Insight into the heterogeneity of breast cancer through next-generation sequencing

Molecular characterization and targeted therapeutic approaches in breast cancer

Despite the wide improvements in breast cancer (BC) detection and adjuvant treatment, BC is still responsible for approximately 40,000 deaths annually in the United States. Novel biomarkers are fundamental to assist clinicians in BC detection, risk stratification, disease subtyping, prediction of treatment response, and surveillance, allowing a more tailored approach to therapy in both primary and metastatic settings. In primary BC, the development of molecular profiling techniques has added prognostic and predictive information to conventional biomarkers--estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2. Moreover, the application of next-generation sequencing and reverse-phase protein microarray methods in the metastatic setting holds the promise to further advance toward a personalized management of cancer. The improvement in our understanding on BC biology associated with the study of the genomic aberrations characterizing the most common molecular subtypes allows us to explore new targets for drug development. Finally, the integration of cancer stem cell-targeted therapies and immune therapies in future combination regimens increases our chances to successfully treat a larger proportion of women with more aggressive and resistant metastatic disease. This article reviews the current state of novel biological markers for BC, the evidence to demonstrate their clinical validity and utility, and the implication for therapeutic targeting.

Cell-lineage heterogeneity and driver mutation recurrence in pre-invasive breast neoplasia

Background

All cells in an individual are related to one another by a bifurcating lineage tree, in which each node is an ancestral cell that divided into two, each branch connects two nodes, and the root is the zygote. When a somatic mutation occurs in an ancestral cell, all its descendants carry the mutation, which can then serve as a lineage marker for the phylogenetic reconstruction of tumor progression. Using this concept, we investigate cell lineage relationships and genetic heterogeneity of pre-invasive neoplasias compared to invasive carcinomas.

Methods

We deeply sequenced over a thousand phylogenetically informative somatic variants in 66 morphologically independent samples from six patients that represent a spectrum of normal, early neoplasia, carcinoma in situ, and invasive carcinoma. For each patient, we obtained a highly resolved lineage tree that establishes the phylogenetic relationships among the pre-invasive lesions and with the invasive carcinoma.

Results

The trees reveal lineage heterogeneity of pre-invasive lesions, both within the same lesion, and between histologically similar ones. On the basis of the lineage trees, we identified a large number of independent recurrences of PIK3CA H1047 mutations in separate lesions in four of the six patients, often separate from the diagnostic carcinoma.

Conclusions

Our analyses demonstrate that multi-sample phylogenetic inference provides insights on the origin of driver mutations, lineage heterogeneity of neoplastic proliferations, and the relationship of genomically aberrant neoplasias with the primary tumors. PIK3CA driver mutations may be comparatively benign inducers of cellular proliferation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0146-2) contains supplementary material, which is available to authorized users.

Mutant allele tumor heterogeneity (MATH) and head and neck squamous cell carcinoma

Intra-tumor heterogeneity, variation between individual tumor cells within a patient's tumor, is increasingly seen as a critical mechanism underlying treatment resistance and therapeutic failure. Despite this growing awareness, few methods to assess intra-tumor heterogeneity exist outside the research laboratory, especially in the absence of a known marker. Mutant allele tumor heterogeneity (MATH) is a novel, non-biased, quantitative method to assess genetic heterogeneity based on tumor next generation exome sequencing. The quantitative aspect of MATH has allowed it to be verified as an actionable biomarker in a retrospective HNSCC data set with available exome sequencing and clinical data. In addition, it was also capable of stratifying patient outcome after controlling for other high-risk features such as p53 mutation, HPV status, and advanced tumor stage. Future work will explore the predictive power of MATH in larger data sets such as The Cancer Genome Atlas and examine the underlying cellular mechanisms responsible for intra-tumor heterogeneity.

In stage II/III lymph node-positive breast cancer patients less than 55 years of age, keratin 8 expression in lymph node metastases but not in the primary tumour is an indicator of better survival

Axillary lymph node status is one of the most important prognostic variables for breast cancer (BC). To investigate and understand the clinical, histopathological and biological factors that affect prognosis in node-positive young breast cancer patients, we compared the phenotype of 100 primary tumours with their corresponding loco-regional lymph node (LN) metastases using conventional immunohistochemistry (IHC) markers currently in use for molecular classification of breast cancer. By comparing the expression of ER, PR, HER-2, Ki67, K8, K5/6 and vimentin, we found that expression of HER-2, Ki67, K8 and vimentin is frequently lost in lymph node metastases. Between the primary tumour and corresponding lymph node metastases, expression of keratins K8 and K5/6 significantly changed. Expression of K8 in lymph node metastases, but not in primary tumours, segregates patients in two sub-groups with different outcomes. Survival of patients with K8-positive LN metastases at 5 years in comparison with patients with K8-negative LN metastases was 75 vs 48 %, at 10 years 62 vs 22 % and at 20 years 53 vs 14 % (p < 0.001). K8 immunostaining of tissue from the lymph node metastasis allows defining a sub-group of lymph node-positive BC patients with a highly unfavourable outcome, for whom therapeutic options might have to be reconsidered.

Molecular subtyping for clinically defined breast cancer subgroups

Introduction

Breast cancer is commonly classified into intrinsic molecular subtypes. Standard gene centering is routinely done prior to molecular subtyping, but it can produce inaccurate classifications when the distribution of clinicopathological characteristics in the study cohort differs from that of the training cohort used to derive the classifier.

Methods

We propose a subgroup-specific gene-centering method to perform molecular subtyping on a study cohort that has a skewed distribution of clinicopathological characteristics relative to the training cohort. On such a study cohort, we center each gene on a specified percentile, where the percentile is determined from a subgroup of the training cohort with clinicopathological characteristics similar to the study cohort. We demonstrate our method using the PAM50 classifier and its associated University of North Carolina (UNC) training cohort. We considered study cohorts with skewed clinicopathological characteristics, including subgroups composed of a single prototypic subtype of the UNC-PAM50 training cohort (n = 139), an external estrogen receptor (ER)-positive cohort (n = 48) and an external triple-negative cohort (n = 77).

Results

Subgroup-specific gene centering improved prediction performance with the accuracies between 77% and 100%, compared to accuracies between 17% and 33% from standard gene centering, when applied to the prototypic tumor subsets of the PAM50 training cohort. It reduced classification error rates on the ER-positive (11% versus 28%; P = 0.0389), the ER-negative (5% versus 41%; P < 0.0001) and the triple-negative (11% versus 56%; P = 0.1336) subgroups of the PAM50 training cohort. In addition, it produced higher accuracy for subtyping study cohorts composed of varying proportions of ER-positive versus ER-negative cases. Finally, it increased the percentage of assigned luminal subtypes on the external ER-positive cohort and basal-like subtype on the external triple-negative cohort.

Conclusions

Gene centering is often necessary to accurately apply a molecular subtype classifier. Compared with standard gene centering, our proposed subgroup-specific gene centering produced more accurate molecular subtype assignments in a study cohort with skewed clinicopathological characteristics relative to the training cohort.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-015-0520-4) contains supplementary material, which is available to authorized users.

Axillary lymph node management in breast cancer with positive sentinel lymph node biopsy

The surgical treatment of localized breast cancer has become progressively less aggressive over the years. The management of the axillary lymph nodes has been modified by the introduction of sentinel lymph node biopsy. Axillary dissection can be avoided in patients with sentinel lymph node negative biopsies. Based on randomized trials data, it has been proposed that no lymph node dissection should be carried out even in certain patients with sentinel lymph node positive biopsies. This commentary discusses the basis of such recommendations and cautions against a general omission of lymph node dissection in breast cancer patients with positive sentinel lymph node biopsies. Instead, an individualized approach based on axillary tumor burden and biology of the cancer should be considered.

Functional and molecular characterisation of EO771.LMB tumours, a new C57BL/6-mouse-derived model of spontaneously metastatic mammary cancer

The translation of basic research into improved therapies for breast cancer patients requires relevant preclinical models that incorporate spontaneous metastasis. We have completed a functional and molecular characterisation of a new isogenic C57BL/6 mouse model of breast cancer metastasis, comparing and contrasting it with the established BALB/c 4T1 model. Metastatic EO771.LMB tumours were derived from poorly metastatic parental EO771 mammary tumours. Functional differences were evaluated using both in vitro assays and spontaneous metastasis assays in mice. Results were compared to non-metastatic 67NR and metastatic 4T1.2 tumours of the 4T1 model. Protein and transcript levels of markers of human breast cancer molecular subtypes were measured in the four tumour lines, as well as p53 (Tp53) tumour-suppressor gene status and responses to tamoxifen in vivo and in vitro. Array-based expression profiling of whole tumours identified genes and pathways that were deregulated in metastatic tumours. EO771.LMB cells metastasised spontaneously to lung in C57BL/6 mice and displayed increased invasive capacity compared with parental EO771. By immunohistochemical assessment, EO771 and EO771.LMB were basal-like, as was the 4T1.2 tumour, whereas 67NR had a luminal phenotype. Primary tumours from all lines were negative for progesterone receptor, Erb-b2/Neu and cytokeratin 5/6, but positive for epidermal growth factor receptor (EGFR). Only 67NR displayed nuclear estrogen receptor alpha (ERα) positivity. EO771 and EO771.LMB expressed mutant p53, whereas 67NR and 4T1.2 were p53-null. Integrated molecular analysis of both the EO771/EO771.LMB and 67NR/4T1.2 pairs indicated that upregulation of matrix metalloproteinase-3 (MMP-3), parathyroid hormone-like hormone (Pthlh) and S100 calcium binding protein A8 (S100a8) and downregulation of the thrombospondin receptor (Cd36) might be causally involved in metastatic dissemination of breast cancer.

Mapping of actionable mutations to histological subtype domains in lung adenocarcinoma: implications for precision medicine

Precision medicine depends on the accurate identification of actionable mutations in a tumor sample. It is unknown how heterogeneous the distribution of such mutations can be in a tumor. Morphological (i.e. histopathological) heterogeneity is well described in lung adenocarcinoma and has been specifically recognized in the most recent official clinico-pathological classification. The most predominant subtype present is now used to classify each lung adenocarcinoma. No molecular profile exists to explain the intratumoral differences in lung adenocarcinoma morphology, despite the consistently observed association between specific predominant subtypes and poorer survival. Given a recent proposal stratifying lung adenocarcinoma into subtypes of differing metastatic potential, we questioned the assumption that major mutations are present uniformly throughout tumors; especially those showing discrete different subtypes.

We selected formalin-fixed paraffin embedded lung adenocarcinoma specimens that showed discrete areas of different subtypes, extracted subtype DNA samples from those areas and screened for mutations in hotspot regions of the EGFR, KRAS and BRAF genes using high resolution melting. Sanger sequencing was used to confirm all identified mutations. Chromogenic in situ hybridization (CISH) was used to identify mutant allele specific imbalances in tumors with EGFR mutations.

Interestingly, we found that KRAS and BRAF mutations could be confined to morphological domains of higher grade. On the other hand, EGFR mutations were found through all histological subtypes in each tumor consistent with the driver status of this mutation.

Intratumoral heterogeneity has major implications for tumorigenesis, chemoresistance and the role of histopathology in molecular screening for precision medicine. This study not only confirms that intratumoral mutational heterogeneity does occur, but also that it is associated with morphologically distinct regions in some tumors. From a practical perspective, small biopsies may not adequately represent a tumor's full mutational profile, particularly for later arising but prognostically important mutations such as those in the KRAS and BRAF genes.

Combining functional genomics strategies identifies modular heterogeneity of breast cancer intrinsic subtypes

Background

The discovery of breast cancer subtypes and subsequent development of treatments aimed at them has allowed for a great reduction in the mortality of breast cancer. But despite this progress, tumors with similar characteristics that belong to the same subtype continue to respond differently to the same treatment. Five subtypes of breast cancer, namely intrinsic subtypes, have been characterized to date based on their gene expression profiles. Among other characteristics, subtypes vary in their degree of intra-subtype heterogeneity. It is not clear, however, whether this heterogeneity is shared across all tumor traits. It is also unclear whether individual traits can be highly heterogeneous among a majority of homogeneous traits.

Results

We employ network theory to uncover gene modules and accordingly consider them as tumor traits, which capture shared biological processes among the subtypes. We then use the β-diversity metric from ecology to quantify the heterogeneity in these gene modules. In doing so, we show that breast cancer heterogeneity is contained in gene modules and that this modular heterogeneity increases monotonically across the subtypes. We identify a core of two modules that are shared among all subtypes which contain nucleosome assembly and mammary morphogenesis genes, and a number of modules that are specific to subtypes. This modular heterogeneity, which increases with global heterogeneity, relates to tumor aggressiveness. Indeed, we observe that Luminal A, the most treatable of subtypes, has the lowest modular heterogeneity whereas the Basal-like subtype, which is among the hardest to treat, has the highest. Furthermore, our analysis shows that a higher degree of global heterogeneity does not imply higher heterogeneity for all modules, as Luminal B shows the highest heterogeneity for core modules.

Conclusions

Overall, modular heterogeneity provides a framework with which to dissect cancer heterogeneity and better understand its underpinnings, thereby ultimately advancing our knowledge towards a more effective personalized cancer therapy.

Electronic supplementary material

The online version of this article (doi:10.1186/1756-0381-7-27) contains supplementary material, which is available to authorized users.

Cancer stem cells--the current status of an old concept: literature review and clinical approaches

As regards their morphology and biology, tumours consist of heterogeneous cell populations. The cancer stem cell (CSC) hypothesis assumes that a tumour is hierarchically organized and not all of the cells are equally capable of generating descendants, similarly to normal tissue. The only cells being able to self-renew and produce a heterogeneous tumour cell population are cancer stem cells. CSCs probably derive from normal stem cells, although progenitor cells may be taken into consideration as the source of cancer stem cells. CSCs reside in the niche defined as the microenvironment formed by stromal cells, vasculature and extracellular matrix. The CSC assays include FACS sorting, xenotransplantation to immunodeficient mice (SCID), incubation with Hoechst 33342 dye, cell culture in non-adherent conditions, cell culture with bromodeoxyuridine. CSCs have certain properties that make them resistant to anticancer therapy, which suggests they may be the target for potential therapeutic strategies.

Hypoxia-inducible factors are required for chemotherapy resistance of breast cancer stem cells

Triple negative breast cancers (TNBCs) are defined by the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 expression, and are treated with cytotoxic chemotherapy such as paclitaxel or gemcitabine, with a durable response rate of less than 20%. TNBCs are enriched for the basal subtype gene expression profile and the presence of breast cancer stem cells, which are endowed with self-renewing and tumor-initiating properties and resistance to chemotherapy. Hypoxia-inducible factors (HIFs) and their target gene products are highly active in TNBCs. Here, we demonstrate that HIF expression and transcriptional activity are induced by treatment of MDA-MB-231, SUM-149, and SUM-159, which are human TNBC cell lines, as well as MCF-7, which is an ER(+)/PR(+) breast cancer line, with paclitaxel or gemcitabine. Chemotherapy-induced HIF activity enriched the breast cancer stem cell population through interleukin-6 and interleukin-8 signaling and increased expression of multidrug resistance 1. Coadministration of HIF inhibitors overcame the resistance of breast cancer stem cells to paclitaxel or gemcitabine, both in vitro and in vivo, leading to tumor eradication. Increased expression of HIF-1α or HIF target genes in breast cancer biopsies was associated with decreased overall survival, particularly in patients with basal subtype tumors and those treated with chemotherapy alone. Based on these results, clinical trials are warranted to test whether treatment of patients with TNBC with a combination of cytotoxic chemotherapy and HIF inhibitors will improve patient survival.

Understanding the complexity of antigen retrieval of DNA methylation for immunofluorescence-based measurement and an approach to challenge

Cytosine methylation (5-methylcytosine, 5meC) in the CpG-rich regions of the mammalian genome is an important epigenetic mechanism playing roles in transcription regulation and genomic stability. The abnormalities in DNA methylation can occur in various types of cancer and some genetic diseases. The measurement of DNA methylation is therefore important and there is a range of methodologies used to detect DNA methylation. Many methods based on bisulfite treatment appeared with a lack of specificity after recent discoveries of various modifications of methylated cytosine, however there are new treatments developed to overcome this limitation. Immunofluorescence is currently known to be able to specifically detect DNA methylation as it uses different antibodies against 5meC and its derivatives, but it is a semi-quantitative method. Immunofluorescence protocols commonly include fixation of cells followed by permeabilisation, antigen retrieval, and treatments with antibodies. Establishing the strategy for antigen retrieval of immunofluorescence is important to unmask epitopes (i.e. 5meC) from other proteins, and therefore to access the antigen of interest. There are many approaches used for antigen retrieval induced by acid, enzyme and/or heat. The selection of antigen retrieval method can depend on a variety of such antigen-based or cell-based conditions, since the dynamic structure of DNA and chromatin accounts for the complexity of involved proteins to mask the epitope. This review aims to specifically focus on the complexity of in situ detection of DNA methylation by immunofluorescence-based methods using antigen retrieval with the current understanding of DNA methylation mechanism, and suggests conditions for antigenic retrieval of 5meC epitope.

Deciphering oncogenic drivers: from single genes to integrated pathways

Technological advances in next-generation sequencing have uncovered a wide spectrum of aberrations in cancer genomes. The extreme diversity in cancer mutations necessitates computational approaches to differentiate between the 'drivers' with vital function in cancer progression and those nonfunctional 'passengers'. Although individual driver mutations are routinely identified, mutational profiles of different tumors are highly heterogeneous. There is growing consensus that pathways rather than single genes are the primary target of mutations. Here we review extant bioinformatics approaches to identifying oncogenic drivers at different mutational levels, highlighting the strategies for discovering driver pathways and networks from cancer mutation data. These approaches will help reduce the mutation complexity, thus providing a simplified picture of cancer.

Ovarian cancer biomarker discovery based on genomic approaches

Ovarian cancer presents at an advanced stage in more than 75% of patients. Early detection has great promise to improve clinical outcomes. Although the advancing proteomic technologies led to the discovery of numerous ovarian cancer biomarkers, no screening method has been recommended for early detection of ovarian cancer. Complexity and heterogeneity of ovarian carcinogenesis is a major obstacle to discover biomarkers. As cancer arises due to accumulation of genetic change, understanding the close connection between genetic changes and ovarian carcinogenesis would provide the opportunity to find novel gene-level ovarian cancer biomarkers. In this review, we summarize the various gene-based biomarkers by genomic technologies, including inherited gene mutations, epigenetic changes, and differential gene expression. In addition, we suggest the strategy to discover novel gene-based biomarkers with recently introduced next generation sequencing.

Statistical measures of transcriptional diversity capture genomic heterogeneity of cancer

BACKGROUND

Molecular heterogeneity of tumors suggests the presence of multiple different subclones that may limit response to targeted therapies and contribute to acquisition of drug resistance, but its quantification has remained challenging.

RESULTS

We performed simulations to evaluate statistical measures that best capture the molecular diversity within a group of tumors for either continuous (gene expression) or discrete (mutations, copy number alterations) molecular data. Dispersion based metrics in the principal component space best captured the underlying heterogeneity. To demonstrate utility of these measures, we characterized the diversity in transcriptional and genomic profiles of different breast tumor subtypes, and showed that basal-like or triple-negative breast cancers (TNBC) are significantly more heterogeneous molecularly than other subtypes. Our analysis also suggests that transcriptional diversity is a global characteristic of the tumors observed across the majority of molecular pathways. Among basal-like tumors, those that were resistant to multi-agent chemotherapy showed greater transcriptional diversity compared to chemotherapy-sensitive tumors, suggesting that potentially multiple mechanisms may be contributing to chemotherapy resistance.

CONCLUSIONS

We proposed and validated measures of transcriptional and genomic diversity that can quantify the molecular diversity of tumors. We applied the new measures to genomic data from breast tumors and demonstrated that basal-like breast cancers are significantly more diverse than other breast cancers. The observation that chemo-resistant tumors are significantly more diverse molecularly than chemosensitive tumors implies that multiple resistance mechanisms may be active, thus limiting the sensitivity and accuracy of predictive markers of chemotherapy response.

A new toolbox for assessing single cells

Unprecedented access to the biology of single cells is now feasible, enabled by recent technological advancements that allow us to manipulate and measure sparse samples and achieve a new level of resolution in space and time. This review focuses on advances in tools to study single cells for specific areas of biology. We examine both mature and nascent techniques to study single cells at the genomics, transcriptomics, and proteomics level. In addition, we provide an overview of tools that are well suited for following biological responses to defined perturbations with single-cell resolution. Techniques to analyze and manipulate single cells through soluble and chemical ligands, the microenvironment, and cell-cell interactions are provided. For each of these topics, we highlight the biological motivation, applications, methods, recent advances, and opportunities for improvement. The toolbox presented in this review can function as a starting point for the design of single-cell experiments.

Intratumor heterogeneity: nature and biological significance

Intratumor heterogeneity inherent in the majority of human cancers is a major obstacle for a highly efficient diagnosis and successful prognosis and treatment of these diseases. Being a result of clonal diversity within the same tumor, intratumor heterogeneity can be manifested in variability of genetic and epigenetic status, gene and protein expression, morphological structure, and other features of the tumor. It is most likely that the appearance of this diversity is a source for the adaptation of the tumor to changes in microenvironmental conditions and/or a tool for changing its malignant potential. In any case, both processes result in the appearance of cell clones with different undetermined sets of hallmarks. In this review, we describe the heterogeneity of molecular disorders in various human tumors and consider modern viewpoints of its development including genetic and non-genetic factors of heterogeneity origin and the role of cancer stem cells and clonal evolution. We also systematize data on the contribution of tumor diversity to progression of various tumors and the efficiency of their treatment. The main problems are indicated in the diagnosis and therapy of malignant tumors caused by intratumor heterogeneity and possible pathways for their solution. Moreover, we also suggest the key goals whose achievement promises to minimize the problem of intratumor heterogeneity and to identify new prognostic, predictive, and target markers for adequate and effective treatment of cancer.

Modeling luminal breast cancer heterogeneity: combination therapy to suppress a hormone receptor-negative, cytokeratin 5-positive subpopulation in luminal disease

Introduction

Many Luminal breast cancers are heterogeneous, containing substantial numbers of estrogen (ER) and progesterone (PR) receptor-negative cells among the ER+ PR+ ones. One such subpopulation we call “Luminobasal” is ER-, PR- and cytokeratin 5 (CK5)-positive. It is not targeted for treatment.

Methods

To address the relationships between ER+PR+CK5– and ER–PR–CK5+ cells in Luminal cancers and tightly control their ratios we generated isogenic pure Luminal (pLUM) and pure Luminobasal (pLB) cells from the same parental Luminal human breast cancer cell line. We used high-throughput screening to identify pLB-specific drugs and examined their efficacy alone and in combination with hormone therapy in mixed-cell tumor models.

Results

We show that pLUM and MCF7 cells suppress proliferation of pLB cells in mixed-cell 3D colonies in vitro and that pLUM cells suppress growth of pLB cells in mixed-cell xenografts in vivo. High-throughput screening of 89 FDA-approved oncology drugs shows that pLB cells are sensitive to monotherapy with the epidermal growth factor receptor (EGFR) inhibitors gefitinib and erlotinib. By exploiting mixed-cell 3D colonies and mixed-cell solid mouse tumors models we demonstrate that combination therapy with gefitinib plus the anti-estrogen fulvestrant constitutes a robust treatment strategy.

Conclusions

We propose that response to combination endocrine/EGFR inhibitor therapies in heterogeneous Luminal cancers may improve long-term survival in patients whose primary tumors have been preselected for appropriate biomarkers, including ER, PR, CK5 and EGFR.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-014-0418-6) contains supplementary material, which is available to authorized users.

Secreted heat shock protein gp96-Ig: next-generation vaccines for cancer and infectious diseases

Over the past decade, our laboratory has developed a secreted heat shock protein (HSP), chaperone gp96, cell-based vaccine that generates effective anti-tumor and anti-infectious immunity in vivo. Gp96-peptide complexes were identified as an extremely efficient stimulator of MHC I-mediated antigen cross-presentation, generating CD8 cytotoxic T-lymphocyte responses detectable in blood, spleen, gut and reproductive tract to femto-molar concentrations of antigen. These studies provided the first evidence that cell-based gp96-Ig-secreting vaccines may serve as a potent modality to induce both systemic and mucosal immunity. This approach takes advantage of the combined adjuvant and antigen delivery capacity of gp96 for the generation of cytotoxic immunity against a wide range of antigens in both anti-vial and anti-cancer vaccination. Here, we review the vaccine design that utilizes the unique property/ability of endoplasmic HSP gp96 to bind antigenic peptides and deliver them to antigen-presenting cells.

Identification of structural variation in mouse genomes

Structural variation is variation in structure of DNA regions affecting DNA sequence length and/or orientation. It generally includes deletions, insertions, copy-number gains, inversions, and transposable elements. Traditionally, the identification of structural variation in genomes has been challenging. However, with the recent advances in high-throughput DNA sequencing and paired-end mapping (PEM) methods, the ability to identify structural variation and their respective association to human diseases has improved considerably. In this review, we describe our current knowledge of structural variation in the mouse, one of the prime model systems for studying human diseases and mammalian biology. We further present the evolutionary implications of structural variation on transposable elements. We conclude with future directions on the study of structural variation in mouse genomes that will increase our understanding of molecular architecture and functional consequences of structural variation.

BRCA2 inhibition enhances cisplatin-mediated alterations in tumor cell proliferation, metabolism, and metastasis

Tumor cells have unstable genomes relative to non-tumor cells. Decreased DNA integrity resulting from tumor cell instability is important in generating favorable therapeutic indices, and intact DNA repair mediates resistance to therapy. Targeting DNA repair to promote the action of anti-cancer agents is therefore an attractive therapeutic strategy. BRCA2 is involved in homologous recombination repair. BRCA2 defects increase cancer risk but, paradoxically, cancer patients with BRCA2 mutations have better survival rates. We queried TCGA data and found that BRCA2 alterations led to increased survival in patients with ovarian and endometrial cancer. We developed a BRCA2-targeting second-generation antisense oligonucleotide (ASO), which sensitized human lung, ovarian, and breast cancer cells to cisplatin by as much as 60%. BRCA2 ASO treatment overcame acquired cisplatin resistance in head and neck cancer cells, but induced minimal cisplatin sensitivity in non-tumor cells. BRCA2 ASO plus cisplatin reduced respiration as an early event preceding cell death, concurrent with increased glucose uptake without a difference in glycolysis. BRCA2 ASO and cisplatin decreased metastatic frequency in vivo by 77%. These results implicate BRCA2 as a regulator of metastatic frequency and cellular metabolic response following cisplatin treatment. BRCA2 ASO, in combination with cisplatin, is a potential therapeutic anti-cancer agent.

BRCA2 inhibition enhances cisplatin-mediated alterations in tumor cell proliferation, metabolism, and metastasis

Tumor cells have unstable genomes relative to non-tumor cells. Decreased DNA integrity resulting from tumor cell instability is important in generating favorable therapeutic indices, and intact DNA repair mediates resistance to therapy. Targeting DNA repair to promote the action of anti-cancer agents is therefore an attractive therapeutic strategy. BRCA2 is involved in homologous recombination repair. BRCA2 defects increase cancer risk but, paradoxically, cancer patients with BRCA2 mutations have better survival rates. We queried TCGA data and found that BRCA2 alterations led to increased survival in patients with ovarian and endometrial cancer. We developed a BRCA2-targeting second-generation antisense oligonucleotide (ASO), which sensitized human lung, ovarian, and breast cancer cells to cisplatin by as much as 60%. BRCA2 ASO treatment overcame acquired cisplatin resistance in head and neck cancer cells, but induced minimal cisplatin sensitivity in non-tumor cells. BRCA2 ASO plus cisplatin reduced respiration as an early event preceding cell death, concurrent with increased glucose uptake without a difference in glycolysis. BRCA2 ASO and cisplatin decreased metastatic frequency in vivo by 77%. These results implicate BRCA2 as a regulator of metastatic frequency and cellular metabolic response following cisplatin treatment. BRCA2 ASO, in combination with cisplatin, is a potential therapeutic anti-cancer agent.

Hypoxia-inducible factors and RAB22A mediate formation of microvesicles that stimulate breast cancer invasion and metastasis

Extracellular vesicles such as exosomes and microvesicles (MVs) are shed by cancer cells, are detected in the plasma of cancer patients, and promote cancer progression, but the molecular mechanisms regulating their production are not well understood. Intratumoral hypoxia is common in advanced breast cancers and is associated with an increased risk of metastasis and patient mortality that is mediated in part by the activation of hypoxia-inducible factors (HIFs). In this paper, we report that exposure of human breast cancer cells to hypoxia augments MV shedding that is mediated by the HIF-dependent expression of the small GTPase RAB22A, which colocalizes with budding MVs at the cell surface. Incubation of naïve breast cancer cells with MVs shed by hypoxic breast cancer cells promotes focal adhesion formation, invasion, and metastasis. In breast cancer patients, RAB22A mRNA overexpression in the primary tumor is associated with decreased overall and metastasis-free survival and, in an orthotopic mouse model, RAB22A knockdown impairs breast cancer metastasis.

Ensemble analyses improve signatures of tumour hypoxia and reveal inter-platform differences

Background

The reproducibility of transcriptomic biomarkers across datasets remains poor, limiting clinical application. We and others have suggested that this is in-part caused by differential error-structure between datasets, and their incomplete removal by pre-processing algorithms.

Methods

To test this hypothesis, we systematically assessed the effects of pre-processing on biomarker classification using 24 different pre-processing methods and 15 distinct signatures of tumour hypoxia in 10 datasets (2,143 patients).

Results

We confirm strong pre-processing effects for all datasets and signatures, and find that these differ between microarray versions. Importantly, exploiting different pre-processing techniques in an ensemble technique improved classification for a majority of signatures.

Conclusions

Assessing biomarkers using an ensemble of pre-processing techniques shows clear value across multiple diseases, datasets and biomarkers. Importantly, ensemble classification improves biomarkers with initially good results but does not result in spuriously improved performance for poor biomarkers. While further research is required, this approach has the potential to become a standard for transcriptomic biomarkers.

BRCA2 inhibition enhances cisplatin-mediated alterations in tumor cell proliferation, metabolism, and metastasis

Tumor cells have unstable genomes relative to non-tumor cells. Decreased DNA integrity resulting from tumor cell instability is important in generating favorable therapeutic indices, and intact DNA repair mediates resistance to therapy. Targeting DNA repair to promote the action of anti-cancer agents is therefore an attractive therapeutic strategy. BRCA2 is involved in homologous recombination repair. BRCA2 defects increase cancer risk but, paradoxically, cancer patients with BRCA2 mutations have better survival rates. We queried TCGA data and found that BRCA2 alterations led to increased survival in patients with ovarian and endometrial cancer. We developed a BRCA2-targeting second-generation antisense oligonucleotide (ASO), which sensitized human lung, ovarian, and breast cancer cells to cisplatin by as much as 60%. BRCA2 ASO treatment overcame acquired cisplatin resistance in head and neck cancer cells, but induced minimal cisplatin sensitivity in non-tumor cells. BRCA2 ASO plus cisplatin reduced respiration as an early event preceding cell death, concurrent with increased glucose uptake without a difference in glycolysis. BRCA2 ASO and cisplatin decreased metastatic frequency in vivo by 77%. These results implicate BRCA2 as a regulator of metastatic frequency and cellular metabolic response following cisplatin treatment. BRCA2 ASO, in combination with cisplatin, is a potential therapeutic anti-cancer agent.

Clonal intratumor heterogeneity of promoter hypermethylation in breast cancer by MS-MLPA

Intratumor heterogeneity may lead to sampling bias and may present major challenges to personalized medicine and biomarker development. Despite many studies investigating genetic heterogeneity, epigenetic intratumor heterogeneity of promoter hypermethylation has only rarely been examined in breast cancer. To examine clonal intratumor heterogeneity of promotor hypermethylation, we performed methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) for 24 established tumor-suppressor genes on multiple spatially separated samples obtained from 21 primary breast carcinomas. Multiregion analysis was performed, representing at least two and a maximum of five tumor blocks per patient and four areas per tumor block. Methylation results were heterogeneous at one or more genetic loci between different tumor regions in 95% of breast carcinomas. The most heterogeneous loci in decreasing frequency were RASSF1A (62%), CDKN2B (43%), APC (38%), GSTP1 (33%), CDH13 (24%), DAPK1 (19%), and CDKN1B (5%). Heterogeneity lead to a methylation status change in at least one locus in 65% of the tumors. For most genes, the relative contribution of between-patients and between-block variability to the total variation in methylation results was similar. Regardless of the gene, contribution of within-block variability was of little importance. In conclusion, although most variation in methylation status is present between individual breast cancers, clonal epigenetic heterogeneity is seen within most primary breast carcinomas, indicating that methylation results from a single random sample may not be representative of the whole tumor.

Anastrozole and everolimus in advanced gynecologic and breast malignancies: activity and molecular alterations in the PI3K/AKT/mTOR pathway

BACKGROUND

Since PI3K/AKT/mTOR pathway activation diminishes the effects of hormone therapy, combining aromatase inhibitors (anatrozole) with mTOR inhibitors (everolimus) was investigated.

PATIENTS AND METHODS

We evaluated anastrozole and everolimus in 55 patients with metastatic estrogen (ER) and/or progesterone receptor (PR)-positive breast and gynecologic tumors. Endpoints were safety, antitumor activity and molecular correlates.

RESULTS

Full doses of anastrozole (1 mg PO daily) and everolimus (10 mg PO daily) were well tolerated. Twelve of 50 evaluable patients (24%) (median = 3 prior therapies) achieved stable disease (SD) ≥ 6 months/partial response (PR)/complete response (CR) (n = 5 (10%) with PR/CR): 9 of 32 (28%) with breast cancer (n=5 (16%) with PR/CR); 2 of 10 (20%), ovarian cancer; and 1 of 6 (17%), endometrial cancer. Six of 22 patients (27%) with molecular alterations in the PI3K/AKT/mTOR pathway achieved SD ≥ 6 months/PR/CR. Six of 8 patients (75%) with SD ≥ 6 months/PR/CR with molecular testing demonstrated at least one alteration in the PI3K/AKT/mTOR pathway: mutations in PIK3CA (n=3) and AKT1 (n=1) or PTEN loss (n=3). All three responders (CR (n = 1); PR (n=2)) who had next generation sequencing demonstrated additional alterations: amplifications in CCNE1, IRS2, MCL1, CCND1, FGFR1 and MYC and a rearrangement in PRKDC.

CONCLUSIONS

Combination anastrozole and everolimus is well tolerated at full approved doses, and is active in heavily-pretreated patients with ER and/or PR-positive breast, ovarian and endometrial cancers. Responses were observed in patients with multiple molecular aberrations. CLINICAL TRAILS INCLUDED: NCT01197170.

Changing genetic paradigms: creating next-generation genetic databases as tools to understand the emerging complexities of genotype/phenotype relationships

Understanding genotype/phenotype relationships has become more complicated as increasing amounts of inter- and intra-tissue genetic heterogeneity have been revealed through next-generation sequencing and evidence showing that factors such as epigenetic modifications, non-coding RNAs and RNA editing can play an important role in determining phenotype. Such findings have challenged a number of classic genetic assumptions including (i) analysis of genomic sequence obtained from blood is an accurate reflection of the genotype responsible for phenotype expression in an individual; (ii) that significant genetic alterations will be found only in diseased individuals, in germline tissues in inherited diseases, or in specific diseased tissues in somatic diseases such as cancer; and (iii) that mutation rates in putative disease-associated genes solely determine disease phenotypes. With the breakdown of our traditional understanding of genotype to phenotype relationships, it is becoming increasingly apparent that new analytical tools will be required to determine the relationship between genotype and phenotypic expression. To this end, we are proposing that next-generation genetic database (NGDB) platforms be created that include new bioinformatics tools based on algorithms that can evaluate genetic heterogeneity, as well as powerful systems biology analysis tools to actively process and evaluate the vast amounts of both genomic and genomic-modifying information required to reveal the true relationships between genotype and phenotype.

Next-generation sequencing: application in liver cancer-past, present and future?

Hepatocellular Carcinoma (HCC) is the third most deadly malignancy worldwide characterized by phenotypic and molecular heterogeneity. In the past two decades, advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. More recently, improvements of sophisticated next-generation sequencing (NGS) technologies have enabled complete and cost-efficient analyses of cancer genomes at a single nucleotide resolution and advanced into valuable tools in translational medicine. Although the use of NGS in human liver cancer is still in its infancy, great promise rests in the systematic integration of different molecular analyses obtained by these methodologies, i.e., genomics, transcriptomics and epigenomics. This strategy is likely to be helpful in identifying relevant and recurrent pathophysiological hallmarks thereby elucidating our limited understanding of liver cancer. Beside tumor heterogeneity, progress in translational oncology is challenged by the amount of biological information and considerable “noise” in the data obtained from different NGS platforms. Nevertheless, the following review aims to provide an overview of the current status of next-generation approaches in liver cancer, and outline the prospects of these technologies in diagnosis, patient classification, and prediction of outcome. Further, the potential of NGS to identify novel applications for concept clinical trials and to accelerate the development of new cancer therapies will be summarized.

PARP inhibitor reduces proliferation and increases apoptosis in breast cancer cells

OBJECTIVE

Apoptosis is a reliable marker of chemotherapeutic efficacy. Olaparib and paclitaxel inhibit proliferation and induce apoptosis in a variety of cancers. We investigated the effects of paclitaxel combined with olaparib on apoptosis in breast cancer Bcap37 cells.

METHODS

Proliferation and apoptosis were detected by MTT assay and PI staining. Degradation of pro-caspase-3 and poly(ADP-ribose) polymerase (PARP) was analyzed by Western blotting.

RESULTS

Compared with paclitaxel alone, paclitaxel combined with 100 mg olaparib significantly reduced survival in Bcap37 cells at all tested treatment durations (P<0.05); inhibition increased with increasing olaparib dose and treatment time (P<0.01). Combined treatment yielded significantly higher rates of apoptosis (P<0.05), which also increased with time (P<0.01). Fluorescence micrographs showed that early and late apoptotic cells increased with treatment time. Pro-caspase-3 and PARP degradation was induced by paclitaxel and enhanced by olaparib in a dose-dependent manner. Thus, combined treatment was substantially more effective than treatment with paclitaxel alone.

CONCLUSIONS

Our findings suggest that paclitaxel and olaparib inhibit breast cancer Bcap37 cell proliferation and induce apoptosis. Combined treatment further reduced cell growth and enhanced apoptosis, suggesting that this combination therapy may be a promising treatment for breast cancer.

Theranostic and molecular classification of breast cancer

CONTEXT

Despite advances in breast cancer management, women continue to relapse and die of breast cancer. Traditionally, evaluation for hormone receptors (estrogen and progesterone), as well as HER2 overexpression, have guided therapy-related decision-making because they are both prognostic and predictive indicators. However, there are limitations with those studies, which can lead to improper treatment. Gene signatures have recently been shown to be of value in identifying molecular portraits of breast carcinoma and are beginning to play role in management and treatment algorithms.

OBJECTIVE

To provide a summary of the prognostic and predictive indicators of breast cancer, such as hormone receptors, HER2, and molecular gene signatures that currently help guide clinical decision making.

DATA SOURCES

Published articles from peer-reviewed journals in PubMed (US National Library of Medicine).

CONCLUSIONS

Emerging evidence shows promise that, in addition to hormone receptors and HER2 studies, evaluating tumors with gene expression profiling can provide additional prognostic and predictive information, further aiding clinical management and leading to a more personalized approach to treating breast cancer.

Integrative gene set analysis of multi-platform data with sample heterogeneity

MOTIVATION

Gene set analysis is a popular method for large-scale genomic studies. Because genes that have common biological features are analyzed jointly, gene set analysis often achieves better power and generates more biologically informative results. With the advancement of technologies, genomic studies with multi-platform data have become increasingly common. Several strategies have been proposed that integrate genomic data from multiple platforms to perform gene set analysis. To evaluate the performances of existing integrative gene set methods under various scenarios, we conduct a comparative simulation analysis based on The Cancer Genome Atlas breast cancer dataset.

RESULTS

We find that existing methods for gene set analysis are less effective when sample heterogeneity exists. To address this issue, we develop three methods for multi-platform genomic data with heterogeneity: two non-parametric methods, multi-platform Mann-Whitney statistics and multi-platform outlier robust T-statistics, and a parametric method, multi-platform likelihood ratio statistics. Using simulations, we show that the proposed multi-platform Mann-Whitney statistics method has higher power for heterogeneous samples and comparable performance for homogeneous samples when compared with the existing methods. Our real data applications to two datasets of The Cancer Genome Atlas also suggest that the proposed methods are able to identify novel pathways that are missed by other strategies.

AVAILABILITY AND IMPLEMENTATION

http://www4.stat.ncsu.edu/∼jytzeng/Software/Multiplatform_gene_set_analysis/

Molecularly targeted cancer therapy: some lessons from the past decade

The tremendous advances achieved in the understanding of cancer biology have delivered unprecedented progress in molecularly targeted cancer therapy in the past decade. The fast growing category of targeted anticancer agents available for clinical use is accompanied by a conceptual revolution in anticancer drug development. Nevertheless, molecularly targeted cancer therapy remains challenged by a high failure rate and an extremely small proportion of patients that can benefit. It is pivotal to take lessons from the past and seek new solutions. This review discusses conceptual progress and remaining challenges in molecularly targeted cancer therapy, and proposes feasible alternatives to increase chances of clinical success in the future.

STX140, but not paclitaxel, inhibits mammary tumour initiation and progression in C3(1)/SV40 T/t-antigen transgenic mice

Despite paclitxael's clinical success, treating hormone-refractory breast cancer remains challenging. Paclitaxel has a poor pharmacological profile, characterized by a low therapeutic index (TIX) caused by severe dose limiting toxicities, such as neutropenia and peripheral neuropathy. Consequently, new drugs are urgently required. STX140, a compound previously shown to have excellent efficacy against many tumors, is here compared to paclitaxel in three translational in vivo breast cancer models, a rat model of peripheral neuropathy, and through pharmacological testing. Three different in vivo mouse models of breast cancer were used; the metastatic 4T1 orthotopic model, the C3(1)/SV40 T-Ag model, and the MDA-MB-231 xenograft model. To determine TIX and pharmacological profile of STX140, a comprehensive dosing regime was performed in mice bearing MDA-MD-231 xenografts. Finally, peripheral neuropathy was examined using a rat plantar thermal hyperalgesia model. In the 4T1 metastatic model, STX140 and paclitaxel significantly inhibited primary tumor growth and lung metastases. All C3(1)/SV40 T-Ag mice in the control and paclitaxel treated groups developed palpable mammary cancer. STX140 blocked 47% of tumors developing and significantly inhibited growth of tumors that did develop. STX140 treatment caused a significant (P<0.001) survival advantage for animals in early and late intervention groups. Conversely, in C3(1)/SV40 T-Ag mice, paclitaxel failed to inhibit tumor growth and did not increase survival time. Furthermore, paclitaxel, but not STX140, induced significant peripheral neuropathy and neutropenia. These results show that STX140 has a greater anti-cancer efficacy, TIX, and reduced neurotoxicity compared to paclitaxel in C3(1)/SV40 T-Ag mice and therefore may be of significant benefit to patients with breast cancer.

Discordance in ERα, PR and HER2 receptor status across different distant breast cancer metastases within the same patient

BACKGROUND

We studied discordance in estrogen receptor alpha (ERα), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) status between multiple distant metastases from the same breast cancer patient.

MATERIAL AND METHODS

Multiple distant metastases from 55 female patients were stained for ERα, PR and HER2 by immunohistochemistry and in situ hybridization for confirmation of the HER2 status.

RESULTS

Different metastatic sites within the same patient showed discordance in ERα receptor status in 7.3% or 10.9% of patients (using a 10% or 1% threshold for positivity, respectively). For PR, 29.1% or 30.9% of patients showed discordance. Taking ERα and PR together, 36.4% of cases (both thresholds) showed discrepancy between metastases. In 10.9% (10% threshold) or 14.5% of patients (1% threshold), such discordance could have clinical consequences with regard to hormonal treatment. For HER2, there was 3.6% discordance on the immunohistochemical level but 0% on the gene level.

CONCLUSION

In a significant proportion of metastatic breast cancer patients, discordance in ERα and PR receptor status between different metastatic sites was observed. This implies that multiple metastases may need to be biopsied to optimally reassess receptors.

Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer

INTRODUCTION

Breast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice.

METHODS

More than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer 'stem' cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account.

RESULTS

The 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working.

CONCLUSIONS

With resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years.

Allogeneic tumor cell vaccines: the promise and limitations in clinical trials

The high mortality rate associated with cancer and its resistance to conventional treatments such as radiation and chemotherapy has led to the investigation of a variety of anti-cancer immunotherapies. The development of novel immunotherapies has been bolstered by the discovery of tumor-associated antigens (TAAs), through gene sequencing and proteomics. One such immunotherapy employs established allogeneic human cancer cell lines to induce antitumor immunity in patients through TAA presentation. Allogeneic cancer immunotherapies are desirable in a clinical setting due to their ease of production and availability. This review aims to summarize clinical trials of allogeneic tumor immunotherapies in various cancer types. To date, clinical trials have shown limited success due potentially to extensive degrees of inter- and intra-tumoral heterogeneity found among cancer patients. However, these clinical results provide guidance for the rational design and creation of more effective allogeneic tumor immunotherapies for use as monotherapies or in combination with other therapies.

Molecular and cellular heterogeneity in breast cancer: challenges for personalized medicine

Breast cancer is noted for disparate clinical behaviors and patient outcomes, despite common histopathological features at diagnosis. Molecular pathogenesis studies suggest that breast cancer is a collection of diseases with variable molecular underpinnings that modulate therapeutic responses, disease-free intervals, and long-term survival. Traditional therapeutic strategies for individual patients are guided by the expression status of the estrogen and progesterone receptors (ER and PR) and human epidermal growth factor receptor 2 (HER2). Although such methods for clinical classification have utility in selection of targeted therapies, short-term patient responses and long-term survival remain difficult to predict. Molecular signatures of breast cancer based on complex gene expression patterns have utility in prediction of long-term patient outcomes, but are not yet used for guiding therapy. Examination of the correspondence between these methods for breast cancer classification reveals a lack of agreement affecting a significant percentage of cases. To realize true personalized breast cancer therapy, a more complete analysis and evaluation of the molecular characteristics of the disease in the individual patient is required, together with an understanding of the contributions of specific genetic and epigenetic alterations (and their combinations) to management of the patient. Here, we discuss the molecular and cellular heterogeneity of breast cancer, the impact of this heterogeneity on practical breast cancer classification, and the challenges for personalized breast cancer treatment.

A multi-site feasibility study for personalized medicine in canines with osteosarcoma

Background

A successful therapeutic strategy, specifically tailored to the molecular constitution of an individual and their disease, is an ambitious objective of modern medicine. In this report, we highlight a feasibility study in canine osteosarcoma focused on refining the infrastructure and processes required for prospective clinical trials using a series of gene expression-based Personalized Medicine (PMed) algorithms to predict suitable therapies within 5 days of sample receipt.

Methods

Tumor tissue samples were collected immediately following limb amputation and shipped overnight from veterinary practices. Upon receipt (day 1), RNA was extracted from snap-frozen tissue, with an adjacent H&E section for pathological diagnosis. Samples passing RNA and pathology QC were shipped to a CLIA-certified laboratory for genomic profiling. After mapping of canine probe sets to human genes and normalization against a (normal) reference set, gene level Z-scores were submitted to the PMed algorithms. The resulting PMed report was immediately forwarded to the veterinarians. Upon receipt and review of the PMed report, feedback from the practicing veterinarians was captured.

Results

20 subjects were enrolled over a 5 month period. Tissue from 13 subjects passed both histological and RNA QC and were submitted for genomic analysis and subsequent PMed analysis and report generation. 11 of the 13 samples for which PMed reports were produced were communicated to the veterinarian within the target 5 business days. Of the 7 samples that failed QC, 4 were due to poor RNA quality, whereas 2 were failed following pathological review. Comments from the practicing veterinarians were generally positive and constructive, highlighting a number of areas for improvement, including enhanced education regarding PMed report interpretation, drug availability, affordable pricing and suitable canine dosing.

Conclusions

This feasibility trial demonstrated that with the appropriate infrastructure and processes it is possible to perform an in-depth molecular analysis of a patient’s tumor in support of real time therapeutic decision making within 5 days of sample receipt. A number of areas for improvement have been identified that should reduce the level of sample attrition and support clinical decision making.

Diagnostic and prognostic implications of the PAX8-PPARγ translocation in thyroid carcinomas-a TMA-based study of 226 cases

AIMS

Follicular thyroid carcinoma (FTC) has been a diagnostic challenge for decades. The PAX8-PPARγ rearrangement has been detected in FTC and classic papillary thyroid carcinomas (PTCs). The aims of this study were to assess the presence of PAX8-PPARγ by using tissue microarrays in a large cohort of different thyroid neoplasms, and to assess its diagnostic and prognostic implications.

METHODS AND RESULTS

Fluorescence in-situ hybridization (FISH) analysis for PAX8-PPARγ was performed on 226 thyroid tumours, comprising FTCs (n = 59), PTCs (n = 126), poorly differentiated thyroid carcinomas (PDs; n = 34), follicular thyroid adenomas (FTAs; n = 5), and follicular tumours of unknown malignant potential (FTUMPs; n = 2). PAX8-PPARγ was detected in 12% of FTCs, 1% of PTCs, 7% of PDs, and in both cases of FTUMP. There was no correlation between the extent of capsular or vascular invasion and PAX8-PPARγ, or between lymph node or haematogenous metastasis and PAX8-PPARγ. Overall survival (OS), tumour-specific survival (TSS) and relapse-free-survival (RFS) were not influenced by PAX8-PPARγ.

CONCLUSIONS

In this study, we demonstrate for the first time the presence of PAX8-PPARγ in PDs and FTUMPs, whereas in FTCs and PTCs the prevalence of PAX8-PPARγ is lower than previously reported. PAX8-PPARγ did not correlate with invasiveness or affect prognosis in any tumour type.

High intratumor genetic heterogeneity is related to worse outcome in patients with head and neck squamous cell carcinoma

BACKGROUND

Although the presence of genetic heterogeneity within the tumors of individual patients is established, it is unclear whether greater heterogeneity predicts a worse outcome. A quantitative measure of genetic heterogeneity based on next-generation sequencing (NGS) data, mutant-allele tumor heterogeneity (MATH), was previously developed and applied to a data set on head and neck squamous cell carcinoma (HNSCC). Whether this measure correlates with clinical outcome was not previously assessed.

METHODS

The authors examined the association between MATH and clinical, pathologic, and overall survival data for 74 patients with HNSCC for whom exome sequencing was completed.

RESULTS

High MATH (a MATH value above the median) was found to be significantly associated with shorter overall survival (hazards ratio, 2.5; 95% confidence interval, 1.3-4.8). MATH was similarly found to be associated with adverse outcomes in clinically high-risk patients with an advanced stage of disease, and in those with tumors classified as high risk on the basis of validated biomarkers including those that were negative for human papillomavirus or having disruptive tumor protein p53 mutations. In patients who received chemotherapy, the hazards ratio for high MATH was 4.1 (95% confidence interval, 1.6-10.2).

CONCLUSIONS

This novel measure of tumor genetic heterogeneity is significantly associated with tumor progression and adverse treatment outcomes, thereby supporting the hypothesis that higher genetic heterogeneity portends a worse clinical outcome in patients with HNSCC. The prognostic value of some known biomarkers may be the result of their association with high genetic heterogeneity. MATH provides a useful measure of that heterogeneity to be prospectively validated as NGS data from homogeneously treated patient cohorts become available.