Stromal genes add prognostic information to proliferation and histoclinical markers: a basis for the next generation of breast cancer gene signatures

Plasma Levels of Decorin Increased in Patients during the Progression of Breast Cancer

Decorin (DCN), an extracellular matrix proteoglycan found in tumor surrounding tissues, is a natural inhibitor of tumor cell proliferation and invasion. We conducted a cross-sectional observation study to evaluate the association of the pathological stage with the levels of DCN in plasma or tumor surrounding tissue. Among 118 patients who underwent breast surgery, 35 were designated as carcinoma in situ (Stage 0), 39 were Stage I, and 44 were Stage II or III. The stromal expression of DCN was quantified using a semiquantitative digital image analysis after immunohistochemical staining. The concentration of DCN was evaluated with a specific ELISA. As we have previously shown, stromal DCN expression was attenuated in the patients with Stage I, whereas stromal and plasma DCN was elevated paradoxically in those with Stage II/III. The elevated plasma DCN is an independent predictive factor of Stage II/III by the multivariate logistic regression analysis. The plasma level of DCN was negatively correlated with stromal DCN expression only in patients with advanced disease (Stage II/III). The plasma level of DCN could become a useful biomarker for patients in the advanced stages. Extensive studies and further assessments are warranted for evaluating the prognostic significance and tumor characteristics to understand the clinical significances of stromal and systemic DCN.

Antimetastatic Effects of Ganoderma lucidum Polysaccharide Peptide on B16-F10-luc-G5 Melanoma Mice With Sleep Fragmentation

Ganoderma lucidum (Lingzhi) polysaccharide peptide (GL-pp) is a component of the globally acknowledged traditional Chinese medicine Ganoderma lucidum; Ganoderma lucidum is known for its sedative, hypnotic, immune regulatory, antitumor, and other pharmacological effects. In recent years, sleep disorders have been linked to many diseases and human body disorders, including cancer. Some experimental studies in mice found that sleep fragmentation could promote tumor development and progression. However, effects on GL-pp on tumor metastasis under circumstances of sleep disorders have rarely been studied. Thus, in this study, we used mice with sleep fragmentation (SF) bearing B16-F10-luc-G5 melanoma tumors to investigate the effect of SF on melanoma metastasis. Furthermore, we investigated the antitumor and antimetastatic effects of GL-pp (80 mg/kg) in mice suffering from SF and bearing B16-F10-luc-G5. Then, whole proteomics was used to analyze the differences in protein expression in the lung tissue between SF mice bearing B16-F10-luc-G5 with and without GL-pp administration. High-throughput pyrosequencing of 16S rRNA was also used to analyze the impact of GL-pp on the gut microbiota composition in SF mice bearing B16-F10-luc-G5. Last, the effects of GL-pp on macrophage polarization and TNF-α serum levels were detected. Collectively, we found that SF significantly facilitated the B16-F10-luc-G5 melanoma tumor metastasis in mice, while GL-pp significantly reduced B16-F10-luc-G5 melanoma tumor metastasis under the condition of SF, in which proteomics and gut microbiota had been changed greatly.

Down-Regulation of the Proteoglycan Decorin Fills in the Tumor-Promoting Phenotype of Ionizing Radiation-Induced Senescent Human Breast Stromal Fibroblasts

Simple Summary

Ionizing radiation (a typical remedy for breast cancer) results in the premature senescence of the adjacent to the neoplastic cells stromal fibroblasts. Here, we showed that these senescent fibroblasts are characterized by the down-regulation of the small leucine-rich proteoglycan decorin, a poor prognostic factor for the progression of the disease. Decorin down-regulation is mediated by secreted growth factors in an autocrine and paracrine (due to the interaction with breast cancer cells) manner, with bFGF and VEGF being the key players of this regulation in young and senescent breast stromal fibroblasts. Autophagy activation increases decorin mRNA levels, indicating that impaired autophagy is implicated in the reduction in decorin in this cell model. Decorin down-regulation acts additively to the already tumor-promoting phenotype of ionizing radiation-induced prematurely senescent human stromal fibroblasts, confirming that stromal senescence is a side-effect of radiotherapy that should be taken into account in the design of anticancer treatments.

Abstract

Down-regulation of the small leucine-rich proteoglycan decorin in the stroma is considered a poor prognostic factor for breast cancer progression. Ionizing radiation, an established treatment for breast cancer, provokes the premature senescence of the adjacent to the tumor stromal fibroblasts. Here, we showed that senescent human breast stromal fibroblasts are characterized by the down-regulation of decorin at the mRNA and protein level, as well as by its decreased deposition in the pericellular extracellular matrix in vitro. Senescence-associated decorin down-regulation is a long-lasting process rather than an immediate response to γ-irradiation. Growth factors were demonstrated to participate in an autocrine manner in decorin down-regulation, with bFGF and VEGF being the critical mediators of the phenomenon. Autophagy inhibition by chloroquine reduced decorin mRNA levels, while autophagy activation using the mTOR inhibitor rapamycin enhanced decorin transcription. Interestingly, the secretome from a series of both untreated and irradiated human breast cancer cell lines with different molecular profiles inhibited decorin expression in young and senescent stromal fibroblasts, which was annulled by SU5402, a bFGF and VEGF inhibitor. The novel phenotypic trait of senescent human breast stromal fibroblasts revealed here is added to their already described cancer-promoting role via the formation of a tumor-permissive environment.

Molecular features of untreated breast cancer and initial metastatic event inform clinical decision-making and predict outcome: long-term results of ESOPE, a single-arm prospective multicenter study

Background

Prognosis evaluation of advanced breast cancer and therapeutic strategy are mostly based on clinical features of advanced disease and molecular profiling of the primary tumor. Very few studies have evaluated the impact of metastatic subtyping during the initial metastatic event in a prospective study. The genomic landscape of metastatic breast cancer has mostly been described in very advanced, pretreated disease, limiting the findings transferability to clinical use.

Methods

We developed a multicenter, single-arm, prospective clinical trial in order to address these issues. Between November 2010 and September 2013, 123 eligible patients were included. Patients at the first, untreated metastatic event were eligible. All matched primary tumors and metastatic samples were centrally reviewed for pathological typing. Targeted and whole-exome sequencing was applied to matched pairs of frozen tissue. A multivariate overall survival analysis was performed (median follow-up 64 months).

Results

Per central review in 84 patients (out of 130), we show that luminal A breast tumors are more prone to subtype switching. By combining targeted sequencing of a 91 gene panel (n = 67) and whole-exome sequencing (n = 30), a slight excess of mutations is observed in the metastases. Luminal A breast cancer has the most heterogeneous mutational profile and the highest number of mutational signatures, when comparing primary tumor and the matched metastatic tissue. Tumors with a subtype change have more mutations that are private. The metastasis-specific mutation load is significantly higher in late than in de novo metastases. The most frequently mutated genes were TP53 and PIK3CA. The most frequent metastasis-specific druggable genes were PIK3CA, PTEN, KDR, ALK, CDKN2A, NOTCH4, POLE, SETD2, SF3B1, and TSC2. Long-term outcome is driven by a combination of tumor load and metastasis biology.

Conclusions

Profiling of the first, untreated, metastatic event of breast cancer reveals a profound heterogeneity mostly in luminal A tumors and in late metastases. Based on this profiling, we can derive information relevant to prognosis and therapeutic intervention, which support current guidelines recommending a biopsy at the first metastatic relapse.

Trial registration

The trial was registered at ClinicalTrials.gov (NCT01956552).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-021-00862-6.

Functional proteomics outlines the complexity of breast cancer molecular subtypes

Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some patients eventually relapse, which suggests some heterogeneity within this category. In the present study, we used proteomics and miRNA profiling techniques to characterize a set of 102 either estrogen receptor-positive (ER+)/progesterone receptor-positive (PR+) or triple-negative formalin-fixed, paraffin-embedded breast tumors. Protein expression-based probabilistic graphical models and flux balance analyses revealed that some ER+/PR+ samples had a protein expression profile similar to that of triple-negative samples and had a clinical outcome similar to those with triple-negative disease. This probabilistic graphical model-based classification had prognostic value in patients with luminal A breast cancer. This prognostic information was independent of that provided by standard genomic tests for breast cancer, such as MammaPrint, OncoType Dx and the 8-gene Score.

Prognostic value of stromal decorin expression in patients with breast cancer: a meta-analysis

BACKGROUND

Numbers of studies have investigated the biological functions of decorin (DCN) in oncogenesis, tumor progression, angiogenesis and metastasis. Although many of them aim to highlight the prognostic value of stromal DCN expression in breast cancer, some controversial results still exist and a consensus has not been reached until now. Therefore, our meta-analysis aims to determine the prognostic significance of stromal DCN expression in breast cancer patients.

METHODS

PubMed, EMBASE, the Web of Science and China National Knowledge Infrastructure (CNKI) databases were searched for full-text literatures met out inclusion criteria. We applied the hazard ratio (HR) with 95% confidence interval (CI) as the appropriate summarized statistics. Q-test and I(2) statistic were employed to estimate the level of heterogeneity across the included studies. Sensitivity analysis was conducted to further identify the possible origins of heterogeneity. The publication bias was detected by Begg's test and Egger's test.

RESULTS

There were three English literatures (involving 6 studies) included into our meta-analysis. On the one hand, both the summarized outcomes based on univariate analysis (HR: 0.513; 95% CI: 0.406-0.648; P<0.001) and multivariate analysis (HR: 0.544; 95% CI: 0.388-0.763; P<0.001) indicated that stromal DCN expression could promise the high cancer-specific survival (CSS) of breast cancer patients. On the other hand, both the summarized outcomes based on univariate analysis (HR: 0.504; 95% CI: 0.389-0.651; P<0.001) and multivariate analysis (HR: 0.568; 95% CI: 0.400-0.806; P=0.002) also indicated that stromal DCN expression was positively associated with high disease-free survival (DFS) of breast cancer patients. No significant heterogeneity or publication bias was observed within this meta-analysis.

CONCLUSIONS

The present evidences indicate that high stromal DCN expression can significantly predict the good prognosis in patients with breast cancer. The discoveries from our meta-analysis have better be confirmed in the updated review pooling more relevant investigations in the future.

Systemic Delivery of an Oncolytic Adenovirus Expressing Decorin for the Treatment of Breast Cancer Bone Metastases

The development of novel therapies for breast cancer bone metastasis is a major unmet medical need. Toward that end, we have constructed an oncolytic adenovirus, Ad.dcn, and a nonreplicating adenovirus, Ad(E1-).dcn, both containing the human decorin gene. Our in vitro studies showed that Ad.dcn produced high levels of viral replication and the decorin protein in the breast tumor cells. Ad(E1-).dcn-mediated decorin expression in MDA-MB-231 cells downregulated the expression of Met, β-catenin, and vascular endothelial growth factor A, all of which are recognized decorin targets and play pivotal roles in the progression of breast tumor growth and metastasis. Adenoviral-mediated decorin expression inhibited cell migration and induced mitochondrial autophagy in MDA-MB-231 cells. Mice bearing MDA-MB-231-luc skeletal metastases were systemically administered with the viral vectors, and skeletal tumor growth was monitored over time. The results of bioluminescence imaging and X-ray radiography indicated that Ad.dcn and Ad(E1-).dcn significantly inhibited the progression of bone metastases. At the terminal time point, histomorphometric analysis, micro-computed tomography, and bone destruction biomarkers showed that Ad.dcn and Ad(E1-).dcn reduced tumor burden and inhibited bone destruction. A nonreplicating adenovirus Ad(E1-).luc expressing the luciferase 2 gene had no significant effect on inhibiting bone metastases, and in several assays, Ad.dcn and Ad(E1-).dcn were better than Ad.luc, a replicating virus expressing the luciferase 2 gene. Our data suggest that adenoviral replication coupled with decorin expression could produce effective antitumor responses in a MDA-MB-231 bone metastasis model of breast cancer. Thus, Ad.dcn could potentially be developed as a candidate gene therapy vector for treating breast cancer bone metastases.

Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces

The pathological description of the stage of a tumor is an important clinical designation and is considered, like many other forms of biomedical data, an ordinal outcome. Currently, statistical methods for predicting an ordinal outcome using clinical, demographic, and high-dimensional correlated features are lacking. In this paper, we propose a method that fits an ordinal response model to predict an ordinal outcome for high-dimensional covariate spaces. Our method penalizes some covariates (high-throughput genomic features) without penalizing others (such as demographic and/or clinical covariates). We demonstrate the application of our method to predict the stage of breast cancer. In our model, breast cancer subtype is a nonpenalized predictor, and CpG site methylation values from the Illumina Human Methylation 450K assay are penalized predictors. The method has been made available in the ordinalgmifs package in the R programming environment.

Robust selection of cancer survival signatures from high-throughput genomic data using two-fold subsampling

Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal) subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external) subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable consensus signature. The software is available as an R package rsig at CRAN (http://cran.r-project.org).

Diverse modes of genomic alteration in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a heterogeneous disease with high mortality rate. Recent genomic studies have identified TP53, AXIN1, and CTNNB1 as the most frequently mutated genes. Lower frequency mutations have been reported in ARID1A, ARID2 and JAK1. In addition, hepatitis B virus (HBV) integrations into the human genome have been associated with HCC.

RESULTS

Here, we deep-sequence 42 HCC patients with a combination of whole genome, exome and transcriptome sequencing to identify the mutational landscape of HCC using a reasonably large discovery cohort. We find frequent mutations in TP53, CTNNB1 and AXIN1, and rare but likely functional mutations in BAP1 and IDH1. Besides frequent hepatitis B virus integrations at TERT, we identify translocations at the boundaries of TERT. A novel deletion is identified in CTNNB1 in a region that is heavily mutated in multiple cancers. We also find multiple high-allelic frequency mutations in the extracellular matrix protein LAMA2. Lower expression levels of LAMA2 correlate with a proliferative signature, and predict poor survival and higher chance of cancer recurrence in HCC patients, suggesting an important role of the extracellular matrix and cell adhesion in tumor progression of a subgroup of HCC patients.

CONCLUSIONS

The heterogeneous disease of HCC features diverse modes of genomic alteration. In addition to common point mutations, structural variations and methylation changes, there are several virus-associated changes, including gene disruption or activation, formation of chimeric viral-human transcripts, and DNA copy number changes. Such a multitude of genomic events likely contributes to the heterogeneous nature of HCC.

Biological functions of decorin in cancer

Decorin is a member of the extracellular matrix small leucine-rich proteoglycans family that exists and functions in stromal and epithelial cells. Accumulating evidence suggests that decorin affects the biology of various types of cancer by directly or indirectly targeting the signaling molecules involved in cell growth, survival, metastasis, and angiogenesis. More recent studies show that decorin plays important roles during tumor development and progression and is a potential cancer therapeutic agent. In this article, we summarize recent studies of decorin in cancer and discuss decorin's therapeutic and prognostic value.

More than matrix: the multifaceted role of decorin in cancer

The small leucine-rich proteoglycan, decorin, has incrementally been shown to be a powerful inhibitor of growth in a wide variety of tumour cells, an effect specifically mediated by the interaction of decorin core protein with the epidermal growth factor receptor (EGFR) and other ErbB family proteins. Nowadays, this matrikine has become the main focus of various cancer studies. Decorin is an important component of the cellular microenvironment or extracellular matrix (ECM). Its interactions with matrix and cell membrane components have been implicated in many physiological and pathophysiological processes including matrix organisation, signal transduction, wound healing, cell migration, inhibition of metastasis, and angiogenesis. This review summarises recent findings on decorin's interactions and behaviour related to cancer. Highlighted are key functions of decorin such as interaction with cell surface receptors, as well as with ECM components, and the therapeutic potential of this multifunctional molecule.