NCAPH drives breast cancer progression and identifies a gene signature that predicts luminal a tumour recurrence.

BACKGROUND: Luminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment. METHODS: We conducted a study to explore non-structural chromosome maintenance condensin I complex subunit H's (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels. RESULTS: We found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPHErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression. CONCLUSIONS: The GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.

NCAPH Drives Breast Cancer Progression and Identifies a Gene Signature that Predicts Luminal A Tumor Recurrence.

Despite their generally favorable prognosis, luminal A tumors paradoxically pose the highest ten-year recurrence risk among breast cancers. From those that relapse, a quarter of them do it within five years after diagnosis. Identifying such patients is crucial, as long-term relapsers could benefit from extended hormone therapy, whereas early relapsers may require aggressive treatment. In this study, we demonstrate that NCAPH plays a role in the pathogenesis of luminal A breast cancer, contributing to its adverse progression in vitro and in vivo. Furthermore, we reveal that a signature of intratumoral gene expression, associated with elevated levels of NCAPH, serves as a potential marker to identify patients facing unfavorable progression of luminal A breast cancer. Indeed, transgenic mice overexpressing NCAPH generated breast tumors with long latency, and in MMTV-NCAPH/ErbB2+ double-transgenic mice, the luminal tumors formed were more aggressive. In addition, high intratumoral levels of Ncaph were associated with worse breast cancer evolution and poor response to chemotherapy in a cohort of genetically heterogeneous transgenic mice generated by backcrossing. In this cohort of mice, we identified a series of transcripts associated with elevated intratumoral levels of NCAPH, which were linked to adverse progression of breast cancer in both mice and humans. Utilizing the Least Absolute Shrinkage and Selection Operator (LASSO) multivariate regression analysis on this series of transcripts, we derived a ten-gene risk score. This score is defined by a gene signature (termed Gene Signature for Luminal A 10 or GSLA10) that correlates with unfavorable progression of luminal A breast cancer. The GSLA10 signature surpassed the Oncotype DX signature in discerning tumors with unfavorable outcomes (previously categorized as Luminal A by PAM50) across three independent human cohorts. This GSLA10 signature aids in identifying patients with Luminal A tumors displaying adverse prognosis, who could potentially benefit from personalized treatment strategies.

Intermediate Molecular Phenotypes to Identify Genetic Markers of Anthracycline-Induced Cardiotoxicity Risk.

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex trait with a polygenic component that is mainly unidentified. We propose that levels of intermediate molecular phenotypes (IMPs) in the myocardium associated with histopathological damage could explain CDA susceptibility, so variants of genes encoding these IMPs could identify patients susceptible to this complication. Thus, a genetically heterogeneous cohort of mice (n = 165) generated by backcrossing were treated with doxorubicin and docetaxel. We quantified heart fibrosis using an Ariol slide scanner and intramyocardial levels of IMPs using multiplex bead arrays and QPCR. We identified quantitative trait loci linked to IMPs (ipQTLs) and cdaQTLs via linkage analysis. In three cancer patient cohorts, CDA was quantified using echocardiography or Cardiac Magnetic Resonance. CDA behaves as a complex trait in the mouse cohort. IMP levels in the myocardium were associated with CDA. ipQTLs integrated into genetic models with cdaQTLs account for more CDA phenotypic variation than that explained by cda-QTLs alone. Allelic forms of genes encoding IMPs associated with CDA in mice, including AKT1, MAPK14, MAPK8, STAT3, CAS3, and TP53, are genetic determinants of CDA in patients. Two genetic risk scores for pediatric patients (n = 71) and women with breast cancer (n = 420) were generated using machine-learning Least Absolute Shrinkage and Selection Operator (LASSO) regression. Thus, IMPs associated with heart damage identify genetic markers of CDA risk, thereby allowing more personalized patient management.

Intermediate molecular phenotypes to identify genetic markers of anthracycline-induced cardiotoxicity risk.

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex disease whose polygenic component is mainly unidentified. We propose that levels of intermediate molecular phenotypes in the myocardium associated with histopathological damage could explain CDA susceptibility; so that variants of genes encoding these intermediate molecular phenotypes could identify patients susceptible to this complication. A genetically heterogeneous cohort of mice generated by backcrossing (N = 165) was treated with doxorubicin and docetaxel. Cardiac histopathological damage was measured by fibrosis and cardiomyocyte size by an Ariol slide scanner. We determine intramyocardial levels of intermediate molecular phenotypes of CDA associated with histopathological damage and quantitative trait loci (ipQTLs) linked to them. These ipQTLs seem to contribute to the missing heritability of CDA because they improve the heritability explained by QTL directly linked to CDA (cda-QTLs) through genetic models. Genes encoding these molecular subphenotypes were evaluated as genetic markers of CDA in three cancer patient cohorts (N = 517) whose cardiac damage was quantified by echocardiography or Cardiac Magnetic Resonance. Many SNPs associated with CDA were found using genetic models. LASSO multivariate regression identified two risk score models, one for pediatric cancer patients and the other for women with breast cancer. Molecular intermediate phenotypes associated with heart damage can identify genetic markers of CDA risk, thereby allowing a more personalized patient management. A similar strategy could be applied to identify genetic markers of other complex trait diseases.

Stromal SNAI2 Is Required for ERBB2 Breast Cancer Progression.

SNAI2 overexpression appears to be associated with poor prognosis in breast cancer, yet it remains unclear in which breast cancer subtypes this occurs. Here we show that excess SNAI2 is associated with a poor prognosis of luminal B HER2+/ERBB2+ breast cancers in which SNAI2 expression in the stroma but not the epithelium correlates with tumor proliferation. To determine how stromal SNAI2 might influence HER2+ tumor behavior, Snai2-deficient mice were crossed with a mouse line carrying the ErbB2/Neu protooncogene to generate HER2+/ERBB2+ breast cancer. Tumors generated in this model expressed SNAI2 in the stroma but not the epithelium, allowing for the role of stromal SNAI2 to be studied without interference from the epithelial compartment. The absence of SNAI2 in the stroma of HER2+/ERBB2+ tumors is associated with: (i) lower levels of cyclin D1 (CCND1) and reduced tumor epithelium proliferation; (ii) higher levels of AKT and a lower incidence of metastasis; (iii) lower levels of angiopoietin-2 (ANGPT2), and more necrosis. Together, these results indicate that the loss of SNAI2 in cancer-associated fibroblasts limits the production of some cytokines, which influences AKT/ERK tumor signaling and subsequent proliferative and metastatic capacity of ERBB2+ breast cancer cells. Accordingly, SNAI2 expression in the stroma enhanced the tumorigenicity of luminal B HER2+/ERBB2+ breast cancers. This work emphasizes the importance of stromal SNAI2 in breast cancer progression and patients' prognosis. SIGNIFICANCE: Stromal SNAI2 expression enhances the tumorigenicity of luminal B HER2+ breast cancers and can identify a subset of patients with poor prognosis, making SNAI2 a potential therapeutic target for this disease. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/23/5216/F1.large.jpg.

Supplementary data for the biological age linked to oxidative stress modifies breast cancer aggressiveness.

The data presented in this article are related to the research paper entitled "The biological age linked to oxidative stress modifies breast cancer aggressiveness" (M.M. Sáez-Freire, A. Blanco-Gómez, S. Castillo-Lluva, A. Gómez-Vecino, J.M. Galvis-Jiménez, C. Martín-Seisdedos, M. Isidoro-García, L. Hontecillas-Prieto, M.B. García-Cenador, F.J. García-Criado, M.C. Patino-Alonso, P. Galindo-Villardón, J.H. Mao, C. Prieto, A. Castellanos-Martín, L. Kaderali, J. Pérez-Losada). The data shown were obtained from a population of transgenic mice, MMTV-Erbb2/Neu, with different susceptibility to breast cancer and a mixed genetic background generated by backcrossing. It was observed that the aggressiveness of breast cancer negatively correlates with age, being lower in chronologically old mice, similar to what occurs in humans. Given that oxidative stress is associated with tumour susceptibility and the degree of aging, the association between the aggressiveness of breast cancer and multiple intermediate phenotypes directly or indirectly related to oxidative stress was studied. Using a mathematical model, we defined biological age and the degree of aging as the difference between biological and chronological ages. As a result, we observed that biologically old mice predominated among those that developed the disease early on, that is, those that were chronologically young. We then identified the specific and common genetic components of Quantitative Trait loci or QTL associated with different evolution of breast cancer, the intermediate phenotypes related to oxidative stress studied, the biological age and the degree of aging. Lastly, we showed that the expression pattern in the livers of biologically old mice were enriched in signalling pathways related to inflammation and response to infections; whereas the biologically young mice exhibited enriched pathways related to mitochondrial activity. For the explanation and discussion of these data refer to the research article cited above.

The biological age linked to oxidative stress modifies breast cancer aggressiveness.

The incidence of breast cancer increases with age until menopause, and breast cancer is more aggressive in younger women. The existence of epidemiological links between breast cancer and aging indicates that both processes share some common mechanisms of development. Oxidative stress is associated with both cancer susceptibility and aging. Here we observed that ERBB2-positive breast cancer, which developed in genetically heterogeneous ERBB2-positive transgenic mice generated by a backcross, is more aggressive in chronologically younger than in older mice (differentiated by the median survival of the cohort that was 79 weeks), similar to what occurs in humans. In this cohort, we estimated the oxidative biological age using a mathematical model that integrated several subphenotypes directly or indirectly related to oxidative stress. The model selected the serum levels of HDL-cholesterol and magnesium and total AKT1 and glutathione concentrations in the liver. The grade of aging was calculated as the difference between the predicted biological age and the chronological age. This comparison permitted the identification of biologically younger and older mice compared with their chronological age. Interestingly, biologically older mice developed more aggressive breast cancer than the biologically younger mice. Genomic regions on chromosomes 2 and 15 linked to the grade of oxidative aging were identified. The levels of expression of Zbp1 located on chromosome 2, a gene related to necroptosis and inflammation, positively correlated with the grade of aging and tumour aggressiveness. Moreover, the pattern of gene expression of genes linked to the inflammation and the response to infection pathways was enriched in the livers of biologically old mice. This study shows part of the complex interactions between breast cancer and aging.

Missing heritability of complex diseases: Enlightenment by genetic variants from intermediate phenotypes.

Diseases of complex origin have a component of quantitative genetics that contributes to their susceptibility and phenotypic variability. However, after several studies, a major part of the genetic component of complex phenotypes has still not been found, a situation known as "missing heritability." Although there have been many hypotheses put forward to explain the reasons for the missing heritability, its definitive causes remain unknown. Complex diseases are caused by multiple intermediate phenotypes involved in their pathogenesis and, very often, each one of these intermediate phenotypes also has a component of quantitative inheritance. Here we propose that at least part of the missing heritability can be explained by the genetic component of intermediate phenotypes that is not detectable at the level of the main complex trait. At the same time, the identification of the genetic component of intermediate phenotypes provides an opportunity to identify part of the missing heritability of complex diseases.

Unraveling heterogeneous susceptibility and the evolution of breast cancer using a systems biology approach.

BACKGROUND: An essential question in cancer is why individuals with the same disease have different clinical outcomes. Progress toward a more personalized medicine in cancer patients requires taking into account the underlying heterogeneity at different molecular levels. RESULTS: Here, we present a model in which there are complex interactions at different cellular and systemic levels that account for the heterogeneity of susceptibility to and evolution of ERBB2-positive breast cancers. Our model is based on our analyses of a cohort of mice that are characterized by heterogeneous susceptibility to ERBB2-positive breast cancers. Our analysis reveals that there are similarities between ERBB2 tumors in humans and those of backcross mice at clinical, genomic, expression, and signaling levels. We also show that mice that have tumors with intrinsically high levels of active AKT and ERK are more resistant to tumor metastasis. Our findings suggest for the first time that a site-specific phosphorylation at the serine 473 residue of AKT1 modifies the capacity for tumors to disseminate. Finally, we present two predictive models that can explain the heterogeneous behavior of the disease in the mouse population when we consider simultaneously certain genetic markers, liver cell signaling and serum biomarkers that are identified before the onset of the disease. CONCLUSIONS: Considering simultaneously tumor pathophenotypes and several molecular levels, we show the heterogeneous behavior of ERBB2-positive breast cancer in terms of disease progression. This and similar studies should help to better understand disease variability in patient populations.

C2ORF40 suppresses breast cancer cell proliferation and invasion through modulating expression of M phase cell cycle genes.

Recently, it has been suggested that C2ORF40 is a candidate tumor suppressor gene in breast cancer. However, the mechanism for reduced expression of C2ORF40 and its functional role in breast cancers remain unclear. Here we show that C2ORF40 is frequently silenced in human primary breast cancers and cell lines through promoter hypermethylation. C2ORF40 mRNA level is significantly associated with patient disease-free survival and distant cancer metastasis. Overexpression of C2ORF4 0 inhibits breast cancer cell proliferation, migration and invasion. By contrast, silencing C2ORF40 expression promotes these biological phenotypes. Bioinformatics and FACS analysis reveal C2ORF40 functions at G2/M phase by downregulation of mitotic genes expression, including UBE2C. Our results suggest that C2ORF40 acts as a tumor suppressor gene in breast cancer pathogenesis and progression and is a candidate prognostic marker for this disease.

Multiple novel alternative splicing forms of FBXW7α have a translational modulatory function and show specific alteration in human cancer.

FBXW7 acts as a tumor suppressor through ubiquitination and degradation of multiple oncoproteins. Loss of FBXW7 expression, which could be partially attributed by the genomic deletion or mutation of FBXW7 locus, is frequently observed in various human cancers. However, the mechanisms regulating FBXW7 expression still remain poorly understood. Here we examined the 5' region of FBXW7 gene to investigate the regulation of FBXW7 expression. We identified seven alternative splicing (AS) 5'-UTR forms of FBXW7α that are composed of multiple novel non-coding exons. A significant difference in translational efficiency among these 5'-UTRs variants was observed by in vivo Luciferase reporter assay and Western blot. Furthermore, we found that the mRNA level of the AS form with high translational efficiency was specifically reduced in more than 80% of breast cancer cell lines and in more than 50% of human primary cancers from various tissues. In addition, we also identified mutations of FBXW7 in prostate cancers (5.6%), kidney cancers (16.7%), and bladder cancers (18.8%). Our results suggest that in addition to mutation, differential expression of FBXW7α AS forms with different translational properties may serve as a novel mechanism for inactivation of FBXW7 in human cancer.

New models towards assessing anti-cancer therapeutics.

Cancer is the subject of intense research around the world, but many questions about how the disease works remain unanswered. How exactly does cancer start and how do tumours grow? In fact, at present there are ten times more anticancer drugs being tested in clinical trials than there were 15 years ago. However, many of the new anticancer agents are predicted to show clinical benefit in only small subpopulations of patients. The cancer stem cell model could explain not only how some cancers work but also why patients suffer relapses, providing a good opportunity to gain insight into the reasons why agents work or, more commonly, don't work, before going into a clinical trial.

Cancer evolution and individual susceptibility.

Cancer susceptibility is due to interactions between inherited genetic factors and exposure to environmental carcinogens. The genetic component is constituted mainly by weakly acting low-penetrance genetic variants that interact among themselves, as well as with the environment. These low susceptibility genes can be categorized into two main groups: one includes those that control intrinsic tumor cell activities (i.e. apoptosis, proliferation or DNA repair), and the other contains those that modulate the function of extrinsic tumor cell compartments (i.e. stroma, angiogenesis, or endocrine and immune systems). Genome-Wide Association Studies (GWAS) of human populations have identified numerous genetic loci linked with cancer risk and behavior, but nevertheless the major component of cancer heritability remains to be explained. One reason may be that GWAS cannot readily capture gene-gene or gene-environment interactions. Mouse model approaches offer an alternative or complementary strategy, because of our ability to control both the genetic and environmental components of risk. Recently developed genetic tools, including high-throughput technologies such as SNP, CGH and gene expression microarrays, have led to more powerful strategies for refining quantitative trait loci (QTL) and identifying the critical genes. In particular, the cross-species approaches will help to refine locations of QTLs, and reveal their genetic and environmental interactions. The identification of human tumor susceptibility genes and discovery of their roles in carcinogenesis will ultimately be important for the development of methods for prediction of risk, diagnosis, prevention and therapy for human cancers.