the average drug responses of cancer types are different.

Challenges and Opportunities in Studying the Epidemiology of Ovarian Cancer Subtypes

PURPOSE OF REVIEW

Only recently has it become clear that epithelial ovarian cancer (EOC) is comprised of such distinct histotypes--with different cells of origin, morphology, molecular features, epidemiologic factors, clinical features, and survival patterns-that they can be thought of as different diseases sharing an anatomical location. Herein, we review opportunities and challenges in studying EOC heterogeneity.

RECENT FINDINGS

The 2014 World Health Organization diagnostic guidelines incorporate accumulated evidence that high- and low-grade serous tumors have different underlying pathogenesis, and that, on the basis of shared molecular features, most high grade tumors, including some previously classified as endometrioid, are now considered to be high-grade serous. At the same time, several studies have reported that high-grade serous EOC, which is the most common histotype, is itself made up of reproducible subtypes discernable by gene expression patterns.

SUMMARY

These major advances in understanding set the stage for a new era of research on EOC risk and clinical outcomes with the potential to reduce morbidity and mortality. We highlight the need for multidisciplinary studies with pathology review using the current guidelines, further molecular characterization of the histotypes and subtypes, inclusion of women of diverse racial/ethnic and socioeconomic backgrounds, and updated epidemiologic and clinical data relevant to current generations of women at risk of EOC.

Towards personalized medicine of colorectal cancer

Efforts in colorectal cancer (CRC) research aim to improve early detection and treatment for metastatic stages which could translate into better prognosis of this disease. One of the major challenges that hinder these efforts is the heterogeneous nature of CRC and involvement of diverse molecular pathways. New large-scale 'omics' technologies are making it possible to generate, analyze and interpret biological data from molecular determinants of CRC. The developments of sophisticated computational analyses would allow information from different omics platforms to be integrated, thus providing new insights into the biology of CRC. Together, these technological advances and an improved mechanistic understanding might allow CRC to be clinically managed at the level of the individual patient. This review provides an account of the current challenges in CRC management and an insight into how new technologies could allow the development of personalized medicine for CRC.

Pooled Clustering of High-Grade Serous Ovarian Cancer Gene Expression Leads to Novel Consensus Subtypes Associated with Survival and Surgical Outcomes

Purpose: Here we assess whether molecular subtyping identifies biological features of tumors that correlate with survival and surgical outcomes of high-grade serous ovarian cancer (HGSOC).Experimental Design: Consensus clustering of pooled mRNA expression data from over 2,000 HGSOC cases was used to define molecular subtypes of HGSOCs. This de novo classification scheme was then applied to 381 Mayo Clinic HGSOC patients with detailed survival and surgical outcome information.Results: Five molecular subtypes of HGSOC were identified. In the pooled dataset, three subtypes were largely concordant with prior studies describing proliferative, mesenchymal, and immunoreactive tumors (concordance > 70%), and the group of tumors previously described as differentiated type was segregated into two new types, one of which (anti-mesenchymal) had downregulation of genes that were typically upregulated in the mesenchymal subtype. Molecular subtypes were significantly associated with overall survival (P < 0.001) and with rate of optimal surgical debulking (≤1 cm, P = 1.9E-4) in the pooled dataset. Among stage III-C or IV Mayo Clinic patients, molecular subtypes were also significantly associated with overall survival (P = 0.001), as well as rate of complete surgical debulking (no residual disease; 16% in mesenchymal tumors compared with >28% in other subtypes; P = 0.02).Conclusions: HGSOC tumors may be categorized into five molecular subtypes that associate with overall survival and the extent of residual disease following debulking surgery. Because mesenchymal tumors may have features that were associated with less favorable surgical outcome, molecular subtyping may have future utility in guiding neoadjuvant treatment decisions for women with HGSOC. Clin Cancer Res; 23(15); 4077-85. ©2017 AACR.

Tumour CD274 (PD-L1) expression and T cells in colorectal cancer

OBJECTIVE

Evidence suggests that CD274 (programmed death-ligand 1, B7-H1) immune checkpoint ligand repress antitumour immunity through its interaction with the PDCD1 (programmed cell death 1, PD-1) receptor of T lymphocytes in various tumours. We hypothesised that tumour CD274 expression levels might be inversely associated with T-cell densities in colorectal carcinoma tissue.

DESIGN

We evaluated tumour CD274 expression by immunohistochemistry in 823 rectal and colon cancer cases within the Nurses' Health Study and Health Professionals Follow-up Study. We conducted multivariable ordinal logistic regression analyses to examine the association of tumour CD274 expression with CD3⁺, CD8⁺, CD45RO (PTPRC)⁺ or FOXP3⁺ cell density in tumour tissue, controlling for potential confounders including tumour status of microsatellite instability (MSI), CpG island methylator phenotype, long interspersed nucleotide element-1 methylation level and KRAS, BRAF and PIK3CA mutations.

RESULTS

CD274 expression in tumour cells or stromal cells (including immune cells) was detected in 731 (89%) or 44 (5%) cases, respectively. Tumour CD274 expression level correlated inversely with FOXP3⁺ cell density in colorectal cancer tissue (outcome) (p_trend=0.0002). For a unit increase in outcome quartile categories, multivariable OR in the highest (vs lowest) CD274 expression score was 0.22 (95% CI 0.10 to 0.47). Tumour CD274 expression was inversely associated with MSI-high status (p=0.001). CD274 expression was not significantly associated with CD3⁺, CD8⁺ or CD45RO⁺ cell density, pathological lymphocytic reactions or patient survival prognosis.

CONCLUSIONS

Tumour CD274 expression is inversely associated with FOXP3⁺ cell density in colorectal cancer tissue, suggesting a possible influence of CD274-expressing carcinoma cells on regulatory T cells in the tumour microenvironment.

Statin use, candidate mevalonate pathway biomarkers, and colon cancer survival in a population-based cohort study

BACKGROUND

Statin use after colorectal cancer diagnosis may improve survival but evidence from observational studies is conflicting. The anti-cancer effect of statins may be restricted to certain molecular subgroups. In this population-based cohort study, the interaction between p53 and 3-hydroxy-3-methylglutaryl coenzyme-A reductase (HMGCR) expression, KRAS mutations, and the association between statin use and colon cancer survival was assessed.

METHODS

The cohort consisted of 740 stage II and III colon cancer patients diagnosed between 2004 and 2008. Statin use was determined through clinical note review. Tissue blocks were retrieved to determine immunohistochemical expression of p53 and HMGCR in tissue microarrays and the presence of KRAS mutations in extracted DNA. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for colorectal cancer-specific and overall survival.

RESULTS

Statin use was not associated with improved cancer-specific survival in this cohort (HR=0.91, 95% CI 0.64-1.28). Statin use was also not associated with improved survival when the analyses were stratified by tumour p53 (wild-type HR=1.31, 95% CI 0.67-2.56 vs aberrant HR=0.80, 95% CI 0.52-1.24), HMGCR (HMGCR-high HR=0.69, 95% CI 0.40-1.18 vs HMGCR-low HR=1.10, 95% CI 0.66-1.84), and KRAS (wild-type HR=0.73, 95% CI 0.44-1.19 vs mutant HR=1.21, 95% CI 0.70-2.21) status.

CONCLUSIONS

Statin use was not associated with improved survival either independently or when stratified by potential mevalonate pathway biomarkers in this population-based cohort of colon cancer patients.

Staphylococcus aureus in the Intensive Care Unit: Are These Golden Grapes Ripe for a New Approach?

Staphylococcus aureus is the leading cause of infection in the setting of critical illness and injury. This pathogen causes life-threatening infection in otherwise healthy individuals and also complicates the clinical course of patients requiring intensive care as a result of their primary medical or surgical disease processes. S. aureus infection in the intensive care unit (ICU) most commonly manifests as sepsis, ventilator-associated pneumonia, and infection of surgical sites and indwelling medical devices. With the epidemic spread of methicillin-resistant S. aureus, many cases of staphylococcal infection in the ICU are now classified as drug resistant, prompting hospital-based screening for methicillin-resistant S. aureus and implementation of both isolation practices and decolonization strategies in ICU patients. The genetic adaptability of S. aureus, heterogeneity of disease presentation, clinical course, and outcome between individual S. aureus-infected ICU patients remains enigmatic, suggesting a need to define disease classification subtypes that inform disease progression and therapy. We propose that S. aureus infection in the ICU now presents a unique opportunity for individualized risk stratification coupled with the investigation of novel approaches to mitigate disease. Given our increasing knowledge of the molecular pathogenesis of S. aureus disease, we suggest that the application of molecular pathological epidemiology to S. aureus infection can usher in a new era of highly focused personalized therapy that may be particularly beneficial in the setting of critical illness and injury.

Pooled Clustering of High-Grade Serous Ovarian Cancer Gene Expression Leads to Novel Consensus Subtypes Associated with Survival and Surgical Outcomes

Purpose: Here we assess whether molecular subtyping identifies biological features of tumors that correlate with survival and surgical outcomes of high-grade serous ovarian cancer (HGSOC).Experimental Design: Consensus clustering of pooled mRNA expression data from over 2,000 HGSOC cases was used to define molecular subtypes of HGSOCs. This de novo classification scheme was then applied to 381 Mayo Clinic HGSOC patients with detailed survival and surgical outcome information.Results: Five molecular subtypes of HGSOC were identified. In the pooled dataset, three subtypes were largely concordant with prior studies describing proliferative, mesenchymal, and immunoreactive tumors (concordance > 70%), and the group of tumors previously described as differentiated type was segregated into two new types, one of which (anti-mesenchymal) had downregulation of genes that were typically upregulated in the mesenchymal subtype. Molecular subtypes were significantly associated with overall survival (P < 0.001) and with rate of optimal surgical debulking (≤1 cm, P = 1.9E-4) in the pooled dataset. Among stage III-C or IV Mayo Clinic patients, molecular subtypes were also significantly associated with overall survival (P = 0.001), as well as rate of complete surgical debulking (no residual disease; 16% in mesenchymal tumors compared with >28% in other subtypes; P = 0.02).Conclusions: HGSOC tumors may be categorized into five molecular subtypes that associate with overall survival and the extent of residual disease following debulking surgery. Because mesenchymal tumors may have features that were associated with less favorable surgical outcome, molecular subtyping may have future utility in guiding neoadjuvant treatment decisions for women with HGSOC. Clin Cancer Res; 23(15); 4077-85. ©2017 AACR.

Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis

Molecular pathological epidemiology (MPE) is an integrative field that utilizes molecular pathology to incorporate interpersonal heterogeneity of a disease process into epidemiology. In each individual, the development and progression of a disease are determined by a unique combination of exogenous and endogenous factors, resulting in different molecular and pathological subtypes of the disease. Based on "the unique disease principle," the primary aim of MPE is to uncover an interactive relationship between a specific environmental exposure and disease subtypes in determining disease incidence and mortality. This MPE approach can provide etiologic and pathogenic insights, potentially contributing to precision medicine for personalized prevention and treatment. Although breast, prostate, lung, and colorectal cancers have been among the most commonly studied diseases, the MPE approach can be used to study any disease. In addition to molecular features, host immune status and microbiome profile likely affect a disease process, and thus serve as informative biomarkers. As such, further integration of several disciplines into MPE has been achieved (e.g., pharmaco-MPE, immuno-MPE, and microbial MPE), to provide novel insights into underlying etiologic mechanisms. With the advent of high-throughput sequencing technologies, available genomic and epigenomic data have expanded dramatically. The MPE approach can also provide a specific risk estimate for each disease subgroup, thereby enhancing the impact of genome-wide association studies on public health. In this article, we present recent progress of MPE, and discuss the importance of accounting for the disease heterogeneity in the era of big-data health science and precision medicine.

Significant Prognostic Features and Patterns of Somatic TP53 Mutations in Human Cancers

TP53 is the most frequently altered gene in human cancers. Numerous retrospective studies have related its mutation and abnormal p53 protein expression to poor patient survival. Nonetheless, the clinical significance of TP53 (p53) status has been a controversial issue. In this work, we aimed to characterize TP53 somatic mutations in tumor cells across multiple cancer types, primarily focusing on several less investigated features of the mutation spectra, and determine their prognostic implications. We performed an integrative study on the clinically annotated genomic data released by The Cancer Genome Atlas. Standard statistical methods, such as the Cox proportional hazards model and logistic regression, were used. This study resulted in several novel findings. They include the following: (1) similar to previously reported cases in breast cancer, the mutations in exons 1 to 4 of TP53 were more lethal than those in exons 5 to 9 for the patients with lung adenocarcinomas; (2) TP53 mutants tended to be negatively selected in mammalian evolution, but the evolutionary conservation had various clinical implications for different cancers; (3) conserved correlation patterns (ie, consistent co-occurrence or consistent mutual exclusivity) between TP53 mutations and the alterations in several other cancer genes (ie, PIK3CA, PTEN, KRAS, APC, CDKN2A, and ATM) were present in several cancers in which prognosis was associated with TP53 status and/or the mutational characteristics; (4) among TP53-mutated tumors, the total mutation burden in other driver genes was a predictive signature (P < .05, false discovery rate <0.11) for better patient survival outcome in several cancer types, including glioblastoma multiforme. Among these findings, the fourth is of special significance as it suggested the potential existence of epistatic interaction effects among the mutations in different cancer driver genes on clinical outcomes.

Specific mutations in KRAS codon 12 are associated with worse overall survival in patients with advanced and recurrent colorectal cancer

Background:

Activating mutations in KRAS have been suggested as potential predictive and prognostic biomarkers. However, the prognostic impact of specific point mutations remains less clear. This study assessed the prognostic impact of specific KRAS mutations on survival for patients with colorectal cancer.

Methods:

Retrospective review of patients KRAS typed for advanced and recurrent colorectal cancer between 2010 and 2015 in a UK Cancer Network.

Results:

We evaluated the impact of KRAS genotype in 392 patients. Mutated KRAS was detected in 42.9% of tumours. KRAS mutations were more common in moderate vs well-differentiated tumours. On multivariate analysis, primary tumour T stage (HR 2.77 (1.54–4.98), P=0.001), N stage (HR 1.51 (1.01–2.26), P=0.04), curative intent surgery (HR 0.51 (0.34–0.76), P=0.001), tumour grade (HR 0.44 (0.30–0.65), P=0.001) and KRAS mutation (1.54 (1.23–2.12), P=0.005) were all predictive of overall survival. Patients with KRAS codon 12 mutations had worse overall survival (HR 1.76 (95% CI 1.27–2.43), P=0.001). Among the five most common codon 12 mutations, only p.G12C (HR 2.21 (1.15–4.25), P=0.01) and p.G12V (HR 1.69 (1.08–2.62), P=0.02) were predictive of overall survival.

Conclusions:

For patients with colorectal cancer, p.G12C and p.G12V mutations in codon 12 were independently associated with worse overall survival after diagnosis.

Tumor SQSTM1 (p62) expression and T cells in colorectal cancer

Evidence suggests that activation of autophagy in neoplastic cells potentiates antitumor immunity through cross-presentation of tumor-associated antigens to T cells and release of immune mediators. The SQSTM1 (sequestosome 1, p62) protein is degraded by activated autophagy, and might enhance immune response to tumor cells. We hypothesized that tumor SQSTM1 expression level might be inversely associated with T-cell densities in colorectal carcinoma tissue. We evaluated tumor SQSTM1 expression by immunohistochemistry in 601 rectal and colon cancer cases within the Nurses' Health Study and Health Professionals Follow-up Study. Ordinal logistic regression analyses were conducted to assess the association of tumor SQSTM1 expression with CD3⁺, CD8⁺, CD45RO (PTPRC)⁺, or FOXP3⁺ cell density in tumor tissue, controlling for potential confounders, including tumor status of microsatellite instability, CpG island methylator phenotype, long interspersed nucleotide element-1 methylation level, and KRAS, BRAF, and PIK3CA mutations. Tumor SQSTM1 expression level was inversely associated with FOXP3⁺ cell density (p_trend = 0.006), but not with CD3⁺, CD8⁺, or CD45RO⁺ cell density (with the adjusted α level of 0.01 for multiple hypothesis testing). For a unit increase in quartile categories of FOXP3⁺ cell density, multivariable odds ratios were 0.66 [95% confidence interval (CI), 0.45-0.98] for intermediate-level SQSTM1 expression, and 0.55 (95% CI, 0.36-0.83) for high-level SQSTM1 expression, compared with low-level SQSTM1 expression. Tumor SQSTM1 expression is inversely associated with FOXP3⁺ cell density in colorectal cancer tissue, suggesting a possible role of SQSTM1-expressing carcinoma cells on regulatory T cells in the tumor microenvironment.

European healthcare systems readiness to shift from ‘one-size fits all’ to personalized medicine

Personalized medicine (PM) is no longer an abstract healthcare approach. It has become a reality over the last years and is already successfully applied in the various medical fields. Although there are success stories of implementing PM, there are still many more opportunities to further implement and make full use of the potential of PM. We assessed the system readiness of healthcare systems in Europe to shift from the predominant ‘one size fits all’ healthcare approach to PM. We conclude that European healthcare systems are only partially ready for PM. Key challenges such as integration of big data, health literacy, reimbursement and regulatory issues need to be overcome in order to strengthen the implementation and uptake of PM.

Cancer prevention in the era of precision oncology

Cancer is a highly heterogeneous disease, both between and within different target organs. Precision cancer prevention requires understanding the molecular pathways leading to cancer on a "per-person" level, identification of individuals most at risk for developing cancer, and tailoring interventions to accommodate pathogenesis, risk, and individual responses to interventions. This commentary will discuss how an investment in precision prevention research can accelerate cancer prevention agent development-the key to reducing cancer incidence and mortality.

Personalized in vitro cancer models to predict therapeutic response: Challenges and a framework for improvement

Personalized cancer therapy focuses on characterizing the relevant phenotypes of the patient, as well as the patient's tumor, to predict the most effective cancer therapy. Historically, these methods have not proven predictive in regards to predicting therapeutic response. Emerging culture platforms are designed to better recapitulate the in vivo environment, thus, there is renewed interest in integrating patient samples into in vitro cancer models to assess therapeutic response. Successful examples of translating in vitro response to clinical relevance are limited due to issues with patient sample acquisition, variability and culture. We will review traditional and emerging in vitro models for personalized medicine, focusing on the technologies, microenvironmental components, and readouts utilized. We will then offer our perspective on how to apply a framework derived from toxicology and ecology towards designing improved personalized in vitro models of cancer. The framework serves as a tool for identifying optimal readouts and culture conditions, thus maximizing the information gained from each patient sample.

Discretization of Gene Expression Data Unmasks Molecular Subgroups Recurring in Different Human Cancer Types

Despite the individually different molecular alterations in tumors, the malignancy associated biological traits are strikingly similar. Results of a previous study using renal cell carcinoma (RCC) as a model pointed towards cancer-related features, which could be visualized as three groups by microarray based gene expression analysis. In this study, we used a mathematic model to verify the presence of these groups in RCC as well as in other cancer types. We developed an algorithm for gene-expression deviation profiling for analyzing gene expression data of a total of 8397 patients with 13 different cancer types and normal tissues. We revealed three common Cancer Transcriptomic Profiles (CTPs) which recurred in all investigated tumors. Additionally, CTPs remained robust regardless of the functions or numbers of genes analyzed. CTPs may represent common genetic fingerprints, which potentially reflect the closely related biological traits of human cancers.

Systematic pan-cancer analysis of tumour purity

The tumour microenvironment is the non-cancerous cells present in and around a tumour, including mainly immune cells, but also fibroblasts and cells that comprise supporting blood vessels. These non-cancerous components of the tumour may play an important role in cancer biology. They also have a strong influence on the genomic analysis of tumour samples, and may alter the biological interpretation of results. Here we present a systematic analysis using different measurement modalities of tumour purity in >10,000 samples across 21 cancer types from the Cancer Genome Atlas. Patients are stratified according to clinical features in an attempt to detect clinical differences driven by purity levels. We demonstrate the confounding effect of tumour purity on correlating and clustering tumours with transcriptomics data. Finally, using a differential expression method that accounts for tumour purity, we find an immunotherapy gene signature in several cancer types that is not detected by traditional differential expression analyses.

The importance of the tumour microenvironment has now been realised, however the presence of non-tumour cells in cancer samples can complicate genomic analyses. Here, the authors estimate tumour purity in 10,000 samples from the TCGA dataset and can detect a signature of T cell activation.

Integration of molecular pathology, epidemiology and social science for global precision medicine

The precision medicine concept and the unique disease principle imply that each patient has unique pathogenic processes resulting from heterogeneous cellular genetic and epigenetic alterations and interactions between cells (including immune cells) and exposures, including dietary, environmental, microbial and lifestyle factors. As a core method field in population health science and medicine, epidemiology is a growing scientific discipline that can analyze disease risk factors and develop statistical methodologies to maximize utilization of big data on populations and disease pathology. The evolving transdisciplinary field of molecular pathological epidemiology (MPE) can advance biomedical and health research by linking exposures to molecular pathologic signatures, enhancing causal inference and identifying potential biomarkers for clinical impact. The MPE approach can be applied to any diseases, although it has been most commonly used in neoplastic diseases (including breast, lung and colorectal cancers) because of availability of various molecular diagnostic tests. However, use of state-of-the-art genomic, epigenomic and other omic technologies and expensive drugs in modern healthcare systems increases racial, ethnic and socioeconomic disparities. To address this, we propose to integrate molecular pathology, epidemiology and social science. Social epidemiology integrates the latter two fields. The integrative social MPE model can embrace sociology, economics and precision medicine, address global health disparities and inequalities, and elucidate biological effects of social environments, behaviors and networks. We foresee advancements of molecular medicine, including molecular diagnostics, biomedical imaging and targeted therapeutics, which should benefit individuals in a global population, by means of an interdisciplinary approach of integrative MPE and social health science.

Association Between Specific Mutations in KRAS Codon 12 and Colorectal Liver Metastasis

IMPORTANCE

Currently, one of the most commonly available biomarkers in the treatment of patients with colorectal liver metastases (CRLM) is the Kirsten rat sarcoma viral oncogene homolog (KRAS); however, the prognostic implications of specific mutations of the KRAS gene are still not well defined.

OBJECTIVE

To investigate the prognostic impact of specific KRAS mutations on patients undergoing liver resection for CRLM.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective single-center study was conducted from January 1, 2003, to December 31, 2013. Data about specific KRAS mutations for 331 patients who underwent hepatic resection for CRLM at Johns Hopkins Hospital between 2003 and 2013 were analyzed. Clinicopathological characteristics, perioperative details, and outcomes were stratified by specific KRAS mutation at codons 12 and 13.

INTERVENTION

Resection of CRLM.

MAIN OUTCOMES AND MEASURES

Overall survival (OS) and recurrence-free survival.

RESULTS

A mutated KRAS (mtKRAS) was identified in 91 patients (27.5%). At a median follow-up of 27.4 months, recurrence was observed in 48 patients (52.7%) with mtKRAS and 130 patients (54.2%) with wild-type KRAS (wtKRAS) (P = .82). Median and 5-year survival among patients with mtKRAS was 32.4 months and 32.7%, respectively, vs 58.5 months and 46.9%, respectively, for patients with wtKRAS (P = .02). Patients with KRAS codon 12 mutations had worse OS (hazard ratio [HR], 1.54; 95% CI, 1.05-2.27; P = .03) vs those with wtKRAS, whereas a KRAS codon 13 mutation was not associated with prognosis (HR, 1.47; 95% CI, 0.83-2.62; P = .19). Among the 6 most common mutations in codons 12 and 13, only G12V (HR, 1.78; 95% CI, 1.00-3.17; P = .05) and G12S (HR, 3.33; 95% CI, 1.22-9.10; P = .02) were associated with worse OS compared with patients with wtKRAS (both P < .05). Among patients who recurred, G12V (HR, 2.96; 95% CI, 1.32-6.61; P = .01), G12C (HR, 6.74; 95% CI, 2.05-22.2; P = .002), and G12S mutations (HR, 4.91; 95% CI, 1.52-15.8; P = .01) were associated with worse OS (both P < .05).

CONCLUSIONS AND RELEVANCE

G12V and G12S mutations of codon 12 were independent prognostic factors of worse OS. Among patients who recurred after resection of CRLM, G12V, G12C, and G12S mutations were associated with worse OS. Information on specific KRAS mutations may help individualize therapeutic and surveillance strategies for patients with resected CRLM.

Prediagnosis Plasma Adiponectin in Relation to Colorectal Cancer Risk According to KRAS Mutation Status

BACKGROUND

Low levels of adiponectin (ADIPOQ; HGNC ID; HGNC:13633), an adipokine, are associated with obesity, adiposity, excess energy balance, and increased risk of colorectal neoplasia. Given the reported association of increased body mass index (BMI) and low-level physical activity with KRAS-mutated colorectal tumor, we hypothesized that low-level plasma adiponectin might be associated with increased risk of KRAS-mutant colorectal carcinoma but not with risk of KRAS wild-type carcinoma.

METHODS

We conducted molecular pathological epidemiology research using a nested case-control study design (307 incident rectal and colon cancer case patients and 593 matched control individuals) within prospective cohort studies, the Nurses' Health Study (152 case patients and 297 control individuals, with blood collection in 1989-1990) and the Health Professionals Follow-up Study (155 case patients and 296 control individuals, with blood collection in 1993-1995). Multivariable conditional logistic regression models and two-sided likelihood ratio tests were used to assess etiologic heterogeneity of the associations.

RESULTS

The association of low-level plasma adiponectin with colorectal cancer risk statistically significantly differed by KRAS mutation status (P heterogeneity = .004). Low levels of plasma adiponectin were associated with KRAS-mutant colorectal cancer (for the lowest vs highest tertile: multivariable odds ratio [OR] = 2.83, 95% confidence interval [CI] = 1.50 to 5.34, P trend = .002) but not with KRAS wild-type cancer (for the lowest vs highest tertile: multivariable OR = 0.83, 95% CI = 0.49 to 1.43, P trend = .48). In secondary analyses, the association between plasma adiponectin and colorectal cancer did not appreciably differ by BRAF or PIK3CA oncogene mutation status.

CONCLUSIONS

Low-level plasma adiponectin is associated with KRAS-mutant colorectal cancer risk but not with KRAS wild-type cancer risk.

Survival Benefit of Exercise Differs by Tumor IRS1 Expression Status in Colorectal Cancer

BACKGROUND

High-level physical activity is associated with lower colorectal cancer (CRC) mortality, likely through insulin sensitization. Insulin receptor substrate 1 (IRS1) is a mediator of insulin and insulin-like growth factor (IGF) signaling pathways, and its down-regulation is associated with insulin resistance. Therefore, we hypothesized that tumor IRS1 expression status might modify cellular sensitivity to insulin and IGF, and the prognostic association of physical activity.

METHODS

We assessed IRS1 expression level in 371 stage I-III rectal and colon cancers in the Nurses' Health Study and the Health Professionals Follow-up Study by immunohistochemistry. In survival analysis, Cox proportional hazards model was used to assess an interaction between post-diagnosis physical activity (ordinal scale of sex-specific quartiles Q1 to Q4) and IRS1 expression (ordinal scale of negative, low, and high), controlling for potential confounders, including microsatellite instability, CpG island methylator phenotype, long interspersed nucleotide element-1 (LINE-1) methylation level, and KRAS, BRAF, and PIK3CA mutation status.

RESULTS

There was a statistically significant interaction between post-diagnosis physical activity and tumor IRS1 expression in CRC-specific mortality analysis (P interaction = 0.005). Multivariable hazard ratio (95% confidence interval) for higher post-diagnosis physical activity (Q3-Q4 vs. Q1-Q2) was 0.15 (0.02-1.38) in the IRS1-negative group, 0.45 (0.19-1.03) in the IRS1-low group, and 1.32 (0.50-3.53) in the IRS1-high group.

CONCLUSIONS

The association of post-diagnosis physical activity with colorectal carcinoma patient survival may differ by tumor IRS1 expression level. If validated, tumor IRS1 expression status may serve as a predictive marker to identify subgroups of patients who might gain greater survival benefit from an increased level of exercise.

Colorectal Cancers with the Uncommon Findings of KRAS Mutation and Microsatellite Instability

Sporadic colorectal cancers with microsatellite instability (MSI) frequently contain a mutation of the BRAF gene. Additionally, it has been shown that BRAF mutations in colorectal cancers are mutually exclusive of KRAS mutation. We evaluated 14 cases of colorectal cancer with MSI that were BRAF wild type but demonstrated a KRAS mutation. The codon 12/13 region in exon 2 of the KRAS oncogene and the codon 600 region in exon 15 of the BRAF gene were analyzed with standard PCR methods. MSI was evaluated by using the Bethesda panel of markers. The methylation status of the mismatch repair system was ascertained using the SALSA(®) MS-MLPA(®) methylation-specific DNA detection. The mismatch repair proteins MLH1, MSH2, MSH6, and PMS2 were evaluated by immunohistochemical staining. A total of 530 colorectal cancers were studied for MSI and KRAS gene mutation. Fourteen (2.6%) cancers with both MSI and a KRAS mutation were identified, and all cancers were BRAF wild type. Methylation was present in 7 (50%), 5 demonstrated methylation of MLH1, 1 showed methylation of MGMT, and 1 showed methylation of MSH2. Four patients had simultaneous cancers, some of which showed different genetic changes. Immunohistochemical staining suggested a germ line mutation for 4 of 10 cases with complete staining information. KRAS mutation may occur with MSI in colorectal cancers with wild-type BRAF. If a mutation in KRAS co-exists with MSI, then strong methylation of the MLH1 gene is unlikely. These tumors demonstrate that a small number of colorectal cancers will develop with atypical patterns of molecular genetic changes, suggesting that a specific pattern of genetic changes may not be as crucial as the overall accumulation of changes, consistent with the 'unique tumor principle'.

Cancer classification in the genomic era: five contemporary problems

Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., “lung cancer” designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification and the successful application of these concepts in precision medicine.

Expression of TP53, BCL-2, and VEGFA Genes in Esophagus Carcinoma and its Biological Significance

BACKGROUND

The pathogenesis of esophagus carcinoma involves a cascade process consisting of multiple factors and accumulation of gene mutations. It is known that vascular endothelial growth factor (VEGF) mainly regulates de novo vascular formation while B-cell lymphoma-2 (BCL-2) gene exerts a tumor-suppressing effect. The prominent expression of VEGFA and BCL-2 genes, along with the most famous tumor-suppressor gene, TP53, raise the possibly of gene interaction. This study therefore investigated the effect and correlation of TP53, BCL-2, and VEGFA genes on cell proliferation and apoptosis of esophagus carcinoma.

MATERIAL AND METHODS

A total of 30 male rats were prepared by subcutaneous injection of methyl-benzyl-nitrosamine (MBNA) to induce esophagus cancer, along with 30 controlled rats which received saline instead. After 4, 10, 20, or 30 weeks, rats were sacrificed to observe the morphological changes of esophageal mucosa. Cell apoptosis was quantified by terminal deoxynucleotidyl transferase-mediated dUTP nick-end-labeling (TUNEL) assay. Immunohistochemical (IHC) staining was employed to examine the expression of TP53, BCL-2 and VEGFA genes.

RESULTS

With the progression of cancer, pathological damages of esophageal tissue aggravated while the cancer cell apoptosis gradually decreased compared to controlled animals. Protein levels of p53, Bcl-2, and VEGF in the model group were significantly elevated at each time point. Positive correlations existed between p53 and Bcl-2 or VEGF.

CONCLUSIONS

Abnormally elevated expression of TP53, BCL-2, and VEGFA genes may participate in the proliferation of esophagus cancer cells in a synergistic manner.

A Meta-Regression Method for Studying Etiological Heterogeneity Across Disease Subtypes Classified by Multiple Biomarkers

In interdisciplinary biomedical, epidemiologic, and population research, it is increasingly necessary to consider pathogenesis and inherent heterogeneity of any given health condition and outcome. As the unique disease principle implies, no single biomarker can perfectly define disease subtypes. The complex nature of molecular pathology and biology necessitates biostatistical methodologies to simultaneously analyze multiple biomarkers and subtypes. To analyze and test for heterogeneity hypotheses across subtypes defined by multiple categorical and/or ordinal markers, we developed a meta-regression method that can utilize existing statistical software for mixed-model analysis. This method can be used to assess whether the exposure-subtype associations are different across subtypes defined by 1 marker while controlling for other markers and to evaluate whether the difference in exposure-subtype association across subtypes defined by 1 marker depends on any other markers. To illustrate this method in molecular pathological epidemiology research, we examined the associations between smoking status and colorectal cancer subtypes defined by 3 correlated tumor molecular characteristics (CpG island methylator phenotype, microsatellite instability, and the B-Raf protooncogene, serine/threonine kinase (BRAF), mutation) in the Nurses' Health Study (1980-2010) and the Health Professionals Follow-up Study (1986-2010). This method can be widely useful as molecular diagnostics and genomic technologies become routine in clinical medicine and public health.

Potential of epigenetic therapies in the management of solid tumors

Cancer is a complex disease with both genetic and epigenetic origins. The growing field of epigenetics has contributed to our understanding of oncogenesis and tumor progression, and has allowed the development of novel therapeutic drugs. First-generation epigenetic inhibitor drugs have obtained modest clinical results in two types of hematological malignancy. Second-generation epigenetic inhibitors are in development, and have intrinsically greater selectivity for their molecular targets. Solid tumors are more genetic and epigenetically complex than hematological malignancies, but the transcriptome and epigenome biomarkers have been identified for many of these malignancies. This solid tumor molecular aberration profile may be modified using specific or quasi-specific epidrugs together with conventional and innovative anticancer treatments. In this critical review, we briefly analyze the strategies to select the targeted epigenetic changes, enumerate the second-generation epigenetic inhibitors, and describe the main signs indicating the potential of epigenetic therapies in the management of solid tumors. We also highlight the work of consortia or academic organizations that support the undertaking of human epigenetic therapeutic projects as well as some examples of transcriptome/epigenome profile determination in clinical assessment of cancer patients treated with epidrugs. There is a good chance that epigenetic therapies will be able to be used in patients with solid tumors in the future. This may happen soon through collaboration of diverse scientific groups, making the selection of targeted epigenetic aberration(s) more rapid, the design and probe of drug candidates, accelerating in vitro and in vivo assays, and undertaking new cancer epigenetic-therapy clinical trails.

Inhibition of Topoisomerase (DNA) I (TOP1): DNA Damage Repair and Anticancer Therapy

Most chemotherapy regimens contain at least one DNA-damaging agent that preferentially affects the growth of cancer cells. This strategy takes advantage of the differences in cell proliferation between normal and cancer cells. Chemotherapeutic drugs are usually designed to target rapid-dividing cells because sustained proliferation is a common feature of cancer [1,2]. Rapid DNA replication is essential for highly proliferative cells, thus blocking of DNA replication will create numerous mutations and/or chromosome rearrangements—ultimately triggering cell death [3]. Along these lines, DNA topoisomerase inhibitors are of great interest because they help to maintain strand breaks generated by topoisomerases during replication. In this article, we discuss the characteristics of topoisomerase (DNA) I (TOP1) and its inhibitors, as well as the underlying DNA repair pathways and the use of TOP1 inhibitors in cancer therapy.

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.

Hormone receptor-independent CXCL10 production is associated with the regulation of cellular factors linked to breast cancer progression and metastasis

Breast cancer (BC) is a major health problem for women around the world. Although advances in the field of molecular therapy have been achieved, the successful therapeutic management of BC, particularly metastatic disease, remains a challenge for patients and clinicians. One of the areas of current investigation is the circulating tumor cells (CTCs), which have a determinant role in the development of distant metastasis. At the present, many of the available treatment strategies for metastatic disease are of limited benefit. However, the elucidation of the mechanisms of tumor progression and metastasis may help to identify key molecules/components that may function as therapeutic targets in the future. In the present study, the functional analysis of CTCs revealed their ability to grow and proliferate to form colonies. Immunofluorescence staining of the CTCs' colonies exhibits elevated expression of cell growth and survival associated proteins such as, survivin, ERK and Akt1. More importantly, the functional screening of the chemokine profile in BC patients' sera revealed an HR-independent elevation of the chemokine CXCL10 when compared to healthy controls. The analysis of chemokines CXCL9 and CXCL11 demonstrated an HR-dependent production pattern. The levels of both CXCL9 and CXCL11 were markedly high in HR+ patients' sera when compared to HR- patients and healthy controls. The functional analysis of HR+ and HR- BC derived cell lines when cultivated in media supplemented with patients' sera demonstrated the alteration of tumor progression and metastasis related proteins. We noted the induction of survivin, β-catenin, MKP-1, pERK, CXCR4 and MMP-1 both at the protein and mRNA levels. The induction of those proteins was in keeping with patients' sera induced cell proliferation as measured by the MTT assay. In conclusion, our data emphasizes the role of chemokines, especially CXCL10, in BC progression and metastasis via the induction of signaling pathways, which mainly involve survivin, β-catenin, MKP-1 and MMP-1.

BRAF-mutated colorectal cancer: clinical implications for a distinct subset of the disease

SUMMARY 

Colorectal cancer (CRC) is many diseases, with each case defined by the underlying genetic and molecular changes of that particular tumor. The heterogeneity of CRC emphasizes the need to understand this disease within the context of genetic subsets. BRAF mutations mark a subpopulation that arises through the serrated pathway to carcinogenesis. This subset of cancers is associated with unique clinical and histopathologic characteristics. BRAF-mutated CRCs have a worse prognosis compared with their wild-type counterparts, and may not be as responsive to chemotherapy. Target therapies specifically against BRAF and its related signaling pathways are under both scientific and clinical investigation. This article highlights the clinical relevance of the subset of BRAF-mutated CRCs.

Personalized radiotherapy: concepts, biomarkers and trial design

In the past decade, and pointing onwards to the immediate future, clinical radiotherapy has undergone considerable developments, essentially including technological advances to sculpt radiation delivery, the demonstration of the benefit of adding concomitant cytotoxic agents to radiotherapy for a range of tumour types and, intriguingly, the increasing integration of targeted therapeutics for biological optimization of radiation effects. Recent molecular and imaging insights into radiobiology will provide a unique opportunity for rational patient treatment, enabling the parallel design of next-generation trials that formally examine the therapeutic outcome of adding targeted drugs to radiation, together with the critically important assessment of radiation volume and dose-limiting treatment toxicities. In considering the use of systemic agents with presumed radiosensitizing activity, this may also include the identification of molecular, metabolic and imaging markers of treatment response and tolerability, and will need particular attention on patient eligibility. In addition to providing an overview of clinical biomarker studies relevant for personalized radiotherapy, this communication will highlight principles in addressing clinical evaluation of combined-modality-targeted therapeutics and radiation. The increasing number of translational studies that bridge large-scale omics sciences with quality-assured phenomics end points-given the imperative development of open-source data repositories to allow investigators the access to the complex data sets-will enable radiation oncology to continue to position itself with the highest level of evidence within existing clinical practice.

Proceedings of the second international molecular pathological epidemiology (MPE) meeting

Disease classification system increasingly incorporates information on pathogenic mechanisms to predict clinical outcomes and response to therapy and intervention. Technological advancements to interrogate omics (genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, interactomics, etc.) provide widely open opportunities in population-based research. Molecular pathological epidemiology (MPE) represents integrative science of molecular pathology and epidemiology. This unified paradigm requires multidisciplinary collaboration between pathology, epidemiology, biostatistics, bioinformatics, and computational biology. Integration of these fields enables better understanding of etiologic heterogeneity, disease continuum, causal inference, and the impact of environment, diet, lifestyle, host factors (including genetics and immunity), and their interactions on disease evolution. Hence, the Second International MPE Meeting was held in Boston in December 2014, with aims to: (1) develop conceptual and practical frameworks; (2) cultivate and expand opportunities; (3) address challenges; and (4) initiate the effort of specifying guidelines for MPE. The meeting mainly consisted of presentations of method developments and recent data in various malignant neoplasms and tumors (breast, prostate, ovarian and colorectal cancers, renal cell carcinoma, lymphoma, and leukemia), followed by open discussion sessions on challenges and future plans. In particular, we recognized need for efforts to further develop statistical methodologies. This meeting provided an unprecedented opportunity for interdisciplinary collaboration, consistent with the purposes of the Big Data to Knowledge, Genetic Associations and Mechanisms in Oncology, and Precision Medicine Initiative of the US National Institute of Health. The MPE meeting series can help advance transdisciplinary population science and optimize training and education systems for twenty-first century medicine and public health.

Tumor phosphatidylinositol 3-kinase signaling in therapy resistance and metastatic dissemination of rectal cancer: opportunities for signaling-adapted therapies

Locally advanced rectal cancer (LARC) comprises heterogeneous tumors with predominant hypoxic components, a hallmark of the tumor microenvironment and determinant of resistance to cytotoxic therapies, local recurrence, and metastatic progression. A rational integration of molecularly targeted agents in established combined-modality treatment regimens may improve local and systemic disease control, but will require a clear definition of functional biomarkers for patient stratification. In a prospective study of LARC patients given neoadjuvant chemotherapy and radiation, we applied a kinase substrate array technology to analyze the patients' tumor biopsies sampled at the time of diagnosis, and observed that receptor tyrosine kinase activities integrated by high phosphatidylinositol 3-kinase signaling were correlated both with poor tumor response to the neoadjuvant treatment and adverse progression-free survival. Conceptually, the specific tumor signature of phosphatidylinositol 3-kinase signaling activity may point to actionable therapy targets in LARC patients with unfavorable disease features. Clinical trial registration number NCT00278694.

Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression

The term 'field effect' (also known as field defect, field cancerization, or field carcinogenesis) has been used to describe a field of cellular and molecular alteration, which predisposes to the development of neoplasms within that territory. We explore an expanded, integrative concept, 'etiologic field effect', which asserts that various etiologic factors (the exposome including dietary, lifestyle, environmental, microbial, hormonal, and genetic factors) and their interactions (the interactome) contribute to a tissue microenvironmental milieu that constitutes a 'field of susceptibility' to neoplasia initiation, evolution, and progression. Importantly, etiological fields predate the acquisition of molecular aberrations commonly considered to indicate presence of filed effect. Inspired by molecular pathological epidemiology (MPE) research, which examines the influence of etiologic factors on cellular and molecular alterations during disease course, an etiologically focused approach to field effect can: (1) broaden the horizons of our inquiry into cancer susceptibility and progression at molecular, cellular, and environmental levels, during all stages of tumor evolution; (2) embrace host-environment-tumor interactions (including gene-environment interactions) occurring in the tumor microenvironment; and, (3) help explain intriguing observations, such as shared molecular features between bilateral primary breast carcinomas, and between synchronous colorectal cancers, where similar molecular changes are absent from intervening normal colon. MPE research has identified a number of endogenous and environmental exposures which can influence not only molecular signatures in the genome, epigenome, transcriptome, proteome, metabolome and interactome, but also host immunity and tumor behavior. We anticipate that future technological advances will allow the development of in vivo biosensors capable of detecting and quantifying 'etiologic field effect' as abnormal network pathology patterns of cellular and microenvironmental responses to endogenous and exogenous exposures. Through an 'etiologic field effect' paradigm, and holistic systems pathology (systems biology) approaches to cancer biology, we can improve personalized prevention and treatment strategies for precision medicine.

TP53 mutations in human cancer: database reassessment and prospects for the next decade

More than 50% of human tumors carry TP53 gene mutations and in consequence more than 45,000 somatic and germline mutations have been gathered in the UMD TP53 database (http://p53.fr). Analyses of these mutations have been invaluable for bettering our knowledge on the structure-function relationships within the TP53 protein and the high degree of heterogeneity of the various TP53 mutants in human cancer. In this review, we discuss how with the release of the sequences of thousands of tumor genomes issued from high-throughput sequencing, the description of novel TP53 mutants is now reaching a plateau indicating that we are close to the full set of mutants that target the elusive tumor-suppressive activity of this protein. We performed an extensive and thorough analysis of the TP53 mutation database, focusing particularly on specific sets of mutations that were overlooked in the past because of their low frequencies, for example, synonymous mutations, splice mutations, or mutations-targeting residues subject to posttranslational modifications. We also discuss the evolution of the statistical methods used to differentiate TP53 passenger mutations and artifactual data from true mutations, a process vital to the release of an accurate TP53 mutation database that will in turn be an invaluable tool for both clinicians and researchers.

SMO expression in colorectal cancer: associations with clinical, pathological, and molecular features

BACKGROUND

Smoothened, frizzled family receptor (SMO) is an important component of the hedgehog signaling pathway, which has been implicated in various human carcinomas. However, clinical, molecular, and prognostic associations of SMO expression in colorectal cancer remain unclear.

METHODS

Using a database of 735 colon and rectal cancers in the Nurse's Health Study and the Health Professionals Follow-up Study, we examined the relationship of tumor SMO expression (assessed by immunohistochemistry) to prognosis, and to clinical, pathological, and tumor molecular features, including mutations of KRAS, BRAF, and PIK3CA, microsatellite instability, CpG island methylator phenotype (CIMP), LINE-1 methylation, and expression of phosphorylated AKT and CTNNB1.

RESULTS

SMO expression was detected in 370 tumors (50 %). In multivariate logistic regression analysis, SMO expression was independently inversely associated with phosphorylated AKT expression [odds ratio (OR) 0.48; 95 % confidence interval (CI) 0.34-0.67] and CTNNB1 nuclear localization (OR 0.48; 95 % CI 0.35-0.67). SMO expression was not significantly associated with colorectal cancer-specific or overall survival. However, in CIMP-high tumors, but not CIMP-low/0 tumors, SMO expression was significantly associated with better colorectal cancer-specific survival (log-rank P = 0.012; multivariate hazard ratio, 0.36; 95 % CI 0.13-0.95; P interaction = 0.035, for SMO and CIMP status).

CONCLUSIONS

Our data reveal novel potential associations between the hedgehog, the WNT/CTNNB1, and the PI3K (phosphatidylinositol-4,5-bisphosphonate 3-kinase)/AKT pathways, supporting pivotal roles of SMO and hedgehog signaling in pathway networking. SMO expression in colorectal cancer may interact with tumor CIMP status to affect patient prognosis, although confirmation by future studies is needed.

BRAF V600E mutation and KRAS codon 13 mutations predict poor survival in Chinese colorectal cancer patients

Background

Mutations in KRAS, BRAF and PIK3CA are the most common somatic alterations found in the colorectal cancer (CRC) patients from Western countries; but their prevalence and prognostic value have not been adequately assessed in Asian patients. The aim of this study was to determine the mutation frequencies of these genes in Chinese CRC patients and to investigate their impact on prognosis.

Methods

The sequences of exon 2 of KRAS, exon 15 of BRAF and exons 9 and 20 of PIK3CA were evaluated by PCR and direct sequencing using DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissues from primary CRC tumors of 214 patients (colon/rectum: 126/88).

Results

KRAS, BRAF and PIK3CA mutations were identified in 44.9% (96/214), 4.2% (9/214) and 12.3% (26/212) CRCs, respectively. The most frequent mutations in KRAS, BRAF and PIK3CA were G12D, V600E and H1047R, respectively. All BRAF and 80.8% PIK3CA mutations were from colon cancer patients. BRAF V600E was associated with advanced TNM (P < 0.001), more distant metastases (P = 0.025), and worse overall survival (OS, P < 0.001; multivariate HR = 4.2, P = 0.004) in colon cancer patients. Compared with KRAS wt/BRAF wt CRC patients (N = 109), those with KRAS codon 13 mutations (N = 25) had significantly worse OS (P = 0.016; multivariate HR = 2.7, P = 0.011), whereas KRAS codon 12-mutated cases were not significantly associated with survival. Among the three most common KRAS mutations, G13D (N = 23) showed significant association with poor OS (P = 0.024; multivariate HR = 2.6, P = 0.016) compared with KRAS wt/BRAF wt patients.

Conclusion

Our findings indicate that PI3K/RAS-RAF signaling pathway genes are frequently mutated in Chinese CRC patients, but have different characteristics than found in Western patients. BRAF V600E is an independent prognostic factor for Chinese patients. Our finding that KRAS codon 13 mutations (in particular G13D) are associated with inferior survival in BRAF wild-type CRCs in Chinese patients was not reported thus far. Our data emphasizes the importance of prospective evaluation of molecular features in CRC patients, because a single mutation type may represent a distinct biologic effect and clinical implication.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2407-14-802) contains supplementary material, which is available to authorized users.

Molecular profiling and companion diagnostics: where is personalized medicine in cancer heading?

The goal of personalized medicine is to use the right drug at the right dose - with minimal or no toxicity - for the right patient at the right time. Recent advances in understanding cell biology and pathways, and in using molecular 'omics' technologies to diagnose cancer, offer a strategic bridge to personalized medicine in cancer. Modern personalized medicine takes into account an individual's genetic makeup and disease history before developing a treatment regimen. The future of clinical oncology will be based on the use of predictive and prognostic biomarkers in patient management. Once implemented widely, personalized medicine will benefit patients and the healthcare system greatly.

World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonisation Project: IV. Tissue collection, processing, and storage in endometriosis research

OBJECTIVE

To harmonize standard operating procedures (SOPs) and standardize the recording of associated data for collection, processing, and storage of human tissues relevant to endometriosis.

DESIGN

An international collaboration involving 34 clinical/academic centers and three industry collaborators from 16 countries on five continents.

SETTING

In 2013, two workshops were conducted followed by global consultation, bringing together 54 leaders in endometriosis research and sample processing from around the world.

PATIENT(S)

None.

INTERVENTION(S)

Consensus SOPs were based on: 1) systematic comparison of SOPs from 24 global centers collecting tissue samples from women with and without endometriosis on a medium or large scale (publication on >100 cases); 2) literature evidence where available, or consultation with laboratory experts otherwise; and 3) several global consultation rounds.

MAIN OUTCOME MEASURE(S)

Standard recommended and minimum required SOPs for tissue collection, processing, and storage in endometriosis research.

RESULT(S)

We developed "recommended standard" and "minimum required" SOPs for the collection, processing, and storage of ectopic and eutopic endometrium, peritoneum, and myometrium, and a biospecimen data collection form necessary for interpretation of sample-derived results.

CONCLUSION(S)

The EPHect SOPs allow endometriosis research centers to decrease variability in tissue-based results, facilitating between-center comparisons and collaborations. The procedures are also relevant to research into other gynecologic conditions involving endometrium, myometrium, and peritoneum. The consensus SOPs are based on the best available evidence; areas with limited evidence are identified as requiring further pilot studies. The SOPs will be reviewed based on investigator feedback and through systematic triannual follow-up. Updated versions will be made available at: http://endometriosisfoundation.org/ephect.

Overcoming tumor heterogeneity in the molecular diagnosis of urological cancers

Our understanding of tumor heterogeneity and impact on treatment response is still in its infancy, presenting significant challenges to the molecular pathologist, treating physician and ultimately for the patient. Given that tumor recurrence due to treatment resistance is the most common cause of cancer death, there remains a critical unmet need to change the current paradigm. The mechanisms which underlie tumor heterogeneity can be broadly divided into genomic instability and non-mutational processes, including stochastic variations in cellular responses, modulation by tumor microenvironment and or phenotypic/ functional plasticity relating to cancer stem cells. We believe that these biological mechanisms are not mutually exclusive and emphasize the need for more suitable methodologies to exploit the spatiotemporal patterns of intratumoral heterogeneity using novel approaches such as quantitative tissue-based biomarker assessment and systemic fluid analytics. Generating a comprehensive patient-centric phenotypic disease profile should generate a 'codex' which can be employed to change the current treatment decision process.