Novel prognostic immunohistochemical biomarker panel for estrogen receptor-positive breast cancer

Differential expression of NAT1 pharmacogene in hormone receptor positive vs. negative female breast tumors may affect drug treatment

Studies have reported overexpression of NAT1 gene for xenobiotic metabolizing arylamine N -acetyltransferase type 1 in estrogen receptor positive breast tumors, and this association has been linked to patient chemoresistance and response to tamoxifen. We probed the expression of NAT1 , using quantitative reverse transcription PCR to screen clinically characterized breast cancer tissue cDNA arrays. Primers detecting all NAT1 alternative transcripts were used, and the protocol and results are reported according to consensus guidelines. The clinical information about 166 tumor samples screened is provided, including tumor stage, estrogen and progesterone receptor status and HER2 expression. NAT1 was found to be significantly ( P  < 0.001) upregulated in hormone receptor positive vs. negative tumors. No correlation was apparent between NAT1 and tumor stage or HER2 expression. Our findings demonstrate a strong correlation between the expression of NAT1 and steroid hormone receptors in breast tumors, supporting its possible utility as a pharmacogenetic biomarker or drug target. Of the two polymorphic NAT genes, NAT1 is the one primarily expressed in breast tissue, and is subjected to regulation by two differential promoters and more than one polyadenylation signal. Hormonal factors may enhance NAT1 gene expression at the transcriptional or epigenetic level, and tamoxifen has additionally been shown to inhibit NAT1 enzymatic activity. The outcome of tamoxifen treatment is also more favorable in patients with NAT1 overexpressing tumors. The study adds to the growing body of evidence implicating NAT1 in breast cancer and its pharmacological treatment.

CT109-SN-38, a Novel Antibody-drug Conjugate with Dual Specificity for CEACAM5 and 6, Elicits Potent Killing of Pancreatic Cancer Cells

BACKGROUND

CEACAM5 and CEACAM6 are glycosylphosphatidylinositol (GPI)- linked members of the carcinoembryonic antigen-related cell adhesion molecule (CEACAM) family, which are frequently upregulated in epithelial cancers where they contribute to invasion, metastasis, immune evasion, and resistance to anoikis. CT109 is a novel antibody with dual specificity to both CEACAM5 and 6.

OBJECTIVES

In this study, we aimed to perform the preclinical characterization of CT109 and antibody- drug conjugate (ADCs) derivatives of CT109, focusing on CT109-SN-38.

METHODS

CT109's cognate epitope was characterized by scanning mutagenesis. CT109 specificity and internalization kinetics were assessed by immunoblot and flow cytometry, respectively. Cognate antigen expression prevalence in colorectal cancer and normal tissue arrays was determined by immunohistochemistry. CT109 conjugations were generated by the reaction of reduced CT109 cysteines with maleimide-functionalized payload linkers. In vitro cytotoxic activity of CT109 ADCs was characterized on antigen-positive and negative pancreatic ductal adenocarcinoma cell (PDAC) lines using a luminometric viability assay. In vivo efficacy of CT109-SN-38 was assessed on a PDAC tumor xenograft model at 10 and 25 mg/kg concentrations.

RESULTS

CT109 was shown to bind a glycoepitope centered on N309. CT109 is internalized in the CEACAM5+/CEACAM6+ double-positive PDAC line, BxPC-3, with a t1/2 of 2.3 hours. CT109 ADCs elicit a dose and antigen-dependent cytotoxic effect, with CT109-SN-38 exhibiting an IC50 value of 21 nM in BxPC-3 cells. In a BxPC-3 tumor xenograft model, CT109-SN-38 reduced tumor growth and induced regression in 3/10 mice at a concentration 25 mg/kg.

CONCLUSION

These data suggest that further preclinical and clinical development of CT109-SN-38 is warranted.

NDRG1 is induced by antigen-receptor signaling but dispensable for B and T cell self-tolerance

Peripheral tolerance prevents the initiation of damaging immune responses by autoreactive lymphocytes. While tolerogenic mechanisms are tightly regulated by antigen-dependent and independent signals, downstream pathways are incompletely understood. N-myc downstream-regulated gene 1 (NDRG1), an anti-cancer therapeutic target, has previously been implicated as a CD4⁺ T cell clonal anergy factor. By RNA-sequencing, we identified Ndrg1 as the third most upregulated gene in anergic, compared to naïve follicular, B cells. Ndrg1 is upregulated by B cell receptor activation (signal one) and suppressed by co-stimulation (signal two), suggesting that NDRG1 may be important in B cell tolerance. However, though Ndrg1^-/- mice have a neurological defect mimicking NDRG1-associated Charcot-Marie-Tooth (CMT4d) disease, primary and secondary immune responses were normal. We find that B cell tolerance is maintained, and NDRG1 does not play a role in downstream responses during re-stimulation of in vivo antigen-experienced CD4⁺ T cells, demonstrating that NDGR1 is functionally redundant for lymphocyte anergy.

The Ni(II)-Binding Activity of the Intrinsically Disordered Region of Human NDRG1, a Protein Involved in Cancer Development

Nickel exposure is associated with tumors of the respiratory tract such as lung and nasal cancers, acting through still-uncharacterized mechanisms. Understanding the molecular basis of nickel-induced carcinogenesis requires unraveling the mode and the effects of Ni(II) binding to its intracellular targets. A possible Ni(II)-binding protein and a potential focus for cancer treatment is hNDRG1, a protein induced by Ni(II) through the hypoxia response pathway, whose expression correlates with higher cancer aggressiveness and resistance to chemotherapy in lung tissue. The protein sequence contains a unique C-terminal sequence of 83 residues (hNDRG1*C), featuring a three-times-repeated decapeptide, involved in metal binding, lipid interaction and post-translational phosphorylation. In the present work, the biochemical and biophysical characterization of unmodified hNDRG1*C was performed. Bioinformatic analysis assigned it to the family of the intrinsically disordered regions and the absence of secondary and tertiary structure was experimentally proven by circular dichroism and NMR. Isothermal titration calorimetry revealed the occurrence of a Ni(II)-binding event with micromolar affinity. Detailed information on the Ni(II)-binding site and on the residues involved was obtained in an extensive NMR study, revealing an octahedral paramagnetic metal coordination that does not cause any major change of the protein backbone, which is coherent with CD analysis. hNDRG1*C was found in a monomeric form by light-scattering experiments, while the full-length hNDRG1 monomer was found in equilibrium between the dimer and tetramer, both in solution and in human cell lines. The results are the first essential step for understanding the cellular function of hNDRG1*C at the molecular level, with potential future applications to clarify its role and the role of Ni(II) in cancer development.

A Knowledge-Based Discovery Approach Couples Artificial Neural Networks With Weight Engineering to Uncover Immune-Related Processes Underpinning Clinical Traits of Breast Cancer

Immune-related processes are important in underpinning the properties of clinical traits such as prognosis and drug response in cancer. The possibility to extract knowledge learned by artificial neural networks (ANNs) from omics data to explain cancer clinical traits is a very attractive subject for novel discovery. Recent studies using a version of ANNs called autoencoders revealed their capability to store biologically meaningful information indicating that autoencoders can be utilized as knowledge discovery platforms aside from their initial assigned use for dimensionality reduction. Here, we devise an innovative weight engineering approach and ANN platform called artificial neural network encoder (ANNE) using an autoencoder and apply it to a breast cancer dataset to extract knowledge learned by the autoencoder model that explains clinical traits. Intriguingly, the extracted biological knowledge in the form of gene-gene associations from ANNE shows immune-related components such as chemokines, carbonic anhydrase, and iron metabolism that modulate immune-related processes and the tumor microenvironment play important roles in underpinning breast cancer clinical traits. Our work shows that biological "knowledge" learned by an ANN model is indeed encoded as weights throughout its neuronal connections, and it is possible to extract learned knowledge via a novel weight engineering approach to uncover important biological insights.

Computer-assisted quantification of tumor-associated collagen signatures to improve the prognosis prediction of breast cancer

BACKGROUND

Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients.

METHODS

In this retrospective and multicenter study, we included 942 invasive breast cancer patients in both a training cohort (n = 355) and an internal validation cohort (n = 334) from one clinical center and in an external validation cohort (n = 253) from a different clinical center. TACS corresponding microscopic features (TCMFs) were firstly extracted from multiphoton images for each patient, and then least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust features to build a TCMF-score. Finally, the Cox proportional hazard regression analysis was used to evaluate the association of TCMF-score with disease-free survival (DFS).

RESULTS

TCMF-score is significantly associated with DFS in univariate Cox proportional hazard regression analysis. After adjusting for clinical variables by multivariate Cox regression analysis, the TCMF-score remains an independent prognostic indicator. Remarkably, the TCMF model performs better than the clinical (CLI) model in the three cohorts and is particularly outstanding in the ER-positive and lower-risk subgroups. By contrast, the TACS model is more suitable for the ER-negative and higher-risk subgroups. When the TACS and TCMF are combined, they could complement each other and perform well in all patients. As expected, the full model (CLI+TCMF+TACS) achieves the best performance (AUC 0.905, [0.873-0.938]; 0.896, [0.860-0.931]; 0.882, [0.840-0.925] in the three cohorts).

CONCLUSION

These results demonstrate that the TCMF-score is an independent prognostic factor for breast cancer, and the increased prognostic performance (TCMF+TACS-score) may help us develop more appropriate treatment protocols.

Advanced Approaches to Breast Cancer Classification and Diagnosis

The International Agency for Research on Cancer (IARC) has recently reported a 66% increase in the global number of cancer deaths since 1960. In the US alone, about one in eight women is expected to develop invasive breast cancer(s) (breast cancer) at some point in their lifetime. Traditionally, a BC diagnosis includes mammography, ultrasound, and some high-end molecular bioimaging. Unfortunately, these techniques detect BC at a later stage. So early and advanced molecular diagnostic tools are still in demand. In the past decade, various histological and immuno-molecular studies have demonstrated that BC is highly heterogeneous in nature. Its growth pattern, cytological features, and expression of key biomarkers in BC cells including hormonal receptor markers can be utilized to develop advanced diagnostic and therapeutic tools. A cancer cell's progression to malignancy exhibits various vital biomarkers, many of which are still underrepresented in BC diagnosis and treatment. Advances in genetics have also enabled the development of multigene assays to detect genetic heterogeneity in BC. However, thus far, the FDA has approved only four such biomarkers-cancer antigens (CA); CA 15-3, CA 27-29, Human epidermal growth factor receptor 2 (HER2), and circulating tumor cells (CTC) in assessing BC in body fluids. An adequately structured portable-biosensor with its non-invasive and inexpensive point-of-care analysis can quickly detect such biomarkers without significantly compromising its specificity and selectivity. Such advanced techniques are likely to discriminate between BC and a healthy patient by accurately measuring the cell shape, structure, depth, intracellular and extracellular environment, and lipid membrane compositions. Presently, BC treatments include surgery and systemic chemo- and targeted radiation therapy. A biopsied sample is then subjected to various multigene assays to predict the heterogeneity and recurrence score, thus guiding a specific treatment by providing complete information on the BC subtype involved. Thus far, we have seven prognostic multigene signature tests for BC providing a risk profile that can avoid unnecessary treatments in low-risk patients. Many comparative studies on multigene analysis projected the importance of integrating clinicopathological information with genomic-imprint analysis. Current cohort studies such as MINDACT, TAILORx, Trans-aTTOM, and many more, are likely to provide positive impact on long-term patient outcome. This review offers consolidated information on currently available BC diagnosis and treatment options. It further describes advanced biomarkers for the development of state-of-the-art early screening and diagnostic technologies.

The Potential Use of Tumour-Based Prognostic and Predictive Tools in Older Women with Primary Breast Cancer: A Narrative Review

A move is under way towards personalised cancer treatment, where tumour biology of an individual patient is examined to give unique predictive and prognostic information. This is extremely important in the setting of older women, who have treatment-specific goals which may differ from their younger counterparts, and may include conservation of quality of life rather than curative intent of treatment. One method employed to assist with this is the use of tumour-based prognostic and predictive tools. This article explores six of the most common tumour-based tools currently available on the market: MammaPrint, Oncotype DX, Mammostrat, Prosigna, EndoPredict, IHC4. The article discusses the creation and validation of these tools, their use and validation in older women, and future directions in the field. With the exception of Oncotype Dx, which has also been licensed for prediction of response from adjuvant chemotherapy, these tools have been licensed for use as prognostic tools only, mainly in the setting of adjuvant therapy following surgery. The evidence base for use in older women is strongest for Mammostrat and PAM50, although overall the evidence is much weaker than that in younger women. Where older women have been included in validation studies, this is often in small numbers, or the exact proportion of older women is unknown. In practice, all six of the tools are recommended to be utilised on surgical excision specimens, as well as in core needle biopsy (CNB) specimens in all of the tools except Mammostrat. This is extremely important in the setting of older women, of whom a large proportion do not undergo surgery. The suggested nature of the sample is formalin-fixed paraffin-embedded in all the tools except MammaPrint, which can also be performed on fresh-frozen samples. Future development of prognostic tools in older women with breast cancer should focus on treatment dilemmas specific to this population. This includes the decision of primary treatment between surgery or endocrine therapy and decisions regarding adjuvant therapy, in particular, chemotherapy.

LAT1 (SLC7A5) Overexpression in Negative Her2 Group of Breast Cancer: A Potential Therapy Target

Objective:

HER2 negative carcinomas of the breast pose a challenge for treatment due to redundancies in potential drug targets and poor patient outcomes. Our aim was to investigate the role of L-type amino acid transporter – LAT1 as a potential prognosticator and a drug target.

Methods:

In this retrospective work, we have studied the expression of LAT1 in 145 breast cancer tissues via immunohistochemistry. Overall survival analysis was used to evaluate patient outcome in various groups of our cohort.

Results:

Positive LAT1 expression was found in 27 (84.4%) luminal A subtype, 27 (64.3%) luminal B/triple positive subtype, 29 (82.9%) triple negative subtype, and 24 (66.7%) HER2-only positive subtype (p=0.1). Interestingly, negative correlation was found between LAT1 and HER2; where positive expression of LAT1 was found in 56 (83.6%) cases in negative HER2 group and 51 (65.4%) cases from positive HER2 group (p=0.01). Unfortunately, we were unable to report significant survival differences when LAT1 expression was studied in the negative HER2 group. Nevertheless, five incidents of mortality (out of 55) were reported in LAT1+/HER2- group compared to none in the LAT1-/HER2- group (N=11).

Conclusion:

Our findings of overexpression of LAT1 in negative HER2 group suggest a role of this protein as prognosticator and drug target in a challenging therapeutic cohort.

The solute carrier SLC7A8 is a marker of favourable prognosis in ER-positive low proliferative invasive breast cancer

PURPOSE

Breast cancer (BC) is a heterogeneous disease consisting of various subtypes, with different prognostic and therapeutic outcomes. The amino acid transporter, SLC7A8, is overexpressed in oestrogen receptor-positive BC. However, the consequence of this overexpression, in terms of disease prognosis, is still obscure. This study aimed to evaluate the biological and prognostic value of SLC7A8 in BC with emphasis on the intrinsic molecular subtypes.

METHODS

SLC7A8 was assessed at the genomic, using METABRIC data (n = 1980), and proteomic, using immunohistochemistry and TMA (n = 1562), levels in well-characterised primary BC cohorts. SLC7A8 expression was examined with clinicopathological parameters, molecular subtypes, and patient outcome.

RESULTS

SLC7A8 mRNA and SLC7A8 protein expression were strongly associated with good prognostic features, including small tumour size, low tumour grade, and good Nottingham Prognostic Index (NPI) (all P < 0.05). Expression of SLC7A8 mRNA was higher in luminal tumours compared to other subtypes (P < 0.001). High expression of SLC7A8 mRNA and SLC7A8 protein was associated with good patient outcome (P ≤ 0.001) but only in the low proliferative ER+/luminal A tumours (P = 0.01). In multivariate analysis, SLC7A8 mRNA and SLC7A8 protein were independent factors for longer breast cancer specific survival (P = 0.01 and P = 0.03), respectively.

CONCLUSION

SLC7A8 appears to play a role in BC and is a marker for favourable prognosis in the most predominant, ER+ low proliferative/luminal A, BC subtype. Functional assessment is necessary to reveal the specific role played by SLC7A8 in ER+ BC.

Cyclooxygenase-2 as a Biomarker with Diagnostic, Therapeutic, Prognostic, and Predictive Relevance in Small Animal Oncology

In canine and feline populations, the number of neoplasm cases continues to increase around the world. Attempts are being made in centres of research to identify new biomarkers that speed up and improve the quality of oncological diagnostics and therapy in human and animal tumour patients. Cyclooxygenase-2 (COX-2) is a promising biomarker with increasing relevance to human oncology, but as yet with less application in veterinary oncology. The expression of COX-2 increases significantly during pathological processes involving inflammation, pain or fever. It is also overexpressed in humans presenting various types of tumours and in selected types of tumours in animals, particularly in dogs. This article discusses the expression of COX-2 in canine and feline tumours, the importance of COX-2 as a biomarker with diagnostic, therapeutic, prognostic and predictive relevance in oncology, and the clinical significance of inhibiting COX-2 overexpression in tumours.

An integrative view on breast cancer signature panels

Introduction: Breast cancer is heterogeneous with distinct clinical outcomes. Diverse types of markers are available on the market for breast cancer prognosis, diagnosis, and therapeutics, with distinct assay approaches. These, though they enlarge our selection pool for characterizing breast cancer patients and help improve the precision on the therapeutics, they can complicate our understanding and choice of marker panels. Areas covered: This review aims at classifying the commonly used marker panels according to their functionalities and detection approaches, comparing their advantages and disadvantages, and identifying their shared features to gain a comprehensive understanding of the diversified molecular profiles that drive breast cancer heterogeneity. Expert opinion: Our effort will contribute as a guidebook for clinicians on the use of breast cancer signature panels for disease management, and for researchers on the establishment of novel marker panels with improved precision and reduced complexity. We propose that collectively analyzing all available marker panels is equally important as investigating on entirely novel marker panels. Advances in technologies capturing signals from multiple levels are of practical importance in breaking through limitations on translating markers into clinical use.

Prognostic & predictive factors for planning adjuvant chemotherapy of early-stage breast cancer

Breast cancer is a heterogeneous disease and may present with different clinical and biological characteristics. At present, breast cancer is divided into molecular subgroups besides its histopathological classification. Decision for adjuvant chemotherapy is made based on not only histopathological characteristics but also molecular and genomic characteristics using indices, guidelines and calculators in early-stage breast cancer. Making a treatment plan through all these prognostic and predictive methods according to risk categories aims at preventing unnecessary or useless treatments. In this review, an attempt to make a general assessment of prognostic and predictive methods is made which may be used for planning individualized therapy and also the comments of the guidelines used by the oncologists worldwide on these methods.

Trimodal distribution of arylamine N-acetyltransferase 1 mRNA in breast cancer tumors: association with overall survival and drug resistance

BACKGROUND

Arylamine N-acetyltransferase 1 (NAT1) is a drug metabolizing enzyme that has been associated with cancer cell proliferation in vitro and with survival in vivo. NAT1 expression has been associated with the estrogen receptor and it has been proposed as a prognostic marker for estrogen receptor positive cancers. However, little is known about the distribution of NAT1 mRNA across an entire patient population or its effects on outcomes. To address this, gene expression data from breast cancer patient cohorts were investigated to identify sub-populations based on the level of NAT1 expression. Patient survival and drug response was examined to determine whether NAT1 mRNA levels influenced any of these parameters.

RESULTS

NAT1 expression showed a trimodal distribution in breast cancer samples (n = 1980) but not in tumor tissue from ovarian, prostate, cervical or colorectal cancers. In breast cancer, NAT1 mRNA in each sub-population correlated with a separate set of genes suggesting different mechanisms of NAT1 gene regulation. Kaplan-Meier plots showed significantly better survival in patients with highest NAT1 mRNA compared to those with intermediate or low expression. While NAT1 expression was elevated in estrogen receptor-positive patients, it did not appear to be dependent on estrogen receptor expression. Overall survival was analyzed in patients receiving no treatment, hormone therapy or chemotherapy. NAT1 expression correlated strongly with survival in the first 5 years in those patients receiving chemotherapy but did not influence survival in the other two groups. This suggests that low NAT1 expression is associated with chemo-resistance. The sensitivity of NAT1 mRNA levels as a single parameter to identify non-responders to chemotherapy was 0.58 at a log(2) < 6.5.

CONCLUSIONS

NAT1 mRNA can be used to segregate breast cancer patients into sub-populations that demonstrate different overall survival. Moreover, low NAT1 expression shows a distinct poor response to chemotherapy. Analysis of NAT1 expression may be useful for identifying specific individuals who would benefit from alternative therapy or drug combinations. However, additional information is required to increase the sensitivity of identifying non-responders.

NDRG1 regulates neutral lipid metabolism in breast cancer cells

BACKGROUND

Altered lipid metabolism is an emerging hallmark of aggressive breast cancers. The N-myc downstream regulated gene (NDRG1) gene plays a critical role in peripheral nervous system myelination, as inactivating mutations cause severe demyelinating neuropathy. In breast cancer, elevated NDRG1 expression has been linked to clinical outcomes, but its functional role in breast cancer physiology has remained unclear.

METHODS

A meta-analysis of NDRG1 expression in multiple large publicly available genomic databases was conducted. Genome-wide expression correlation and Cox proportional hazards and Kaplan-Meier modeling of clinical outcomes associated with elevated expression were assessed. To study NDRG1 function, gene silencing and overexpression phenotypic studies were carried out in a panel of cell lines representing all major breast cancer molecular subtypes. Changes in cell proliferation, morphology, and neutral lipid accumulation due to altered NDRG1 expression were assessed by high throughput, quantitative microscopy. Comprehensive lipidomics mass spectrometry was applied to characterize global changes in lipid species due to NDRG1 silencing. Labeled fatty acids were used to monitor cellular fatty acid uptake and subcellular distribution under nutrient replete and starvation culture conditions.

RESULTS

NDRG1 overexpression correlated with glycolytic and hypoxia-associated gene expression, and was associated with elevated rates of metastasis and patient mortality. Silencing NDRG1 reduced cell proliferation rates, causing lipid metabolism dysfunction including increased fatty acid incorporation into neutral lipids and lipid droplets. Conversely, NDRG1 expression minimized lipid droplet formation under nutrient replete and starvation conditions.

CONCLUSIONS

Here we report that NDRG1 contributes to breast cancer aggressiveness by regulating the fate of lipids in cells that exhibit an altered lipid metabolic phenotype. In line with its role in promoting myelination and its association with altered metabolism in cancer, our findings show that NDRG1 is a critical regulator of lipid fate in breast cancer cells. The association between NDRG1 and poor prognosis in breast cancer suggests it should play a more prominent role in patient risk assessment. The function of NDRG1 in breast cancer lipid metabolism may represent a promising therapeutic approach in the future.

Current issues with luminal subtype classification in terms of prediction of benefit from endocrine therapy in early breast cancer

Endocrine therapy for oestrogen receptor-positive (ER+) breast cancer (BC) is arguably the most successful targeted cancer therapy to date. Nevertheless, resistance to endocrine therapy still occurs in a significant proportion of patients, limiting its clinical utility. ER+ or luminal BC, which represents approximately three-quarters of all breast malignancies, are biologically heterogeneous, with no distinct, clinically defined subclasses able to predict the benefit of endocrine therapy in early settings. To improve patient outcomes there is a clear need for improved understanding of the biology of the luminal BC, with subsequent translation into more effective methods of diagnosis to identify potential predictive biomarkers for endocrine therapy. This review summarises current knowledge of factors predictive of benefit of endocrine therapy and discusses why molecular classification systems of BC have yet to be translated into the clinic.

Targeting invadopodia for blocking breast cancer metastasis

Dissemination of cancer cells from the primary tumor and their spread to distant sites of the body is the leading cause of mortality in metastatic cancer patients. Metastatic cancer cells invade surrounding tissues and blood vessels by forming F-actin-rich protrusions known as invadopodia, which degrade the extracellular matrix and enable invasion of tumor cells through it. Invadopodia have now been observed in vivo, and recent evidence demonstrates direct molecular links between assembly of invadopodia and cancer metastasis in both mouse models and in human patients. While significant progress has been achieved in the last decade in understanding the molecular mechanisms and signaling pathways regulating invadopodia formation and function, the application of this knowledge to development of prognostic and therapeutic approaches for cancer metastasis has not been discussed before. Here, we provide a detailed overview of current prognostic markers and tests for cancer metastasis and discuss their advantages, disadvantages, and their predicted efficiency. Using bioinformatic patient database analysis, we demonstrate, for the first time, a significant correlation between invadopodia-associated genes to breast cancer metastasis, suggesting that invadopodia could be used as both a prognostic marker and as a therapeutic target for blocking cancer metastasis. We include here a novel network interaction map of invadopodia-associated proteins with currently available inhibitors, demonstrating a central role for the recently identified EGFR-Pyk2-Src-Arg-cortactin invadopodial pathway, to which re-purposing of existent inhibitors could be used to block breast cancer metastasis. We then present an updated overview of current cancer-related clinical trials, demonstrating the negligible number of trials focusing on cancer metastasis. We also discuss the difficulties and complexity of performing cancer metastasis clinical trials, and the possible development of anti-metastasis drug resistance when using a prolonged preventive treatment with invadopodia inhibitors. This review presents a new perspective on invadopodia-mediated tumor invasiveness and may lead to the development of novel prognostic and therapeutic approaches for cancer metastasis.

Informative three-dimensional survey of cell/tissue architectures in thick paraffin sections by simple low-vacuum scanning electron microscopy

Recent advances in bio-medical research, such as the production of regenerative organs from stem cells, require three-dimensional analysis of cell/tissue architectures. High-resolution imaging by electron microscopy is the best way to elucidate complex cell/tissue architectures, but the conventional method requires a skillful and time-consuming preparation. The present study developed a three-dimensional survey method for assessing cell/tissue architectures in 30-µm-thick paraffin sections by taking advantage of backscattered electron imaging in a low-vacuum scanning electron microscope. As a result, in the kidney, the podocytes and their processes were clearly observed to cover the glomerulus. The 30 µm thickness facilitated an investigation on face-side (instead of sectioned) images of the epithelium and endothelium, which are rarely seen within conventional thin sections. In the testis, differentiated spermatozoa were three-dimensionally assembled in the middle of the seminiferous tubule. Further application to vascular-injury thrombus formation revealed the distinctive networks of fibrin fibres and platelets, capturing the erythrocytes into the thrombus. The four-segmented BSE detector provided topographic bird’s-eye images that allowed a three-dimensional understanding of the cell/tissue architectures at the electron-microscopic level. Here, we describe the precise procedures of this imaging method and provide representative electron micrographs of normal rat organs, experimental thrombus formation, and three-dimensionally cultured tumour cells.

A 35-gene signature discriminates between rapidly- and slowly-progressing glioblastoma multiforme and predicts survival in known subtypes of the cancer

BACKGROUND

Gene expression can be employed for the discovery of prognostic gene or multigene signatures cancer. In this study, we assessed the prognostic value of a 35-gene expression signature selected by pathway and machine learning based methods in adjuvant therapy-linked glioblastoma multiforme (GBM) patients from the Cancer Genome Atlas.

METHODS

Genes with high expression variance was subjected to pathway enrichment analysis and those having roles in chemoradioresistance pathways were used in expression-based feature selection. A modified Support Vector Machine Recursive Feature Elimination algorithm was employed to select a subset of these genes that discriminated between rapidly-progressing and slowly-progressing patients.

RESULTS

Survival analysis on TCGA samples not used in feature selection and samples from four GBM subclasses, as well as from an entirely independent study, showed that the 35-gene signature discriminated between the survival groups in all cases (p<0.05) and could accurately predict survival irrespective of the subtype. In a multivariate analysis, the signature predicted progression-free and overall survival independently of other factors considered.

CONCLUSION

We propose that the performance of the signature makes it an attractive candidate for further studies to assess its utility as a clinical prognostic and predictive biomarker in GBM patients. Additionally, the signature genes may also be useful therapeutic targets to improve both progression-free and overall survival in GBM patients.

Amino Acid Transporters and Glutamine Metabolism in Breast Cancer

Amino acid transporters are membrane transport proteins, most of which are members of the solute carrier families. Amino acids are essential for the survival of all types of cells, including tumor cells, which have an increased demand for nutrients to facilitate proliferation and cancer progression. Breast cancer is the most common malignancy in women worldwide and is still associated with high mortality rates, despite improved treatment strategies. Recent studies have demonstrated that the amino acid metabolic pathway is altered in breast cancer and that amino acid transporters affect tumor growth and progression. In breast cancer, glutamine is one of the key nutrients, and glutamine metabolism is closely related to the amino acid transporters. In this review, we focus on amino acid transporters and their roles in breast cancer. We also highlight the different subsets of upregulated amino acid transporters in breast cancer and discuss their potential applications as treatment targets, cancer imaging tracers, and drug delivery components. Glutamine metabolism as well as its regulation and therapeutic implication in breast cancer are also discussed.

High N-Acetyltransferase 1 Expression Is Associated with Estrogen Receptor Expression in Breast Tumors, but Is not Under Direct Regulation by Estradiol, 5α-androstane-3β,17β-Diol, or Dihydrotestosterone in Breast Cancer Cells

N-acetyltransferase 1 (NAT1) is an enzyme that metabolizes carcinogens, which suggests a potential role in breast carcinogenesis. High NAT1 expression in breast tumors is associated with estrogen receptor α (ERα+) and the luminal subtype. We report that NAT1 mRNA transcript, protein, and enzyme activity were higher in human breast tumors with high expression of ERα/ESR1 compared with normal breast tissue. There was a strong correlation between NATb promoter and NAT1 protein expression/enzyme activity. High NAT1 expression in tumors was not the result of adipocytes, as evidenced by low perilipin (PLIN) expression. ESR1, NAT1, and XBP1 expression were associated in tumor biopsies. Direct regulation of NAT1 transcription by estradiol (E₂) was investigated in ERα (+) MCF-7 and T47D breast cancer cells. E₂ did not increase NAT1 transcript expression but increased progesterone receptor expression in a dose-dependent manner. Likewise, NAT1 transcript levels were not increased by dihydrotestosterone (DHT) or 5α-androstane-3β, (3β-adiol) 17β-diol. Dithiothreitol increased levels of the activated, spliced XBP1 in ERα (+) MCF-7 and T47D breast cancer cells but did not affect NAT1 or ESR1 expression. We conclude that NAT1 expression is not directly regulated by E₂, DHT, 3β-adiol, or dithiothreitol despite high NAT1 and ESR1 expression in luminal A breast cancer cells, suggesting that ESR1, XBP1, and NAT1 expression may share a common transcriptional network arising from the luminal epithelium associated with better survival in breast cancer. Clusters of high-expression genes, including NAT1, in breast tumors might serve as potential targets for novel therapeutic drug development.

Gene expression profiling to predict recurrence of advanced squamous cell carcinoma of the tongue: discovery and external validation

OBJECTIVES

To establish a prognostic signature for locally advanced tongue squamous cell carcinoma (TSCC) patients treated with surgery.

RESULTS

In the discovery study, unsupervised hierarchical clustering analysis identified two clusters which differentiated the Kaplan-Meier curves of RFS [median RFS, 111 days vs. not reached; log-rank test, P = 0.023]. The 30 genes identified were combined into a dichotomous PI. In the validation cohort, classification according to the PI was associated with RFS [median RFS, 754 days vs. not reached; log-rank test, P = 0.026 in GSE31056] and DSS [median DSS, 540 days vs. not reached; log-rank test, P = 0.046 in GSE42743 and 443 days vs. not reached; P < 0.001 in GSE41613]. Among genes, positive immunohistochemical staining of cytokeratin 4 was associated with favorable prognostic values for RFS (hazard ratio (HR), 0.591, P = 0.045) and DSS (HR, 0.333, P = 0.004).

MATERIALS AND METHODS

We conducted gene expression profiling of 26 clinicopathologically homogeneous advanced TSCC tissue samples using cDNA microarray as a discovery study. Candidate genes were screened using clustering analysis and univariate Cox regression analysis for relapse-free survival (RFS). These were combined into a prognostic index (PI), which was validated using three public microarray datasets of tongue and oral cancer (123 patients). Some genes identified in discovery were immunohistochemically examined for protein expression in another 127 TSCC patients.

CONCLUSION

We identified robust molecular markers that showed significant associations with prognosis in TSCC patients. Gene expression profiling data were successfully converted to protein expression profiling data.

Clinical significance of NDRG3 in patients with breast cancer

AIM

The expression level of NDRG3 gene is investigated among breast cancer (BC) patients.

METHODS

Real-time quantitative PCR was performed.

RESULTS

 NDRG3 was downregulated in BC patients particularly in advanced stage of the disease. HER2 status was significantly correlated with the expression of NDRG3. Also, triple-negative BC patients showed low levels of NDRG3 expression in comparison to other subtypes. Lastly, the expression of NDRG3 had significant impact on survival, with NDRG3 downregulated patients having the worst event-free survival rate among others.

CONCLUSION

We have presented that NDRG3 might be a tumor suppressor candidate. NDRG3 downregulation might be involved in the tumorigenesis and development of invasive BC in an advanced phase of the disease.

N-myc downstream regulated gene 1(NDRG1) promotes the stem-like properties of lung cancer cells through stabilized c-Myc

Tumor-initiating cells (TICs) play an important role in tumorigenesis and development for many various tissue origin cancers including non-small cell lung cancer (NSCLC). However, the mechanism to maintain TICs in NSCLC is still largely unknown. Here, we evaluated differences of mRNA expression between parental and oncosphere cells that enriched TICs. We found that N-myc downstream regulated gene 1(NDRG1) was upregulated in oncosphere cells derived from human NSCLC cell lines and primary NSCLC cells. NDRG1 promoted stem-like properties of LTICs in NSCLC including iPSC (induced pluripotent stem cell) factors (OCT4, SOX2, KLF4, and C-MYC), the spheres-forming ability and the tumorigenicity of NSCLC. NDRG1 prevented the degradation of c-Myc through Skp2-mediated ubiquitination. NDRG1 directly interacted with Skp2, and decreased phosphorylation of Skp2 through inactivation of CDK2. Finally, we confirmed that NDRG1 was negatively correlated with survival and prognosis. Thus, our findings indicate that NDRG1 is a potential target for eradicating TICs in NSCLC.

Pathologic diagnosis of breast cancer patients: evolution of the traditional clinical-pathologic paradigm toward "precision" cancer therapy

We present an updated account of breast cancer treatment and of progress toward "precision" cancer therapy; we focus on new developments in diagnostic molecular pathology and breast cancer that have emerged during the past 2 years. Increasing awareness of new prognostic and predictive methodologies, and introduction of next generation sequencing has increased understanding of both tumor biology and clinical behavior, which offers the possibility of more appropriate therapeutic choices. It remains unclear which of these testing methodologies provides the most informative and cost-effective actionable results for predictive and prognostic pathology. It is likely, however, that an integrated "step-wise" approach that uses the traditional clinical-pathologic paradigms coordinated with molecular characterization of breast tumor tissue, will offer the most comprehensive and cost-effective options for individualized, "precision" therapy for patients with breast cancer.

Development of a Postcolumn Infused-Internal Standard Liquid Chromatography Mass Spectrometry Method for Quantitative Metabolomics Studies

Quantitative metabolomics has become much more important in clinical research in recent years. Individual differences in matrix effects (MEs) and the injection order effect are two major factors that reduce the quantification accuracy in liquid chromatography-electrospray ionization-mass spectrometry-based (LC-ESI-MS) metabolomics studies. This study proposed a postcolumn infused-internal standard (PCI-IS) combined with a matrix normalization factor (MNF) strategy to improve the analytical accuracy of quantitative metabolomics. The PCI-IS combined with the MNF method was applied for a targeted metabolomics study of amino acids (AAs). D8-Phenylalanine was used as the PCI-IS, and it was postcolumn-infused into the ESI interface for calibration purposes. The MNF was used to bridge the AA response in a standard solution with the plasma samples. The MEs caused signal changes that were corrected by dividing the AA signal intensities by the PCI-IS intensities after adjustment with the MNF. After the method validation, we evaluated the method applicability for breast cancer research using 100 plasma samples. The quantification results revealed that the 11 tested AAs exhibit an accuracy between 88.2 and 110.7%. The principal component analysis score plot revealed that the injection order effect can be successfully removed, and most of the within-group variation of the tested AAs decreased after the PCI-IS correction. Finally, targeted metabolomics studies on the AAs showed that tryptophan was expressed more in malignant patients than in the benign group. We anticipate that a similar approach can be applied to other endogenous metabolites to facilitate quantitative metabolomics studies.

OPTIMA prelim: a randomised feasibility study of personalised care in the treatment of women with early breast cancer

BACKGROUND

There is uncertainty about the chemotherapy sensitivity of some oestrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancers. Multiparameter assays that measure the expression of several tumour genes simultaneously have been developed to guide the use of adjuvant chemotherapy for this breast cancer subtype. The assays provide prognostic information and have been claimed to predict chemotherapy sensitivity. There is a dearth of prospective validation studies. The Optimal Personalised Treatment of early breast cancer usIng Multiparameter Analysis preliminary study (OPTIMA prelim) is the feasibility phase of a randomised controlled trial (RCT) designed to validate the use of multiparameter assay directed chemotherapy decisions in the NHS.

OBJECTIVES

OPTIMA prelim was designed to establish the acceptability to patients and clinicians of randomisation to test-driven treatment assignment compared with usual care and to select an assay for study in the main RCT.

DESIGN

Partially blinded RCT with adaptive design.

SETTING

Thirty-five UK hospitals.

PARTICIPANTS

Patients aged ≥ 40 years with surgically treated ER-positive HER2-negative primary breast cancer and with 1-9 involved axillary nodes, or, if node negative, a tumour at least 30 mm in diameter.

INTERVENTIONS

Randomisation between two treatment options. Option 1 was standard care consisting of chemotherapy followed by endocrine therapy. In option 2, an Oncotype DX(®) test (Genomic Health Inc., Redwood City, CA, USA) performed on the resected tumour was used to assign patients either to standard care [if 'recurrence score' (RS) was > 25] or to endocrine therapy alone (if RS was ≤ 25). Patients allocated chemotherapy were blind to their randomisation.

MAIN OUTCOME MEASURES

The pre-specified success criteria were recruitment of 300 patients in no longer than 2 years and, for the final 150 patients, (1) an acceptance rate of at least 40%; (2) recruitment taking no longer than 6 months; and (3) chemotherapy starting within 6 weeks of consent in at least 85% of patients.

RESULTS

Between September 2012 and 3 June 2014, 350 patients consented to join OPTIMA prelim and 313 were randomised; the final 150 patients were recruited in 6 months, of whom 92% assigned chemotherapy started treatment within 6 weeks. The acceptance rate for the 750 patients invited to participate was 47%. Twelve out of the 325 patients with data (3.7%, 95% confidence interval 1.7% to 5.8%) were deemed ineligible on central review of receptor status. Interviews with researchers and recordings of potential participant consultations made as part of the integral qualitative recruitment study provided insights into recruitment barriers and led to interventions designed to improve recruitment. Patient information was changed as the result of feedback from three patient focus groups. Additional multiparameter analysis was performed on 302 tumour samples. Although Oncotype DX, MammaPrint(®)/BluePrint(®) (Agendia Inc., Irvine, CA, USA), Prosigna(®) (NanoString Technologies Inc., Seattle, WA, USA), IHC4, IHC4 automated quantitative immunofluorescence (AQUA(®)) [NexCourse BreastTM (Genoptix Inc. Carlsbad, CA, USA)] and MammaTyper(®) (BioNTech Diagnostics GmbH, Mainz, Germany) categorised comparable numbers of tumours into low- or high-risk groups and/or equivalent molecular subtypes, there was only moderate agreement between tests at an individual tumour level (kappa ranges 0.33-0.60 and 0.39-0.55 for tests providing risks and subtypes, respectively). Health economics modelling showed the value of information to the NHS from further research into multiparameter testing is high irrespective of the test evaluated. Prosigna is currently the highest priority for further study.

CONCLUSIONS

OPTIMA prelim has achieved its aims of demonstrating that a large UK clinical trial of multiparameter assay-based selection of chemotherapy in hormone-sensitive early breast cancer is feasible. The economic analysis shows that a trial would be economically worthwhile for the NHS. Based on the outcome of the OPTIMA prelim, a large-scale RCT to evaluate the clinical effectiveness and cost-effectiveness of multiparameter assay-directed chemotherapy decisions in hormone-sensitive HER2-negative early breast would be appropriate to take place in the NHS.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN42400492.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 10. See the NIHR Journals Library website for further project information. The Government of Ontario funded research at the Ontario Institute for Cancer Research. Robert C Stein received additional support from the NIHR University College London Hospitals Biomedical Research Centre.

Lipocalin 2 (LCN2) is a promising target for cholangiocarcinoma treatment and bile LCN2 level is a potential cholangiocarcinoma diagnostic marker

Cholangiocarcinoma (CCA) is a devastating disease due to resistance to traditional chemotherapies and radiotherapies. New therapeutic strategies against CCA are urgently needed. This study investigated the role of lipocalin-2 (LCN2) in human cholangiocarcinoma as a potential therapeutic target and diagnostic marker. So far, the role of LCN2 in cancer is still controversial and studies regarding the role of LCN2 in CCA are limited. LCN2 knockdown inhibited CCA cell growth in vitro and in vivo through induction of cell cycle arrest at G0/G1 phases and decreased metastatic potential due to repression of epithelial-mesenchymal transition (EMT). Overexpression of LCN2 in CCA cells increased cell metastatic potential. We showed for the first time that the N-myc downstream regulated gene 1 (NDRG1) and NDRG2, known as tumor suppressor genes, are negatively regulated by LCN2 in CCA cells. LCN2 concentration in bile was higher in patients with CCA than that in patients with gallstones, with a cutoff value of 20.08 ng/ml making this a potential diagnostic marker. Higher LCN2 expression was associated with worse survival in patients with CCA. LCN2 is a promising target for CCA treatment and bile LCN2 level is a potential diagnostic marker for CCA.

Cancer Hallmarks, Biomarkers and Breast Cancer Molecular Subtypes

Breast cancer is a complex disease encompassing multiple tumor entities, each characterized by distinct morphology, behavior and clinical implications. Besides estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2, novel biomarkers have shown their prognostic and predictive values, complicating our understanding towards to the heterogeneity of such cancers. Ten cancer hallmarks have been proposed by Weinberg to characterize cancer and its carcinogenesis. By reviewing biomarkers and breast cancer molecular subtypes, we propose that the divergent outcome observed from patients stratified by hormone status are driven by different cancer hallmarks. 'Sustaining proliferative signaling' further differentiates cancers with positive hormone receptors. 'Activating invasion and metastasis' and 'evading immune destruction' drive the differentiation of triple negative breast cancers. 'Resisting cell death', 'genome instability and mutation' and 'deregulating cellular energetics' refine breast cancer classification with their predictive values. 'Evading growth suppressors', 'enabling replicative immortality', 'inducing angiogenesis' and 'tumor-promoting inflammation' have not been involved in breast cancer classification which need more focus in the future biomarker-related research. This review novels in its global view on breast cancer heterogeneity, which clarifies many confusions in this field and contributes to precision medicine.

FKBPL: a marker of good prognosis in breast cancer

FK506-binding protein-like (FKBPL) has established roles as an anti-tumor protein, with a therapeutic peptide based on this protein, ALM201, shortly entering phase I/II clinical trials. Here, we evaluated FKBPL's prognostic ability in primary breast cancer tissue, represented on tissue microarrays (TMA) from 3277 women recruited into five independent retrospective studies, using immunohistochemistry (IHC). In a meta-analysis, FKBPL levels were a significant predictor of BCSS; low FKBPL levels indicated poorer breast cancer specific survival (BCSS) (hazard ratio (HR) = 1.30, 95% confidence interval (CI) 1.14–1.49, p < 0.001). The prognostic impact of FKBPL remained significant after adjusting for other known prognostic factors (HR = 1.25, 95% CI 1.07–1.45, p = 0.004). For the sub-groups of 2365 estrogen receptor (ER) positive patients and 1649 tamoxifen treated patients, FKBPL was significantly associated with BCSS (HR = 1.34, 95% CI 1.13–1.58, p < 0.001, and HR = 1.25, 95% CI 1.04–1.49, p = 0.02, respectively). A univariate analysis revealed that FKBPL was also a significant predictor of relapse free interval (RFI) within the ER positive patient group, but it was only borderline significant within the smaller tamoxifen treated patient group (HR = 1.32 95% CI 1.05–1.65, p = 0.02 and HR = 1.23 95% CI 0.99–1.54, p = 0.06, respectively). The data suggests a role for FKBPL as a prognostic factor for BCSS, with the potential to be routinely evaluated within the clinic.

Expression of a-Tocopherol-Associated protein (TAP) is associated with clinical outcome in breast cancer patients

BACKGROUND

The role of vitamin E in breast cancer prevention and treatment has been widely investigated, and the different tocopherols that comprise this nutrient have been shown to have divergent associations with cancer outcome. Our previous studies have shown that α-Tocopherol-associated protein (TAP), a vitamin E binding protein, may function as a tumor suppressor-like factor in breast carcinogenesis. The current study addresses the association of TAP expression with breast cancer clinical outcomes.

METHODS

Immunohistochemical stain for TAP was applied to a tissue microarray from a breast cancer cohort consisting of 271 patients with a median follow-up time of 5.2 years. The expression of TAP in tumor cells was compared with patient's clinical outcome at 5 years after diagnosis. The potential role of TAP in predicting outcome was also assessed in clinically relevant subsets of the cohort. In addition, we compared TAP expression and Oncotype DX scores in an independent breast cancer cohort consisting of 71 cases.

RESULTS

We demonstrate that the expression of TAP was differentially expressed within the breast cancer cohort, and that ER+/PR ± tumors were more likely to exhibit TAP expression. TAP expression was associated with an overall lower recurrence rate and a better 5-year survival rate. This association was primarily in patients with ER+ tumors; exploratory analysis showed that this association was strongest in patients with node-positive tumors and was independent of stage and treatment with chemotherapy. TAP expression in ER/PR negative or triple negative tumors had no association with clinical outcome. In addition, we did not observe an association between TAP expression and Oncotype DX recurrence score.

CONCLUSIONS

The significant positive association we found for α-Tocopherol-associated protein with outcome in breast cancer may help to better define and explain studies addressing α-tocopherol's association with cancer risk and outcome. Additionally, further studies to validate and extend these findings may allow TAP to serve as a breast-specific prognostic marker in breast cancer patients, especially in those patients with ER+ tumors.

High Expression of Three-Gene Signature Improves Prediction of Relapse-Free Survival in Estrogen Receptor-Positive and Node-Positive Breast Tumors

The objective of the present study was to validate prognostic gene signature for estrogen receptor alpha-positive (ER03B1+) and lymph node (+) breast cancer for improved selection of patients for adjuvant therapy. In our previous study, we identified a group of seven genes (GATA3, NTN4, SLC7A8, ENPP1, MLPH, LAMB2, and PLAT) that show elevated messenger RNA (mRNA) expression levels in ERα (+) breast cancer patient samples. The prognostic values of these genes were evaluated using gene expression data from three public data sets of breast cancer patients (n = 395). Analysis of ERα (+) breast cancer cohort (n = 195) showed high expression of GATA3, NTN4, and MLPH genes significantly associated with longer relapse-free survival (RFS). Next cohort of ERα (+) and node (+) samples (n = 109) revealed high mRNA expression of GATA3, SLC7A8, and MLPH significantly associated with longer RFS. Multivariate analysis of combined three-gene signature for ERα (+) cohort, and ERα (+) and node (+) cohorts showed better hazard ratio than individual genes. The validated three-gene signature sets for ERα (+) cohort, and ERα (+) and node (+) cohort may have potential clinical utility since they demonstrated predictive and prognostic ability in three independent public data sets.

Using second harmonic generation to predict patient outcome in solid tumors

BACKGROUND

Over-treatment of estrogen receptor positive (ER+), lymph node-negative (LNN) breast cancer patients with chemotherapy is a pressing clinical problem that can be addressed by improving techniques to predict tumor metastatic potential. Here we demonstrate that analysis of second harmonic generation (SHG) emission direction in primary tumor biopsies can provide prognostic information about the metastatic outcome of ER+, LNN breast cancer, as well as stage 1 colorectal adenocarcinoma.

METHODS

SHG is an optical signal produced by fibrillar collagen. The ratio of the forward-to-backward emitted SHG signals (F/B) is sensitive to changes in structure of individual collagen fibers. F/B from excised primary tumor tissue was measured in a retrospective study of LNN breast cancer patients who had received no adjuvant systemic therapy and related to metastasis-free survival (MFS) and overall survival (OS) rates. In addition, F/B was studied for its association with the length of progression-free survival (PFS) in a subgroup of ER+ patients who received tamoxifen as first-line treatment for recurrent disease, and for its relation with OS in stage I colorectal and stage 1 lung adenocarcinoma patients.

RESULTS

In 125 ER+, but not in 96 ER-negative (ER-), LNN breast cancer patients an increased F/B was significantly associated with a favorable MFS and OS (log rank trend for MFS: p = 0.004 and for OS: p = 0.03). On the other hand, an increased F/B was associated with shorter PFS in 60 ER+ recurrent breast cancer patients treated with tamoxifen (log rank trend p = 0.02). In stage I colorectal adenocarcinoma, an increased F/B was significantly related to poor OS (log rank trend p = 0.03), however this relationship was not statistically significant in stage I lung adenocarcinoma.

CONCLUSION

Within ER+, LNN breast cancer specimens the F/B can stratify patients based upon their potential for tumor aggressiveness. This offers a "matrix-focused" method to predict metastatic outcome that is complementary to genomic "cell-focused" methods. In combination, this and other methods may contribute to improved metastatic prediction, and hence may help to reduce patient over-treatment.

Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential

BACKGROUND

Development of human cancer can proceed through the accumulation of different genetic changes affecting the structure and function of the genome. Combined analyses of molecular data at multiple levels, such as DNA copy-number alteration, mRNA and miRNA expression, can clarify biological functions and pathways deregulated in cancer. The integrative methods that are used to investigate these data involve different fields, including biology, bioinformatics, and statistics.

RESULTS

These methodologies are presented in this review, and their implementation in breast cancer is discussed with a focus on integration strategies. We report current applications, recent studies and interesting results leading to the identification of candidate biomarkers for diagnosis, prognosis, and therapy in breast cancer by using both individual and combined analyses.

CONCLUSION

This review presents a state of art of the role of different technologies in breast cancer based on the integration of genetics and epigenetics, and shares some issues related to the new opportunities and challenges offered by the application of such integrative approaches.

Combined Immunohistochemistry of PLK1, p21, and p53 for Predicting TP53 Status: An Independent Prognostic Factor of Breast Cancer

It is difficult to predict the TP53 status by p53 immunohistochemistry (IHC). We aimed to improve the accuracy of p53 IHC with p53-regulated proteins for predicting the TP53 mutation status. TP53 mutations were detected in 19 of 38 breast cancer patients (50%). Five of 7 cases of protein-truncating mutation of TP53 were completely negative for p53 IHC, whereas 11 of 12 cases of TP53 point mutation were strongly positive for p53 IHC. Therefore, to avoid false negatives, we extracted p53-dependent universally downregulated genes using microarray analysis from 38 breast cancer patients and 2 p53-inducible cell lines. From 9 commonly repressed genes, we evaluated 3 genes, baculoviral IAP repeat-containing 5 (BIRC5), polo-like kinase 1 (PLK1), and BUB1 mitotic checkpoint serine/threonine kinase (BUB1), which were previously identified as p53-dependent repressed genes. PLK1≥Allred total score (TS) 5 showed the highest correlation with TP53 mutation. To decrease false positivity, we evaluated p21 IHC. Although strong staining of p21 was observed in 4 cases (10.5%), all 4 were wild-type TP53. Thus, p53 mutation-like (p53mt-like) IHC was identified by p53 TS7,8 with PLK1≥TS 5 and p21 TS≤6. p53 mt-like IHC correlated with TP53 mutation (predictive value=0.94). In other 157 breast cancer cases, p53 mt-like was an independent prognostic marker in multivariate analysis and a strong prognostic factor. Stratification with p53 mt-like IHC identified patients with a poorer prognosis. In conclusion, we identified reliable IHC conditions to predict the TP53 status of breast cancer patients.

Reciprocal regulation of amino acid import and epigenetic state through Lat1 and EZH2

Lat1 (SLC7A5) is an amino acid transporter often required for tumor cell import of essential amino acids (AA) including Methionine (Met). Met is the obligate precursor of S-adenosylmethionine (SAM), the methyl donor utilized by all methyltransferases including the polycomb repressor complex (PRC2)-specific EZH2. Cell populations sorted for surface Lat1 exhibit activated EZH2, enrichment for Met-cycle intermediates, and aggressive tumor growth in mice. In agreement, EZH2 and Lat1 expression are co-regulated in models of cancer cell differentiation and co-expression is observed at the invasive front of human lung tumors. EZH2 knockdown or small-molecule inhibition leads to de-repression of RXRα resulting in reduced Lat1 expression. Our results describe a Lat1-EZH2 positive feedback loop illustrated by AA depletion or Lat1 knockdown resulting in SAM reduction and concomitant reduction in EZH2 activity. shRNA-mediated knockdown of Lat1 results in tumor growth inhibition and points to Lat1 as a potential therapeutic target.

Advances in the Molecular Analysis of Breast Cancer: Pathway toward Personalized Medicine

Background

Breast cancer is a heterogeneous disease that encompasses a wide range of clinical behaviors and histological and molecular variants. It is the most common type of cancer affecting women worldwide and is the second leading cause of cancer death.

Methods

A comprehensive literature search was performed to explore the advances in molecular medicine related to the diagnosis and treatment of breast cancer.

Results

During the last few decades, advances in molecular medicine have changed the landscape of cancer treatment as new molecular tests complement and, in many instances, exceed traditional methods for determining patient prognosis and response to treatment options. Personalized medicine is becoming the standard of care around the world. Developments in molecular profiling, genomic analysis, and the discovery of targeted drug therapies have significantly improved patient survival rates and quality of life.

Conclusions

This review highlights what pathologists need to know about current molecular tests for classification and prognostic/predictive assessment of breast carcinoma as well as their role as part of the medical team.

Molecular diagnostic testing in breast cancer

OBJECTIVES

An overview of molecular tests used in the treatment of breast cancer, organized by stage and clinical condition.

DATA SOURCES

Systematic review of scientific literature, guideline recommendations, and data published by test manufacturers.

CONCLUSION

Several molecular tests that analyze expression of cancer-related genes have been validated in clinical trials and are recommended by clinical practice guidelines to inform diagnosis and treatment decisions for personalized interventions.

IMPLICATIONS FOR NURSING PRACTICE

Molecular testing has become an important part of patient care for those with breast cancer. Oncology nurses must understand this methodology to prescribe tests, interpret the results, and provide guidance to patients.

Emerging understanding of multiscale tumor heterogeneity

Cancer is a multifaceted disease characterized by heterogeneous genetic alterations and cellular metabolism, at the organ, tissue, and cellular level. Key features of cancer heterogeneity are summarized by 10 acquired capabilities, which govern malignant transformation and progression of invasive tumors. The relative contribution of these hallmark features to the disease process varies between cancers. At the DNA and cellular level, germ-line and somatic gene mutations are found across all cancer types, causing abnormal protein production, cell behavior, and growth. The tumor microenvironment and its individual components (immune cells, fibroblasts, collagen, and blood vessels) can also facilitate or restrict tumor growth and metastasis. Oncology research is currently in the midst of a tremendous surge of comprehension of these disease mechanisms. This will lead not only to novel drug targets but also to new challenges in drug discovery. Integrated, multi-omic, multiplexed technologies are essential tools in the quest to understand all of the various cellular changes involved in tumorigenesis. This review examines features of cancer heterogeneity and discusses how multiplexed technologies can facilitate a more comprehensive understanding of these features.

Pathologic diagnosis, immunohistochemistry, multigene assays and breast cancer treatment: progress toward "precision" cancer therapy

Clinical decisions regarding the suitability of adjuvant systemic therapy for individual patients with breast cancer depends on comprehensive assessment of the underlying biology of each patient's tumor. The previous clinical-pathologic paradigm for treatment, which had been used for decades, now has been augmented by significant advances in molecular analysis of breast tumor tissue samples. Molecular testing has the potential to understand better both tumor biology and clinical behavior, which enables more appropriate therapy choices to be made. We review the rapid evolution in profiling breast cancer tissues, and discuss the current evidence for clinical use of this information and how the emerging molecular paradigm can be integrated into the clinical-pathologic context as we progress toward "precision" therapy for patients with breast cancer and other solid tumors.

Time dependence of biomarkers: non-proportional effects of immunohistochemical panels predicting relapse risk in early breast cancer

Background:

We investigated the impact of follow-up duration to determine whether two immunohistochemical prognostic panels, IHC4 and Mammostrat, provide information on the risk of early or late distant recurrence using the Edinburgh Breast Conservation Series and the Tamoxifen vs Exemestane Adjuvant Multinational (TEAM) trial.

Methods:

The multivariable fractional polynomial time (MFPT) algorithm was used to determine which variables had possible non-proportional effects. The performance of the scores was assessed at various lengths of follow-up and Cox regression modelling was performed over the intervals of 0–5 years and >5 years.

Results:

We observed a strong time dependence of both the IHC4 and Mammostrat scores, with their effects decreasing over time. In the first 5 years of follow-up only, the addition of both scores to clinical factors provided statistically significant information (P<0.05), with increases in R² between 5 and 6% and increases in D-statistic between 0.16 and 0.21.

Conclusions:

Our analyses confirm that the IHC4 and Mammostrat scores are strong prognostic factors for time to distant recurrence but this is restricted to the first 5 years after diagnosis. This provides evidence for their combined use to predict early recurrence events in order to select those patients who may/will benefit from adjuvant chemotherapy.

Predictive and prognostic value of the 21-gene recurrence score in hormone receptor-positive, node-positive breast cancer

The addition of adjuvant chemotherapy to hormonal therapy is recommended for patients with estrogen receptor-positive (ER+), node-positive (N+) early breast cancer (EBC). Some of these patients, however, are not likely to benefit from treatment and may, therefore, be overtreated while also incurring unnecessary treatment-related adverse events and health care costs. The 21-gene Recurrence Score assay has been clinically validated and recommended for use in patients with ER+, node-negative (N0) EBC to assess the 10-year risk of distant disease recurrence and predict the likelihood of response to adjuvant chemotherapy. A growing body of evidence from several large phase III clinical trials reports similar findings in patients with ER+, N+ EBC. A systematic review of published literature from key clinical trials that have used the 21-gene breast cancer assay in patients with ER+, N+ EBC was performed. The Recurrence Score has been shown to be an independent predictor of disease-free survival, overall survival, and distant recurrence-free interval in patients with ER+, N+ EBC. Outcomes from decision impact and health economics studies further indicate that the Recurrence Score affects physician treatment recommendations equally in patients with N+ or N0 disease. It also indicates that a reduction in Recurrence Score-directed chemotherapy is cost-effective. There is a large body of evidence to support the use of the 21-gene assay Recurrence Score in patients with N+ EBC. Use of this assay could help guide treatment decisions for patients who are most likely to receive benefit from chemotherapy.

Molecular markers for breast cancer diagnosis, prognosis and targeted therapy

Precision medicine involves understanding the molecular drivers unique to an individual patient's cancer so that specific factors may be targeted with the goal of improved patient outcomes. The purpose of this article is to review standard of care and research grade (non-standard of care) biomarkers in breast cancer that may be useful for diagnosis, prognosis and targeted therapy.

Adaptive designs for clinical trials assessing biomarker-guided treatment strategies

BACKGROUND

The Biomarker Strategy Design has been proposed for trials assessing the value of a biomarker in guiding treatment in oncology. In such trials, patients are randomised to either receive the standard chemotherapy treatment or a biomarker-directed treatment arm, in which biomarker status is used to guide treatment.

METHODS

Motivated by a current trial, we consider an adaptive design in which two biomarkers are assessed. The trial is conducted in two stages. In the first stage, patients in the biomarker-guided arm are assessed using a standard and an alternative cheaper biomarker, with the standard biomarker guiding treatment. An analysis comparing biomarker results is then used to choose the biomarker to use for the remainder of the trial. The new biomarker is used if the results for the two biomarkers are sufficiently similar.

RESULTS

We show that in practical situations the first-stage results can be used to adapt the trial without type I error rate inflation. We also show that there can be considerable cost gains with only a small loss in power in the case where the alternative biomarker is highly concordant with the standard one.

CONCLUSIONS

Adaptive designs have an important role in reducing the cost and increasing the clinical utility of trials evaluating biomarker-guided treatment strategies.

The functional and molecular entities underlying amino acid and peptide transport by the mammary gland under different physiological and pathological conditions

This review describes the properties and regulation of the membrane transport proteins which supply the mammary gland with aminonitrogen to support metabolism under different physiological conditions (i.e. pregnancy, lactation and involution). Early studies focussed on characterising amino acid and peptide transport pathways with respect to substrate specificity, kinetics and hormonal regulation to allow a broad picture of the systems within the gland to be established. Recent investigations have concentrated on identifying the individual transporters at the molecular level (i.e. mRNA and protein). Many of the latter studies have identified the molecular correlates of the transport systems uncovered in the earlier functional investigations but in turn have also highlighted the need for more amino acid transport studies to be performed. The transporters function as either cotransporters and exchangers (or both) and act in a coordinated and regulated fashion to support the metabolic needs of the gland. However, it is apparent that a physiological role for a number of the transport proteins has yet to be elucidated. This article highlights the many gaps in our knowledge regarding the precise cellular location of a number of amino acid transporters within the gland. We also describe the role of amino acid transport in mammary cell volume regulation. Finally, the important role that individual mammary transport proteins may have in the growth and proliferation of mammary tumours is discussed.

Emerging technologies in extracellular vesicle-based molecular diagnostics

Extracellular vesicles (EVs), including exosomes and microvesicles, have been shown to carry a variety of biomacromolecules including mRNA, microRNA and other non-coding RNAs. Within the past 5 years, EVs have emerged as a promising minimally invasive novel source of material for molecular diagnostics. Although EVs can be easily identified and collected from biological fluids, further research and proper validation is needed in order for them to be useful in the clinical setting. In addition, innovative and more efficient means of nucleic acid profiling are needed to facilitate investigations into the cellular and molecular mechanisms of EV function and to establish their potential as useful clinical biomarkers and therapeutic tools. In this article, we provide an overview of recent technological improvements in both upstream EV isolation and downstream analytical technologies, including digital PCR and next generation sequencing, highlighting future prospects for EV-based molecular diagnostics.

Predicting and communicating the risk of recurrence and death in women with early-stage breast cancer: a systematic review of risk prediction models

BACKGROUND

It is a challenge for oncologists to distinguish patients with breast cancer who can forego adjuvant systemic treatment without negatively affecting survival from those who cannot. Risk prediction models (RPMs) have been developed for this purpose. Oncologists seem to have embraced RPMs (particularly Adjuvant!) in clinical practice and often use them to communicate prognosis to patients. We performed a systematic review of published RPMs and provide an overview of the prognosticators incorporated and reported clinical validity. Subsequently, we selected the RPMs that are currently used in the clinic for a more in-depth assessment of clinical validity. Finally, we assessed lay comprehensibility of the reports generated by RPMs.

METHODS

Pubmed, EMBASE, and Web of Science were searched. Two reviewers independently selected relevant articles and extracted data. Agreement on article selection and data extraction was achieved in consensus meetings.

RESULTS

We identified RPMs based on clinical prognosticators (N = 6) and biomolecular features (N = 14). Generally predictions from RPMs seem to be accurate, except for patients ≤ 50 years or ≥ 75 years at diagnosis, in addition to Asian populations. RPM reports contain much medical jargon or technical details, which are seldom explained in lay terms.

CONCLUSION

The accuracy of RPMs' prognostic estimates is suboptimal in some patient subgroups. This urgently needs to be addressed. In their current format, RPM reports are not conducive to patient comprehension. Communicating survival probabilities using RPM might seem straightforward, but it is fraught with difficulties. If not done properly, it can backfire and confuse patients. Evidence to guide best communication practice is needed.