One-year recovery from breast cancer: Importance of tumor and treatment-related factors, resilience, and sociodemographic factors for health-related quality of life.

Aim: This study investigated the changes in health-related quality of life from diagnosis to 1 year after diagnosis in breast cancer (BC) patients and the influence of clinical, psychological, and sociodemographic variables. An additional aim was to explore the mediating and moderating effects of resilience on changes in health-related quality of life. Methods: A longitudinal population-based study was conducted in southern Sweden. Newly diagnosed BC patients filled in measures of health-related quality of life, resilience, and sociodemographic variables at diagnosis (N = 980) and 1 year post-diagnosis (N = 780). Clinical variables were extracted from the Swedish national breast cancer quality registry. Mixed-model analyses were performed. Results: Most health-related quality of life outcomes declined from diagnosis to 1 year post-diagnosis. Role limitations due to emotional problems remained the same, whereas mental health improved. Lower health-related quality of life outcomes were associated with symptomatic detection and axillary dissection. Patients with a higher TNM stage and histologic grade and estrogen receptor (ER)-negative and human epidermal growth factor 2 (HER2)-positive status, who received chemotherapy, antibody therapy, or bisphosphonate therapy, had a steeper decline in outcomes. Changes in resilience were positively associated with all outcomes but did not mediate or moderate changes in any. Resilience at baseline moderated changes in bodily pain, vitality, and mental health, with higher baseline resilience being associated with a steeper decline, possibly due to floor or ceiling effects. Patients with lower socioeconomic status, educational level, and older age had a lower health-related quality of life. Conclusion: Physical health-related quality of life among breast cancer patients declined 1 year post-diagnosis, whereas mental health-related quality of life improved. Low resilient patients may be especially vulnerable at diagnosis. Biopsychosocial assessment at diagnosis can help identify patients who may require additional support. A multidimensional treatment plan should be started early to help overcome the problems in everyday activities.

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer.

Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 (five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high (90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests.

How Reliable Are Gene Expression-Based and Immunohistochemical Biomarkers Assessed on a Core-Needle Biopsy? A Study of Paired Core-Needle Biopsies and Surgical Specimens in Early Breast Cancer.

In early breast cancer, a preoperative core-needle biopsy (CNB) is vital to confirm the malignancy of suspected lesions and for assessing the expression of treatment predictive and prognostic biomarkers in the tumor to choose the optimal treatments, emphasizing the importance of obtaining reliable results when biomarker status is assessed on a CNB specimen. This study aims to determine the concordance between biomarker status assessed as part of clinical workup on a CNB compared to a medically untreated surgical specimen. Paired CNB and surgical specimens from 259 patients that were part of the SCAN-B cohort were studied. The concordance between immunohistochemical (IHC) and gene expression (GEX) based biomarker status was investigated. Biomarkers of interest included estrogen receptor (ER; specifically, the alpha variant), progesterone receptor (PgR), Ki67, HER2, and tumor molecular subtype. In general, moderate to very good correlation in biomarker status between the paired CNB and surgical specimens was observed for both IHC assessment (83-99% agreement, kappa range 0.474-0.917) and GEX assessment (70-97% agreement, kappa range 0.552-0.800), respectively. However, using IHC, 52% of cases with low Ki67 status in the CNB shifted to high Ki67 status in the surgical specimen (McNemar's p = 0.011). Similarly, when using GEX, a significant shift from negative to positive ER (47%) and from low to high Ki67 (16%) was observed between the CNB and surgical specimen (McNemar's p = 0.027 and p = 0.002 respectively). When comparing biomarker status between different techniques (IHC vs. GEX) performed on either CNBs or surgical specimens, the agreement in ER, PgR, and HER2 status was generally over 80% in both CNBs and surgical specimens (kappa range 0.395-0.708), but Ki67 and tumor molecular subtype showed lower concordance levels between IHC and GEX (48-62% agreement, kappa range 0.152-0.398). These results suggest that both the techniques used for collecting tissue samples and analyzing biomarker status have the potential to affect the results of biomarker assessment, potentially also impacting treatment decisions and patient survival outcomes.

Psychological Resilience and Health-Related Quality of Life in 418 Swedish Women with Primary Breast Cancer: Results from a Prospective Longitudinal Study.

Psychological resilience is considered a major protective psychological mechanism that enables a person to successfully handle significant adversities, e.g., a cancer diagnosis. Higher levels of resilience have been associated with higher levels of health-related quality of life (HRQoL) in breast cancer (BC) patients, but research examining the longitudinal process of resilience is limited. The aim of this population-based longitudinal study was to investigate resilience and HRQoL from diagnosis to one year later in 418 Swedish women with primary BC. Resilience was measured with the Connor-Davidson Resilience Scale 25, and HRQoL was measured with the Short Form Health Survey. The participants responded to questions regarding demographic and study-specific variables. Clinicopathological variables were collected from the Swedish National Quality Register for Breast Cancer. The mean score for resilience was 70.6 (standard deviation, SD = 13.0) at diagnosis and 68.9 (SD = 14.0) one year later, p < 0.001. The level of trust in the treatment and financial situation demonstrated the greatest association with the change in resilience levels. No oncological treatment modality was associated with a change in resilience levels. HRQoL decreased over time in the cohort. Resilience was positively associated with HRQoL at one year post diagnosis, which demonstrates that resilience is an important factor in maintaining HRQoL.

Preexisting Somatic Mutations of Estrogen Receptor Alpha (ESR1) in Early-Stage Primary Breast Cancer.

Background: More than three-quarters of primary breast cancers are positive for estrogen receptor alpha (ER; encoded by the gene ESR1), the most important factor for directing anti-estrogenic endocrine therapy (ET). Recently, mutations in ESR1 were identified as acquired mechanisms of resistance to ET, found in 12% to 55% of metastatic breast cancers treated previously with ET. Methods: We analyzed 3217 population-based invasive primary (nonmetastatic) breast cancers (within the SCAN-B study, ClinicalTrials.gov NCT02306096), sampled from initial diagnosis prior to any treatment, for the presence of ESR1 mutations using RNA sequencing. Mutations were verified by droplet digital polymerase chain reaction on tumor and normal DNA. Patient outcomes were analyzed using Kaplan-Meier estimation and a series of 2-factor Cox regression multivariable analyses. Results: We identified ESR1 resistance mutations in 30 tumors (0.9%), of which 29 were ER positive (1.1%). In ET-treated disease, presence of ESR1 mutation was associated with poor relapse-free survival and overall survival (2-sided log-rank test P < .001 and P = .008, respectively), with hazard ratios of 3.00 (95% confidence interval = 1.56 to 5.88) and 2.51 (95% confidence interval = 1.24 to 5.07), respectively, which remained statistically significant when adjusted for other prognostic factors. Conclusions: These population-based results indicate that ESR1 mutations at diagnosis of primary breast cancer occur in about 1% of women and identify for the first time in the adjuvant setting that such preexisting mutations are associated to eventual resistance to standard hormone therapy. If replicated, tumor ESR1 screening should be considered in ER-positive primary breast cancer, and for patients with mutated disease, ER degraders such as fulvestrant or other therapeutic options may be considered as more appropriate.

"Association of mammographic features with molecular breast tumor profiles".

PURPOSE: Mammographic density and tumor appearance are breast cancer prognostic factors. Conceivably, mammographic features are macroscopic reflections of tumor´s molecular composition, but to an unknown extent. Our aim was to study associations of mammographic features with molecular tumor profiles. METHODS: Invasive breast cancers (2007-2016) in Malmö Diet and Cancer Study (MDCS) for which there were tumor RNA-sequencing analyses within Sweden Cancerome Analysis Network - Breast (SCAN-B) (n=102) or All Breast Cancer in Malmö (ABIM) (n=50) were identified. Density (fatty vs. dense), tumor appearance (mass vs. spiculation), and intrinsic subtypes were registered. Differences in gene/metagene expression and Microenvironment Cell Population Counter were analyzed with R. Overall survival was used as endpoint. RESULTS: No gene expression differences between density groups was observed. In one cohort (but not the other), Luminal A tumors associated with fatty breasts. For spiculation vs. mass, (p<0.01, t-test) 86 genes were differentially expressed; only one gene was differentially expressed comparing density. Gene set enrichment analysis showed genes highly expressed in spiculated tumors were enriched for extracellular matrix-associated genes whereas genes highly expressed with masses were associated with proliferation. A spiculation metagene, based on differentially expressed genes, showed association with estrogen receptor positivity, lower grade, and improved survival, but it was not an independent prognostic factor. CONCLUSION: There are clear differences in molecular composition between breast tumors with a spiculated appearance vs. a mass as the dominant tumor appearance. However, there are no apparent molecular differences related to the density of the breast in which the tumor has arisen.

Identification of extracellular matrix proteins secreted by human dermal fibroblasts cultured in 3D electrospun scaffolds.

The appreciation that cell interactions in tissues is dependent on their three dimensional (3D) distribution has stimulated the development of 3D cell culture models. We constructed an artificial 3D tumour by culturing human breast cancer JIMT-1 cells and human dermal fibroblasts (HDFs) in a 3D network of electrospun polycaprolactone fibres. Here, we investigate ECM components produced by the cells in the artificial 3D tumour, which is an important step in validating the model. Immunostaining and confocal fluorescence microscopy show that the ECM proteins fibronectin, collagen I, and laminin are deposited throughout the entire 3D structure. Secreted soluble factors including matrix metalloproteinases (MMPs) and interleukine-6 (IL-6) were analysed in collected medium and were found to be mainly derived from the HDFs. Treatment with transforming growth factor-ß1 (TGF-ß1), a major cytokine found in a tumour, significantly alters the MMP activity and IL-6 concentration. In addition, TGF-ß1 treatment, changes the morphology of the HDFs to become more elongated and with increased linearized actin filaments compared to non-treated HDFs. Collectively, these novel findings suggest that the artificial 3D tumour displays a clear cell distribution and ECM deposition that resembles a tumour environment in vivo, suggesting an innovative biological model to study a human tumour.

Psychological Resilience and Health-Related Quality of Life in Swedish Women with Newly Diagnosed Breast Cancer.

PURPOSE: Psychological resilience appears to be an important influencing factor in various aspects of health-related quality of life (HRQoL) in a context of adversity, eg, being informed of a cancer diagnosis. The purpose was to investigate psychological resilience and HRQoL in Swedish women with newly diagnosed breast cancer in relation to demographic and clinicopathological characteristics. METHODS: A population-based cross-sectional study was conducted including 517 women with breast cancer in the South Swedish Health Care Region. Participants were enrolled at the time of consultation for the diagnosis. Psychological resilience was assessed with the Connor-Davidson Resilience Scale 25 (CD-RISC25), and HRQoL was assessed with the Short Form Health Survey. The participants responded to questions regarding demographic variables. Clinicopathological data were collected from the Swedish National Quality Register for Breast Cancer. RESULTS: The mean score for psychological resilience was 70.6, identifying 15% of included patients with a score lower than 58 (-1 standard deviation). The study cohort had significantly lower mean scores for several aspects of HRQoL compared with Swedish normative data. Regression analyses demonstrated that psychological resilience was significantly associated with all domains of HRQoL after adjustment for demographic and clinicopathological factors. CONCLUSION: Higher levels of psychological resilience were significantly related to higher levels of HRQoL in Swedish women with newly diagnosed breast cancer and no modifying factor was identified. The assessment of psychological resilience at the time of breast cancer diagnosis might allow for early identification of women in need of more intense psychosocial support. Future studies are needed to identify a clinically relevant threshold of the CD-RISC25.

The mutational landscape of the SCAN-B real-world primary breast cancer transcriptome.

Breast cancer is a disease of genomic alterations, of which the panorama of somatic mutations and how these relate to subtypes and therapy response is incompletely understood. Within SCAN-B (ClinicalTrials.gov: NCT02306096), a prospective study elucidating the transcriptomic profiles for thousands of breast cancers, we developed a RNA-seq pipeline for detection of SNVs/indels and profiled a real-world cohort of 3,217 breast tumors. We describe the mutational landscape of primary breast cancer viewed through the transcriptome of a large population-based cohort and relate it to patient survival. We demonstrate that RNA-seq can be used to call mutations in genes such as PIK3CA, TP53, and ERBB2, as well as the status of molecular pathways and mutational burden, and identify potentially druggable mutations in 86.8% of tumors. To make this rich dataset available for the research community, we developed an open source web application, the SCAN-B MutationExplorer (http://oncogenomics.bmc.lu.se/MutationExplorer). These results add another dimension to the use of RNA-seq as a clinical tool, where both gene expression- and mutation-based biomarkers can be interrogated in real-time within 1 week of tumor sampling.

Prognostic implications of the expression levels of different immunoglobulin heavy chain-encoding RNAs in early breast cancer.

The extent and composition of the immune response in a breast cancer is one important prognostic factor for the disease. The aim of the current work was to refine the analysis of the humoral component of an immune response in breast tumors by quantifying mRNA expression of different immunoglobulin classes and study their association with prognosis. We used RNA-Seq data from two local population-based breast cancer cohorts to determine the expression of IGJ and immunoglobulin heavy (IGH) chain-encoding RNAs. The association with prognosis was investigated and public data sets were used to corroborate the findings. Except for IGHE and IGHD, mRNAs encoding heavy chains were generally detected at substantial levels and correlated with other immune-related genes. High IGHG1 mRNA was associated with factors related to poor prognosis such as estrogen receptor negativity, HER2 amplification, and high grade, whereas high IGHA2 mRNA levels were primarily associated with lower age at diagnosis. High IGHA2 and IGJ mRNA levels were associated with a more favorable prognosis both in univariable and multivariable Cox models. When adjusting for other prognostic factors, high IGHG1 mRNA levels were positively associated with improved prognosis. To our knowledge, these results are the first to demonstrate that expression of individual Ig class types has prognostic implications in breast cancer.

Comprehensive molecular comparison of BRCA1 hypermethylated and BRCA1 mutated triple negative breast cancers.

Homologous recombination deficiency (HRD) is a defining characteristic in BRCA-deficient breast tumors caused by genetic or epigenetic alterations in key pathway genes. We investigated the frequency of BRCA1 promoter hypermethylation in 237 triple-negative breast cancers (TNBCs) from a population-based study using reported whole genome and RNA sequencing data, complemented with analyses of genetic, epigenetic, transcriptomic and immune infiltration phenotypes. We demonstrate that BRCA1 promoter hypermethylation is twice as frequent as BRCA1 pathogenic variants in early-stage TNBC and that hypermethylated and mutated cases have similarly improved prognosis after adjuvant chemotherapy. BRCA1 hypermethylation confers an HRD, immune cell type, genome-wide DNA methylation, and transcriptional phenotype similar to TNBC tumors with BRCA1-inactivating variants, and it can be observed in matched peripheral blood of patients with tumor hypermethylation. Hypermethylation may be an early event in tumor development that progress along a common pathway with BRCA1-mutated disease, representing a promising DNA-based biomarker for early-stage TNBC.

Whole-genome sequencing of triple-negative breast cancers in a population-based clinical study.

Whole-genome sequencing (WGS) brings comprehensive insights to cancer genome interpretation. To explore the clinical value of WGS, we sequenced 254 triple-negative breast cancers (TNBCs) for which associated treatment and outcome data were collected between 2010 and 2015 via the population-based Sweden Cancerome Analysis Network-Breast (SCAN-B) project (ClinicalTrials.gov ID:NCT02306096). Applying the HRDetect mutational-signature-based algorithm to classify tumors, 59% were predicted to have homologous-recombination-repair deficiency (HRDetect-high): 67% explained by germline/somatic mutations of BRCA1/BRCA2, BRCA1 promoter hypermethylation, RAD51C hypermethylation or biallelic loss of PALB2. A novel mechanism of BRCA1 abrogation was discovered via germline SINE-VNTR-Alu retrotransposition. HRDetect provided independent prognostic information, with HRDetect-high patients having better outcome on adjuvant chemotherapy for invasive disease-free survival (hazard ratio (HR) = 0.42; 95% confidence interval (CI) = 0.2-0.87) and distant relapse-free interval (HR = 0.31, CI = 0.13-0.76) compared to HRDetect-low, regardless of whether a genetic/epigenetic cause was identified. HRDetect-intermediate, some possessing potentially targetable biological abnormalities, had the poorest outcomes. HRDetect-low cancers also had inadequate outcomes: ~4.7% were mismatch-repair-deficient (another targetable defect, not typically sought) and they were enriched for (but not restricted to) PIK3CA/AKT1 pathway abnormalities. New treatment options need to be considered for now-discernible HRDetect-intermediate and HRDetect-low categories. This population-based study advocates for WGS of TNBC to better inform trial stratification and improve clinical decision-making.

Cross comparison and prognostic assessment of breast cancer multigene signatures in a large population-based contemporary clinical series.

Multigene expression signatures provide a molecular subdivision of early breast cancer associated with patient outcome. A gap remains in the validation of such signatures in clinical treatment groups of patients within population-based cohorts of unselected primary breast cancer representing contemporary disease stages and current treatments. A cohort of 3520 resectable breast cancers with RNA sequencing data included in the population-based SCAN-B initiative (ClinicalTrials.gov ID NCT02306096) were selected from a healthcare background population of 8587 patients diagnosed within the years 2010-2015. RNA profiles were classified according to 19 reported gene signatures including both gene expression subtypes (e.g. PAM50, IC10, CIT) and risk predictors (e.g. Oncotype DX, 70-gene, ROR). Classifications were analyzed in nine adjuvant clinical assessment groups: TNBC-ACT (adjuvant chemotherapy, n = 239), TNBC-untreated (n = 82), HER2+/ER- with anti-HER2+ ACT treatment (n = 110), HER2+/ER+ with anti-HER2 + ACT + endocrine treatment (n = 239), ER+/HER2-/LN- with endocrine treatment (n = 1113), ER+/HER2-/LN- with endocrine + ACT treatment (n = 243), ER+/HER2-/LN+ with endocrine treatment (n = 423), ER+/HER2-/LN+ with endocrine + ACT treatment (n = 433), and ER+/HER2-/LN- untreated (n = 200). Gene signature classification (e.g., proportion low-, high-risk) was generally well aligned with stratification based on current immunohistochemistry-based clinical practice. Most signatures did not provide any further risk stratification in TNBC and HER2+/ER- disease. Risk classifier agreement (low-, medium/intermediate-, high-risk groups) in ER+ assessment groups was on average 50-60% with occasional pair-wise comparisons having <30% agreement. Disregarding the intermediate-risk groups, the exact agreement between low- and high-risk groups was on average ~80-95%, for risk prediction signatures across all assessment groups. Outcome analyses were restricted to assessment groups of TNBC-ACT and endocrine treated ER+/HER2-/LN- and ER+/HER2-/LN+ cases. For ER+/HER2- disease, gene signatures appear to contribute additional prognostic value even at a relatively short follow-up time. Less apparent prognostic value was observed in the other groups for the tested signatures. The current study supports the usage of gene expression signatures in specific clinical treatment groups within population-based breast cancer. It also stresses the need of further development to reach higher consensus in individual patient classifications, especially for intermediate-risk patients, and the targeting of patients where current gene signatures and prognostic variables provide little support in clinical decision-making.

Agreement between molecular subtyping and surrogate subtype classification: a contemporary population-based study of ER-positive/HER2-negative primary breast cancer.

PURPOSE: Oestrogen receptor-positive (ER+) and human epidermal receptor 2-negative (HER2-) breast cancers are classified as Luminal A or B based on gene expression, but immunohistochemical markers are used for surrogate subtyping. The aims of this study were to examine the agreement between molecular subtyping (MS) and surrogate subtyping and to identify subgroups consisting mainly of Luminal A or B tumours. METHODS: The cohort consisted of 2063 patients diagnosed between 2013-2017, with primary ER+/HER2- breast cancer, analysed by RNA sequencing. Surrogate subtyping was performed according to three algorithms (St. Gallen 2013, Maisonneuve and our proposed Grade-based classification). Agreement (%) and kappa statistics (κ) were used as concordance measures and ROC analysis for luminal distinction. Ki67, progesterone receptor (PR) and histological grade (HG) were further investigated as surrogate markers. RESULTS: The agreement rates between the MS and St. Gallen 2013, Maisonneuve and Grade-based classifications were 62% (κ = 0.30), 66% (κ = 0.35) and 70% (κ = 0.41), respectively. PR did not contribute to distinguishing Luminal A from B tumours (auROC = 0.56). By classifying HG1-2 tumours as Luminal A-like and HG3 as Luminal B-like, agreement with MS was 80% (κ = 0.46). Moreover, by combining HG and Ki67 status, a large subgroup of patients (51% of the cohort) having > 90% Luminal A tumours could be identified. CONCLUSIONS: Agreement between MS and surrogate classifications was generally poor. However, a post hoc analysis showed that a combination of HG and Ki67 could identify patients very likely to have Luminal A tumours according to MS.

Prediction of Lymph Node Metastasis in Breast Cancer by Gene Expression and Clinicopathological Models: Development and Validation within a Population-Based Cohort.

PURPOSE: More than 70% of patients with breast cancer present with node-negative disease, yet all undergo surgical axillary staging. We aimed to define predictors of nodal metastasis using clinicopathological characteristics (CLINICAL), gene expression data (GEX), and mixed features (MIXED) and to identify patients at low risk of metastasis who might be spared sentinel lymph node biopsy (SLNB).Experimental Design: Breast tumors (n = 3,023) from the population-based Sweden Cancerome Analysis Network-Breast initiative were profiled by RNA sequencing and linked to clinicopathologic characteristics. Seven machine-learning models present the discriminative ability of N0/N+ in development (n = 2,278) and independent validation cohorts (n = 745) stratified as ER+HER2-, HER2+, and TNBC. Possible SLNB reduction rates are proposed by applying CLINICAL and MIXED predictors. RESULTS: In the validation cohort, the MIXED predictor showed the highest area under ROC curves to assess nodal metastasis; AUC = 0.72. For the subgroups, the AUCs for MIXED, CLINICAL, and GEX predictors ranged from 0.66 to 0.72, 0.65 to 0.73, and 0.58 to 0.67, respectively. Enriched proliferation metagene and luminal B features were noticed in node-positive ER+HER2- and HER2+ tumors, while upregulated basal-like features were observed in node-negative TNBC tumors. The SLNB reduction rates in patients with ER+HER2- tumors were 6% to 7% higher for the MIXED predictor compared with the CLINICAL predictor accepting false negative rates of 5% to 10%. CONCLUSIONS: Although CLINICAL and MIXED predictors of nodal metastasis had comparable accuracy, the MIXED predictor identified more node-negative patients. This translational approach holds promise for development of classifiers to reduce the rates of SLNB for patients at low risk of nodal involvement.

Refinement of breast cancer molecular classification by miRNA expression profiles.

BACKGROUND: Accurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction. RESULTS: We found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day's signatures. CONCLUSIONS: We show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.

The Molecular Basis for Inhibition of Stemlike Cancer Cells by Salinomycin.

Tumors are phenotypically heterogeneous and include subpopulations of cancer cells with stemlike properties. The natural product salinomycin, a K+-selective ionophore, was recently found to exert selectivity against such cancer stem cells. This selective effect is thought to be due to inhibition of the Wnt signaling pathway, but the mechanistic basis remains unclear. Here, we develop a functionally competent fluorescent conjugate of salinomycin to investigate the molecular mechanism of this compound. By subcellular imaging, we demonstrate a rapid cellular uptake of the conjugate and accumulation in the endoplasmic reticulum (ER). This localization is connected to induction of Ca2+ release from the ER into the cytosol. Depletion of Ca2+ from the ER induces the unfolded protein response as shown by global mRNA analysis and Western blot analysis of proteins in the pathway. In particular, salinomycin-induced ER Ca2+ depletion up-regulates C/EBP homologous protein (CHOP), which inhibits Wnt signaling by down-regulating ß-catenin. The increased cytosolic Ca2+ also activates protein kinase C, which has been shown to inhibit Wnt signaling. These results reveal that salinomycin acts in the ER membrane of breast cancer cells to cause enhanced Ca2+ release into the cytosol, presumably by mediating a counter-flux of K+ ions. The clarified mechanistic picture highlights the importance of ion fluxes in the ER as an entry to inducing phenotypic effects and should facilitate rational development of cancer treatments.

Clinical Value of RNA Sequencing-Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network-Breast Initiative.

PURPOSE: In early breast cancer (BC), five conventional biomarkers-estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, and Nottingham histologic grade (NHG)-are used to determine prognosis and treatment. We aimed to develop classifiers for these biomarkers that were based on tumor mRNA sequencing (RNA-seq), compare classification performance, and test whether such predictors could add value for risk stratification. METHODS: In total, 3,678 patients with BC were studied. For 405 tumors, a comprehensive multi-rater histopathologic evaluation was performed. Using RNA-seq data, single-gene classifiers and multigene classifiers (MGCs) were trained on consensus histopathology labels. Trained classifiers were tested on a prospective population-based series of 3,273 BCs that included a median follow-up of 52 months (Sweden Cancerome Analysis Network-Breast [SCAN-B], ClinicalTrials.gov identifier: NCT02306096), and results were evaluated by agreement statistics and Kaplan-Meier and Cox survival analyses. RESULTS: Pathologist concordance was high for ER, PgR, and HER2 (average κ, 0.920, 0.891, and 0.899, respectively) but moderate for Ki67 and NHG (average κ, 0.734 and 0.581). Concordance between RNA-seq classifiers and histopathology for the independent cohort of 3,273 was similar to interpathologist concordance. Patients with discordant classifications, predicted as hormone responsive by histopathology but non-hormone responsive by MGC, had significantly inferior overall survival compared with patients who had concordant results. This extended to patients who received no adjuvant therapy (hazard ratio [HR], 3.19; 95% CI, 1.19 to 8.57), or endocrine therapy alone (HR, 2.64; 95% CI, 1.55 to 4.51). For cases identified as hormone responsive by histopathology and who received endocrine therapy alone, the MGC hormone-responsive classifier remained significant after multivariable adjustment (HR, 2.45; 95% CI, 1.39 to 4.34). CONCLUSION: Classification error rates for RNA-seq-based classifiers for the five key BC biomarkers generally were equivalent to conventional histopathology. However, RNA-seq classifiers provided added clinical value in particular for tumors determined by histopathology to be hormone responsive but by RNA-seq to be hormone insensitive.

Structure-Activity Relationships in Salinomycin: Cytotoxicity and Phenotype Selectivity of Semi-synthetic Derivatives.

The ionophore salinomycin has attracted attention for its exceptional ability to selectively reduce the proportion of cells with stem-like properties in cancer cell populations of varying origin. Targeting the tumorigenicity of such cells is of interest as they are implicated in recurrence, metastasis, and drug resistance. Structural derivatives of salinomycin are thus sought after, both as tools for probing the molecular mechanism(s) underlying the observed phenotype effects, and for improving selectivity and activity against cancer stem cells. Synthetic strategies for modification of each of the directly accessible functional groups of salinomycin are presented and the resulting library of analogues was investigated to establish structure-activity relationships, both with respect to cytotoxicity and phenotype selectivity in breast cancer cells. 20-O-Acylated derivatives stand out by exhibiting both improved selectivity and activity. Mechanistically, the importance of the ionophore properties of salinomycin is highlighted by a significant loss of activity by modifications directly interfering with either of the two primary ion coordinating motifs in salinomycin, the C11 ketone and the C1 carboxylate.

Breast cancer stem cell selectivity of synthetic nanomolar-active salinomycin analogs.

BACKGROUND: Cancer stem cells (CSCs) have been invoked in resistance, recurrence and metastasis of cancer. Consequently, curative cancer treatments may be contingent on CSC selective approaches. Of particular interest in this respect is the ionophore salinomycin, a natural product shown to be 100-fold more active against CSCs than clinically used paclitaxel. We have previously reported that synthetic salinomycin derivatives display increased activity against breast cancer cell lines. Herein we specifically investigate the CSC selectivity of the most active member in each class of C20-O-acylated analogs as well as a C1-methyl ester analog incapable of charge-neutral metal ion transport. METHODS: JIMT-1 breast cancer cells were treated with three C20-O-acylated analogs, the C1-methyl ester of salinomycin, and salinomycin. The effects of treatment on the CSC-related CD44(+)/CD24(-) and the aldehyde dehydrogenase positive (ALDH(+)) populations were determined using flow cytometry. The survival ability of CSCs after treatment was investigated with a colony formation assay under serum free conditions. The effect of the compounds on cell migration was evaluated using wound-healing and Boyden chamber assays. The expression of vimentin, related to mesenchymal traits and expression of E-cadherin and ß-catenin, related to the epithelial traits, were investigated using immunofluorescence microscopy. RESULTS: Treatment with each of the three C20-acylated analogs efficiently decreased the putative CSC population as reflected by reduction of the CD44(+)/CD24(-) and ALDH(+) populations already at a 50 nM concentration. In addition, colony forming efficiency and cell migration were reduced, and the expression of the epithelial markers E-cadherin and ß-catenin at the cell surface were increased. In contrast, salinomycin used at the same concentration did not significantly influence the CSC population and the C1-methyl ester was inactive even at a 20 µM concentration. CONCLUSIONS: Synthetic structural analogs of salinomycin, previously shown to exhibit increased activity against cancer cells, also exhibited improved activity against CSCs across several assays even at nanomolar concentrations where salinomycin was found inactive. The methyl ester analog of salinomycin, incapable of charge-neutral metal ion transport, did not show activity in CSC assays, lending experimental support to ionophoric stress as the molecular initiating event for the CSC effects of salinomycin and related structures.