HER2-targeted, enzyme-activated liposomes show superior in vivo efficacy in an ovarian cancer model.

Liposomes carrying chemotherapeutic drugs can accumulate passively in solid tumors at high levels. However, additional targeting of the liposomes towards e.g. receptors expressed on cancer cells may improve their interaction and therapeutic properties. In this study, we designed a liposomal delivery system, which utilizes the intrinsic characteristics of HER2-positive tumors to ensure efficient delivery of oxaliplatin to the cancer cells. On the liposome surface, trastuzumab, an antibody specific to the HER2 receptor, was shown to facilitate internalization by the cancer cells. A polyethylene glycol (PEG) layer on the liposome surface provides protection from mononuclear phagocyte system uptake. To optimize the interaction between liposomes and cancer cells, a protease-sensitive cleavable peptide linker was inserted at the base of each PEG. The PEG layer is then cleaved off by intra- and extracellular matrix metalloproteinases (MMPs) upon accumulation in the tumor. Our data demonstrate that the removal of PEG significantly destabilizes the liposomes and leads to substantial oxaliplatin release. The proposed beneficial effect of combining antibody-mediated internalization with MMP sensitivity was confirmed in a series of in vivo studies using ovarian cancer xenograft models. The results demonstrated that HER2-targeted MMP-sensitive liposomes have superior anticancer activity compared to non-targeted and non-cleavable liposomes.

Ensemble-based classification using microRNA expression identifies a breast cancer patient subgroup with an ultralow long-term risk of metastases.

BACKGROUND: Current clinical markers overestimate the recurrence risk in many lymph node negative (LNN) breast cancer (BC) patients such that a majority of these low-risk patients unnecessarily receive systemic treatments. We tested if differential microRNA expression in primary tumors allows reliable identification of indolent LNN BC patients to provide an improved classification tool for overtreatment reduction in this patient group. METHODS: We collected freshly frozen primary tumors of 80 LNN BC patients with recurrence and 80 recurrence-free patients (mean follow-up: 20.9 years). The study comprises solely systemically untreated patients to exclude that administered treatments confound the metastasis status. Samples were pairwise matched for clinical-pathological characteristics to minimize dependence of current markers. Patients were classified into risk-subgroups according to the differential microRNA expression of their tumors via classification model building with cross-validation using seven classification methods and a voting scheme. The methodology was validated using available data of two independent cohorts (n = 123, n = 339). RESULTS: Of the 80 indolent patients (who would all likely receive systemic treatments today) our ultralow-risk classifier correctly identified 37 while keeping a sensitivity of 100% in the recurrence group. Multivariable logistic regression analysis confirmed independence of voting results from current clinical markers. Application of the method in two validation cohorts confirmed successful classification of ultralow-risk BC patients with significantly prolonged recurrence-free survival. CONCLUSION: Profiles of differential microRNAs expression can identify LNN BC patients who could spare systemic treatments demanded by currently applied classifications. However, further validation studies are required for clinical implementation of the applied methodology.

Deciphering the monocyte-targeting mechanisms of PEGylated cationic liposomes by investigating the biomolecular corona.

Cationic liposomes specifically target monocytes in blood, rendering them promising drug-delivery tools for cancer immunotherapy, vaccines, and therapies for monocytic leukaemia. The mechanism behind this monocyte targeting ability is, however, not understood, but may involve plasma proteins adsorbed on the liposomal surfaces. To shed light on this, we investigated the biomolecular corona of three different types of PEGylated cationic liposomes, finding all of them to adsorb hyaluronan-associated proteins and proteoglycans upon incubation in human blood plasma. This prompted us to study the role of the TLR4 co-receptors CD44 and CD14, both involved in signalling and uptake pathways of proteoglycans and glycosaminoglycans. We found that separate inhibition of each of these receptors hampered the monocyte uptake of the liposomes in whole human blood. Based on clues from the biomolecular corona, we have thus identified two receptors involved in the targeting and uptake of cationic liposomes in monocytes, in turn suggesting that certain proteoglycans and glycosaminoglycans may serve as monocyte-targeting opsonins. This mechanistic knowledge may pave the way for rational design of future monocyte-targeting drug-delivery platforms.

Co-targeting CDK2 and CDK4/6 overcomes resistance to aromatase and CDK4/6 inhibitors in ER+ breast cancer.

Resistance to aromatase inhibitor (AI) treatment and combined CDK4/6 inhibitor (CDK4/6i) and endocrine therapy (ET) are crucial clinical challenges in treating estrogen receptor-positive (ER+) breast cancer. Understanding the resistance mechanisms and identifying reliable predictive biomarkers and novel treatment combinations to overcome resistance are urgently needed. Herein, we show that upregulation of CDK6, p-CDK2, and/or cyclin E1 is associated with adaptation and resistance to AI-monotherapy and combined CDK4/6i and ET in ER+ advanced breast cancer. Importantly, co-targeting CDK2 and CDK4/6 with ET synergistically impairs cellular growth, induces cell cycle arrest and apoptosis, and delays progression in AI-resistant and combined CDK4/6i and fulvestrant-resistant cell models and in an AI-resistant autocrine breast tumor in a postmenopausal xenograft model. Analysis of CDK6, p-CDK2, and/or cyclin E1 expression as a combined biomarker in metastatic lesions of ER+ advanced breast cancer patients treated with AI-monotherapy or combined CDK4/6i and ET revealed a correlation between high biomarker expression and shorter progression-free survival (PFS), and the biomarker combination was an independent prognostic factor in both patients cohorts. Our study supports the clinical development of therapeutic strategies co-targeting ER, CDK4/6 and CDK2 following progression on AI-monotherapy or combined CDK4/6i and ET to improve survival of patients exhibiting high tumor levels of CDK6, p-CDK2, and/or cyclin E1.

Enhancing Adoptive Cell Therapy by T Cell Loading of SHP2 Inhibitor Nanocrystals before Infusion.

Whereas adoptive T cell therapy has been extensively studied for cancer treatment, the response is still limited primarily due to immune dysfunction related to poor cell engraftment, tumor infiltration and engagement, and lack of a target. In addition, the modification of therapeutic T cells often suffers from being complex and expensive. Here, we present a strategy to load T cells with SHP099, an allosteric SHP2 inhibitor, to enhance the therapeutic efficacy of the T cells. Remote-loading of SHP099 into lipid nanoparticles decorated with triarginine motifs resulted in nanocrystal formation of SHP099 inside the lipid vesicles and allowed high loading efficiency and prolonged retention of SHP099 nanocrystals within T cells. Cell-loaded SHP099 enabled sustained inhibition of the PD-1/PD-L1 signaling and increased cytolytic activity of the T cells. We show in a mouse model that tumor-homing T cells can circulate with the cargos, improving their tumor accumulation compared to systemically administered lipid nanoparticles. On an established solid tumor model, adoptively transferred SHP099 loaded T cells induced complete tumor eradication and durable immune memory against tumor rechallenging on all treated mice by effectively inhibiting the PD-1/PD-L1 checkpoint signal. We demonstrate that the combination of T cell therapy with SHP2 inhibition is a promising therapeutic strategy, and the lipid nanocrystal platform could be generalized as a promising approach for T cell loading of immunomodulatory drugs.

Mechanisms of selective monocyte targeting by liposomes functionalized with a cationic, arginine-rich lipopeptide.

Stimulation of monocytes with immunomodulating agents can harness the immune system to treat a long range of diseases, including cancers, infections and autoimmune diseases. To this end we aimed to develop a monocyte-targeting delivery platform based on cationic liposomes, which can be utilized to deliver immunomodulators and thus induce monocyte-mediated immune responses while avoiding off-target side-effects. The cationic liposome design is based on functionalizing the liposomal membrane with a cholesterol-anchored tri-arginine peptide (TriArg). We demonstrate that TriArg liposomes can target monocytes with high specificity in both human and murine blood and that this targeting is dependent on the content of TriArg in the liposomal membrane. In addition, we show that the mechanism of selective monocyte targeting involves the CD14 co-receptor, and selectivity is compromised when the TriArg content is increased, resulting in complement-mediated off-target uptake in granulocytes. The presented mechanistic findings of uptake by peripheral blood leukocytes may guide the design of future drug delivery systems utilized for immunotherapy. STATEMENT OF SIGNIFICANCE: Monocytes are attractive targets for immunotherapies of cancers, infections and autoimmune diseases. Specific delivery of immunostimulatory drugs to monocytes is typically achieved using ligand-targeted drug delivery systems, but a simpler approach is to target monocytes using cationic liposomes. To achieve this, however, a deep understanding of the mechanisms governing the interactions of cationic liposomes with monocytes and other leukocytes is required. We here investigate these interactions using liposomes incorporating a cationic arginine-rich lipopeptide. We demonstrate that monocyte targeting can be achieved by fine-tuning the lipopeptide content in the liposomes. Additionally, we reveal that the CD14 receptor is involved in the targeting process, whereas the complement system is not. These mechanistic findings are critical for future design of monocyte-targeting liposomal therapies.

Comparison of the Metastasis Predictive Potential of mRNA and Long Non-Coding RNA Profiling in Systemically Untreated Breast Cancer.

Several gene expression signatures based on mRNAs and a few based on long non-coding RNAs (lncRNAs) have been developed to provide prognostic information beyond clinical evaluation in breast cancer (BC). However, the comparison of such signatures for predicting recurrence is very scarce. Therefore, we compared the prognostic utility of mRNAs and lncRNAs in low-risk BC patients using two different classification strategies. Frozen primary tumor samples from 160 lymph node negative and systemically untreated BC patients were included; 80 developed recurrence-i.e., regional or distant metastasis while 80 remained recurrence-free (mean follow-up of 20.9 years). Patients were pairwise matched for clinicopathological characteristics. Classification based on differential mRNA or lncRNA expression using seven individual machine learning methods and a voting scheme classified patients into risk-subgroups. Classification by the seven methods with a fixed sensitivity of ≥90% resulted in specificities ranging from 16-40% for mRNA and 38-58% for lncRNA, and after voting, specificities of 38% and 60% respectively. Classifier performance based on an alternative classification approach of balanced accuracy optimization also provided higher specificities for lncRNA than mRNA at comparable sensitivities. Thus, our results suggested that classification followed by voting improved prognostic power using lncRNAs compared to mRNAs regardless of classification strategy.

Co-targeting CDK4/6 and AKT with endocrine therapy prevents progression in CDK4/6 inhibitor and endocrine therapy-resistant breast cancer.

CDK4/6 inhibitors (CDK4/6i) combined with endocrine therapy have shown impressive efficacy in estrogen receptor-positive advanced breast cancer. However, most patients will eventually experience disease progression on this combination, underscoring the need for effective subsequent treatments or better initial therapies. Here, we show that triple inhibition with fulvestrant, CDK4/6i and AKT inhibitor (AKTi) durably impairs growth of breast cancer cells, prevents progression and reduces metastasis of tumor xenografts resistant to CDK4/6i-fulvestrant combination or fulvestrant alone. Importantly, switching from combined fulvestrant and CDK4/6i upon resistance to dual combination with AKTi and fulvestrant does not prevent tumor progression. Furthermore, triple combination with AKTi significantly inhibits growth of patient-derived xenografts resistant to combined CDK4/6i and fulvestrant. Finally, high phospho-AKT levels in metastasis of breast cancer patients treated with a combination of CDK4/6i and endocrine therapy correlates with shorter progression-free survival. Our findings support the clinical development of ER, CDK4/6 and AKT co-targeting strategies following progression on CDK4/6i and endocrine therapy combination, and in tumors exhibiting high phospho-AKT levels, which are associated with worse clinical outcome.

MCM3 upregulation confers endocrine resistance in breast cancer and is a predictive marker of diminished tamoxifen benefit.

Resistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancer is a major clinical problem with poorly understood mechanisms. There is an unmet need for prognostic and predictive biomarkers to allow appropriate therapeutic targeting. We evaluated the mechanism by which minichromosome maintenance protein 3 (MCM3) influences endocrine resistance and its predictive/prognostic potential in ER+ breast cancer. We discovered that ER+ breast cancer cells survive tamoxifen and letrozole treatments through upregulation of minichromosome maintenance proteins (MCMs), including MCM3, which are key molecules in the cell cycle and DNA replication. Lowering MCM3 expression in endocrine-resistant cells restored drug sensitivity and altered phosphorylation of cell cycle regulators, including p53(Ser315,33), CHK1(Ser317), and cdc25b(Ser323), suggesting that the interaction of MCM3 with cell cycle proteins is an important mechanism of overcoming replicative stress and anti-proliferative effects of endocrine treatments. Interestingly, the MCM3 levels did not affect the efficacy of growth inhibitory by CDK4/6 inhibitors. Evaluation of MCM3 levels in primary tumors from four independent cohorts of breast cancer patients receiving adjuvant tamoxifen mono-therapy or no adjuvant treatment, including the Stockholm tamoxifen (STO-3) trial, showed MCM3 to be an independent prognostic marker adding information beyond Ki67. In addition, MCM3 was shown to be a predictive marker of response to endocrine treatment. Our study reveals a coordinated signaling network centered around MCM3 that limits response to endocrine therapy in ER+ breast cancer and identifies MCM3 as a clinically useful prognostic and predictive biomarker that allows personalized treatment of ER+ breast cancer patients.

Morbidity as a Predictor for Participation in the Danish National Mammography Screening Program: A Cross-Sectional Study.

PURPOSE: In this cross-sectional study, we evaluated the association between morbidity and participation in the prevalence round of the Danish national mammography screening program. PATIENTS AND METHODS: Morbidity was assessed by the Charlson Comorbidity Index (CCI) score (0, 1-2, and ≥3) and by 19 individual diagnoses. We retrieved data on participation from The Danish Quality Database of Mammography Screening and on diagnoses from The Danish National Patient Registry. We estimated prevalence proportion ratios (PR) with 95% confidence intervals (CI). RESULTS: In total, 519,009 (79.8%) women participated in the first national breast cancer screening round. Relative to women with a CCI score of 0, the adjusted PRs were 0.96 (95% CI: 0.95-0.96) for a CCI score of 1-2 and 0.80 (95% CI: 0.79-0.81) for a CCI score of ≥3. Compared with no disease, the PRs for a diagnosis of the most prevalent, but less severe diseases, chronic pulmonary disease, cerebrovascular disease, diabetes I and II were 0.93 (95% CI: 0.93-0.94), 0.96 (95% CI: 0.94-0.96), and 0.96 (95% CI: 0.95-0.97), respectively. Among women with low prevalent, but most severe diseases, the PRs were 0.69 (95% CI: 0.60-0.81) for AIDS and 0.73 (95% CI: 0.70-0.76) for metastatic solid tumor. CONCLUSION: Women with a high CCI score or one severe chronic condition are less likely to participate in breast cancer screening compared to women without disease. However, these women account for a small proportion of all non-participating women. Thus, it might be most beneficial to maximize breast cancer screening participation in women with less severe although more common morbidities.

Modulating the antibody density changes the uptake and transport at the blood-brain barrier of both transferrin receptor-targeted gold nanoparticles and liposomal cargo.

Transport of the majority of therapeutic molecules to the brain is precluded by the presence of the blood-brain barrier (BBB) rendering efficient treatment of many neurological disorders impossible. This BBB, nonetheless, may be circumvented by targeting receptors and transport proteins expressed on the luminal surface of the brain capillary endothelial cells (BCECs). The transferrin receptor (TfR) has remained a popular target since its original description for this purpose, although clinical progression of TfR-targeted drug constructs or nanomedicines remains unsuccessful. One proposed issue pertaining to the use of TfR-targeting in nanomedicines is the efficient tuning of the ligand density on the nanoparticle surface. We studied the impact of TfR antibody density on the uptake and transport of nanoparticles into the brain, taking a parallel approach to investigate the impact on both antibody-functionalized gold nanoparticles (AuNPs) and cargo-loaded liposomes. We report that among three different low-range mean ligand densities (0.15, 0.3, and 0.6 ∗ 103 antibodies/µm2), the highest density yielded the highest ability towards both targeting of the BCECs and subsequent transport across the BBB in vivo, and in vitro using primary cultures of the murine BBB. We also find that TfR-targeting on liposomes in the mouse may induce severe adverse effects after intravenous administration.

CYPOR is a novel and independent prognostic biomarker of recurrence-free survival in triple-negative breast cancer patients.

Prognostic and predictive biomarkers of disease and treatment outcome are needed to ensure optimal treatment of patients with triple-negative breast cancer (TNBC). In a mass spectrometry-based global proteomic study of 44 formalin-fixed, paraffin-embedded (FFPE) primary TNBC tumors and 10 corresponding metastases, we found that Cytochrome P450 reductase (CYPOR) expression correlated with patient outcome. The correlation between CYPOR expression and outcome was further evaluated in a Danish cohort of 113 TNBC patients using immunohistochemistry and publicly available gene expression data from two cohorts of TNBC and basal-like breast cancer patients, respectively (N = 249 and N = 580). A significant correlation between high CYPOR gene expression and shorter recurrence-free survival (RFS), but not overall survival, was found in the cohort of 249 TNBC patients (p = 0.018, HR = 1.77, 95% CI 1.1-2.85), and this correlation was recapitulated in a cohort of 580 basal-like breast cancer patients (p = 0.018, HR = 1.4, 95% CI 1.06-1.86). High CYPOR protein expression was also associated with shorter RFS in the cohort of 113 TNBC patients (p = 0.017, HR = 2.73, 95% CI 1.20-6.19), particularly those who were lymph node tumor-negative (p = 0.029, HR = 5.22). Multivariate Cox regression analysis identified CYPOR as an independent prognostic factor for shorter RFS in TNBC patients (p = 0.032, HR = 2.19, 95% CI 1.07-4.47). Together, these data suggest high expression of CYPOR as an independent prognostic biomarker of shorter RFS, which could be used to identify patients who should receive more extensive adjuvant treatment and more aggressive surveillance.

Non-linear transformations of age at diagnosis, tumor size, and number of positive lymph nodes in prediction of clinical outcome in breast cancer.

BACKGROUND: Prognostic factors in breast cancer are often measured on a continuous scale, but categorized for clinical decision-making. The primary aim of this study was to evaluate if accounting for continuous non-linear effects of the three factors age at diagnosis, tumor size, and number of positive lymph nodes improves prognostication. These factors will most likely be included in the management of breast cancer patients also in the future, after an expected implementation of gene expression profiling for adjuvant treatment decision-making. METHODS: Four thousand four hundred forty seven and 1132 women with primary breast cancer constituted the derivation and validation set, respectively. Potential non-linear effects on the log hazard of distant recurrences of the three factors were evaluated during 10 years of follow-up. Cox-models of successively increasing complexity: dichotomized predictors, predictors categorized into three or four groups, and predictors transformed using fractional polynomials (FPs) or restricted cubic splines (RCS), were used. Predictive performance was evaluated by Harrell's C-index. RESULTS: Using FP-transformations, non-linear effects were detected for tumor size and number of positive lymph nodes in univariable analyses. For age, non-linear transformations did, however, not improve the model fit significantly compared to the linear identity transformation. As expected, the C-index increased with increasing model complexity for multivariable models including the three factors. By allowing more than one cut-point per factor, the C-index increased from 0.628 to 0.674. The additional gain, as measured by the C-index, when using FP- or RCS-transformations was modest (0.695 and 0.696, respectively). The corresponding C-indices for these four models in the validation set, based on the same transformations and parameter estimates from the derivation set, were 0.675, 0.700, 0.706, and 0.701. CONCLUSIONS: Categorization of each factor into three to four groups was found to improve prognostication compared to dichotomization. The additional gain by allowing continuous non-linear effects modeled by FPs or RCS was modest. However, the continuous nature of these transformations has the advantage of making it possible to form risk groups of any size.

Genetic Incorporation of Olefin Cross-Metathesis Reaction Tags for Protein Modification.

Olefin cross-metathesis (CM) is a viable reaction for the modification of alkene-containing proteins. Although allyl sulfide or selenide side-chain motifs in proteins can critically enhance the rate of CM reactions, no efficient method for their site-selective genetic incorporation into proteins has been reported to date. Here, through the systematic evaluation of olefin-bearing unnatural amino acids for their metabolic incorporation, we have discovered S-allylhomocysteine (Ahc) as a genetically encodable Met analogue that is not only processed by translational cellular machinery but also a privileged CM substrate residue in proteins. In this way, Ahc was used for efficient Met codon reassignment in a Met-auxotrophic strain of E. coli (B834 (DE3)) as well as metabolic labeling of protein in human cells and was reactive toward CM in several representative proteins. This expands the use of CM in the toolkit for "tag-and-modify" functionalization of proteins.

SNAI2 upregulation is associated with an aggressive phenotype in fulvestrant-resistant breast cancer cells and is an indicator of poor response to endocrine therapy in estrogen receptor-positive metastatic breast cancer.

BACKGROUND: Endocrine resistance in estrogen receptor-positive (ER+) breast cancer is a major clinical problem and is associated with accelerated cancer cell growth, increased motility and acquisition of mesenchymal characteristics. However, the specific molecules and pathways involved in these altered features remain to be detailed, and may be promising therapeutic targets to overcome endocrine resistance. METHODS: In the present study, we evaluated altered expression of epithelial-mesenchymal transition (EMT) regulators in ER+ breast cancer cell models of tamoxifen or fulvestrant resistance, by gene expression profiling. We investigated the specific role of increased SNAI2 expression in fulvestrant-resistant cells by gene knockdown and treatment with a SNAIL-p53 binding inhibitor, and evaluated the effect on cell growth, migration and expression of EMT markers. Furthermore, we evaluated SNAI2 expression by immunohistochemical analysis in metastatic samples from two cohorts of patients with breast cancer treated with endocrine therapy in the advanced setting. RESULTS: SNAI2 was found to be significantly upregulated in all endocrine-resistant cells compared to parental cell lines, while no changes were observed in the expression of other EMT-associated transcription factors. SNAI2 knockdown with specific small interfering RNA (siRNA) converted the mesenchymal-like fulvestrant-resistant cells into an epithelial-like phenotype and reduced cell motility. Furthermore, inhibition of SNAI2 with specific siRNA or a SNAIL-p53 binding inhibitor reduced growth of cells resistant to fulvestrant treatment. Clinical evaluation of SNAI2 expression in two independent cohorts of patients with ER+ metastatic breast cancer treated with endocrine therapy in the advanced setting (N = 86 and N = 67) showed that high SNAI2 expression in the metastasis correlated significantly with shorter progression-free survival on endocrine treatment (p = 0.0003 and p = 0.004). CONCLUSIONS: Our results suggest that SNAI2 is a key regulator of the aggressive phenotype observed in endocrine-resistant breast cancer cells, an independent prognostic biomarker in ER+ advanced breast cancer treated with endocrine therapy, and may be a promising therapeutic target in combination with endocrine therapies in ER+ metastatic breast cancer exhibiting high SNAI2 levels.

Antibody affinity and valency impact brain uptake of transferrin receptor-targeted gold nanoparticles.

Rationale: The ability to treat invalidating neurological diseases is impeded by the presence of the blood-brain barrier (BBB), which inhibits the transport of most blood-borne substances into the brain parenchyma. Targeting the transferrin receptor (TfR) on the surface of brain capillaries has been a popular strategy to give a preferential accumulation of drugs or nanomedicines, but several aspects of this targeting strategy remain elusive. Here we report that TfR-targeted gold nanoparticles (AuNPs) can accumulate in brain capillaries and further transport across the BBB to enter the brain parenchyma. Methods: We characterized our targeting strategy both in vitro using primary models of the BBB and in vivo using quantitative measurements of gold accumulation by inductively-coupled plasma-mass spectrometry together with morphological assessments using light microscopy after silver enhancement and transmission electron microscopy with energy-dispersive X-ray spectroscopy. Results: We find that the uptake capacity is significantly modulated by the affinity and valency of the AuNP-conjugated antibodies. Specifically, antibodies with high and low affinities mediate a low and intermediate uptake of AuNPs into the brain, respectively, whereas a monovalent (bi-specific) antibody improves the uptake capacity remarkably. Conclusion: Our findings indicate that monovalent ligands may be beneficial for obtaining transcytosis of TfR-targeted nanomedicines across the BBB, which is relevant for future design of nanomedicines for brain drug delivery.

Association of miR-548c-5p, miR-7-5p, miR-210-3p, miR-128-3p with recurrence in systemically untreated breast cancer.

Current prognostic markers allocate the majority of lymph node (LN) negative and estrogen receptor (ER) positive breast cancer patients into the high-risk group. Accordingly, most patients receive systemic treatments although approximately 40% of these patients may have been cured by surgery and radiotherapy alone. Two studies identified seven prognostic microRNAs in systemically untreated, LN negative and ER positive breast cancer patients which may allow more precise patient classification. However, six of the seven microRNAs were analyzed in both studies but only found to be prognostic in one study. To validate their prognostic potential, we analyzed microRNA expression in an independent cohort (n = 110) using a pair-matched study design minimizing dependence of classical markers. The expression of hsa-miR-548c-5p was significantly associated with abridged disease-free survival (hazard ratio [HR]:1.96, p = 0.027). Contradicting published results, high hsa-miR-516-3p expression was associated with favorable outcome (HR:0.29, p = 0.0068). The association is probably time-dependent indicating later relapse. Additionally, re-analysis of previously published expression data of two matching cohorts (n = 100, n = 255) supports an association of hsa-miR-128-3p with shortened disease-free survival (HR:2.48, p = 0.0033) and an upregulation of miR-7-5p (p = 0.0038; p = 0.039) and miR-210-3p (p = 0.031) in primary tumors of patients who experienced metastases. Further analysis may verify the prognostic potential of these microRNAs.

Identification of metastasis driver genes by massive parallel sequencing of successive steps of breast cancer progression.

Cancer results from alterations at essential genomic sites and is characterized by uncontrolled cell proliferation, invasion and metastasis. Identification of driver genes of metastatic progression is essential, as metastases, not primary tumors, are fatal. To gain insight into the mutational concordance between different steps of malignant progression we performed exome sequencing and validation with targeted deep sequencing of successive steps of malignant progression from pre-invasive stages to asynchronous distant metastases in six breast cancer patients. Using the ratio of non-synonymous to synonymous mutations, a surprisingly large number of cancer driver genes, ranging between 3 and 145, were estimated to confer a selective advantage in the studied primary tumors. We report a substantial amount of metastasis specific mutations and a number of novel putative metastasis driver genes. Most notable are the DCC, ABCA13, TIAM2, CREBBP, BCL6B and ZNF185 genes, mainly mutated exclusively in metastases and highly likely driver genes of metastatic progression. We find different genes and pathways to be affected at different steps of malignant progression. The Adherens junction pathway is affected in four of the six studied patients and this pathway most likely plays a vital role in the metastatic process.