Explore the vast range of titles available.

Background The four intrinsic subtypes of breast cancer, defined by differential expression of 50 genes (PAM50), have been shown to be predictive of risk of recurrence and benefit of hormonal therapy and chemotherapy. Here we describe the development of Prosigna™, a PAM50-based subtype classifier and risk model on the NanoString nCounter Dx Analysis System intended for decentralized testing in clinical laboratories. Methods 514 formalin-fixed, paraffin-embedded (FFPE) breast cancer patient samples were used to train prototypical centroids for each of the intrinsic subtypes of breast cancer on the NanoString platform. Hierarchical cluster analysis of gene expression data was used to identify the prototypical centroids defined in previous PAM50 algorithm training exercises. 304 FFPE patient samples from a well annotated clinical cohort in the absence of adjuvant systemic therapy were then used to train a subtype-based risk model (i.e. Prosigna ROR score). 232 samples from a tamoxifen-treated patient cohort were used to verify the prognostic accuracy of the algorithm prior to initiating clinical validation studies. Results The gene expression profiles of each of the four Prosigna subtype centroids were consistent with those previously published using the PCR-based PAM50 method. Similar to previously published classifiers, tumor samples classified as Luminal A by Prosigna had the best prognosis compared to samples classified as one of the three higher-risk tumor subtypes. The Prosigna Risk of Recurrence (ROR) score model was verified to be significantly associated with prognosis as a continuous variable and to add significant information over both commonly available IHC markers and Adjuvant! Online. Conclusions The results from the training and verification data sets show that the FDA-cleared and CE marked Prosigna test provides an accurate estimate of the risk of distant recurrence in hormone receptor positive breast cancer and is also capable of identifying a tumor's intrinsic subtype that is consistent with the previously published PCR-based PAM50 assay. Subsequent analytical and clinical validation studies confirm the clinical accuracy and technical precision of the Prosigna PAM50 assay in a decentralized setting.

Exosomes are stable nanovesicles secreted by cells into the circulation. Their reported sizes differ substantially, which likely reflects the difference in the isolation techniques used, the cells that secreted them, and the methods used in their characterization. We analyzed the influence of the last factor on the measured sizes and shapes of hydrated and desiccated exosomes isolated from the serum of a pancreatic cancer patient and a healthy control. We found that hydrated exosomes are close-to-spherical nanoparticles with a hydrodynamic radius that is substantially larger than the geometric size. For desiccated exosomes, we found that the desiccated shape and sizing are influenced by the manner in which drying occurred. Isotropic desiccation in aerosol preserves the near-spherical shape of the exosomes, whereas drying on a surface likely distorts their shapes and influences the sizing results obtained by techniques that require surface fixation prior to analysis.

Imatinib mesylate (IM) is a first-line treatment option for patients with chronic myeloid leukemia (CML). Patients who fail or are intolerant to IM therapy are treated with more expensive second and third-generation tyrosine kinase inhibitors. Patients show wide variation in trough concentrations in response to standard dosing. Thus, many patients receive subtherapeutic or supratherapeutic doses. Therapeutic drug monitoring (TDM) may improve dose management that, in turn, may reduce costs and improve outcomes. However, TDM also adds to the cost of patient care. The objective of this study was to determine the cost-effectiveness of TDM for generic IM therapy. We developed a microsimulation model for the trough plasma concentration of IM which is related to a cytogenetic or molecular response. We compared two cohorts: one with TDM and one without TDM (NTDM). The lifetime incremental cost-effectiveness ratio (ICER) was calculated using quality-adjusted life years (QALYs) as the effectiveness measure. One-way and probabilistic sensitivity analyses were performed. The lifetime cost and QALY of treatment with TDM were $2,137K [95% Ci: 2,079K; 2,174K] and 12.37 [95% CI: 12.07; 12.55], respectively. The cost and QALY of NTDM were $2,132K [95% CI: 2,091K; 2,197K] and 12.23 [95% CI: 11.96; 12.50], respectively. The incremental cost and QALY for TDM relative to NTDM was $4,417 [95% CI: -52,582; 32,097]) and 0.15 [95% CI: -0.13; 0.28]. The ICER for TDM relative to NTDM was $30,450/QALY. Probabilistic sensitivity analysis showed that TDM was cost-effective relative to NTDM in 90% of the tested scenarios at a willingness-to-pay threshold of $100,000/QALY. Although the impact of TDM is modest, the cost-effectiveness over a lifetime horizon (societal perspective, ($30,450/QALY) falls within the acceptable range (< $100k/QALY).

Lung adenocarcinoma (LAD) has extreme genetic variation among patients, which is currently not well understood, limiting progress in therapy development and research. LAD intrinsic molecular subtypes are a validated stratification of naturally-occurring gene expression patterns and encompass different functional pathways and patient outcomes. Patients may have incurred different mutations and alterations that led to the different subtypes. We hypothesized that the LAD molecular subtypes co-occur with distinct mutations and alterations in patient tumors. The LAD molecular subtypes (Bronchioid, Magnoid, and Squamoid) were tested for association with gene mutations and DNA copy number alterations using statistical methods and published cohorts (n = 504). A novel validation (n = 116) cohort was assayed and interrogated to confirm subtype-alteration associations. Gene mutation rates (EGFR, KRAS, STK11, TP53), chromosomal instability, regional copy number, and genomewide DNA methylation were significantly different among tumors of the molecular subtypes. Secondary analyses compared subtypes by integrated alterations and patient outcomes. Tumors having integrated alterations in the same gene associated with the subtypes, e.g. mutation, deletion and underexpression of STK11 with Magnoid, and mutation, amplification, and overexpression of EGFR with Bronchioid. The subtypes also associated with tumors having concurrent mutant genes, such as KRAS-STK11 with Magnoid. Patient overall survival, cisplatin plus vinorelbine therapy response and predicted gefitinib sensitivity were significantly different among the subtypes. The lung adenocarcinoma intrinsic molecular subtypes co-occur with grossly distinct genomic alterations and with patient therapy response. These results advance the understanding of lung adenocarcinoma etiology and nominate patient subgroups for future evaluation of treatment response.

Quantitative phase imaging (QPI) measures the growth rate of individual cells by quantifying changes in mass versus time. Here, we use the breast cancer cell lines MCF-7, BT-474, and MDA-MB-231 to validate QPI as a multiparametric approach for determining response to single-agent therapies. Our method allows for rapid determination of drug sensitivity, cytotoxicity, heterogeneity, and time of response for up to 100,000 individual cells or small clusters in a single experiment. We find that QPI EC 50 values are concordant with CellTiter-Glo (CTG), a gold standard metabolic endpoint assay. In addition, we apply multiparametric QPI to characterize cytostatic/cytotoxic and rapid/slow responses and track the emergence of resistant subpopulations. Thus, QPI reveals dynamic changes in response heterogeneity in addition to average population responses, a key advantage over endpoint viability or metabolic assays. Overall, multiparametric QPI reveals a rich picture of cell growth by capturing the dynamics of single-cell responses to candidate therapies. The authors developed a real-time and label-free approach based on quantitative phase imaging to determine drug sensitivity with significant advantages over endpoint viability or metabolic assays, and which reveals single cell response heterogeneity.

Background Many methodologies have been used in research to identify the “intrinsic” subtypes of breast cancer commonly known as Luminal A, Luminal B, HER2-Enriched (HER2-E) and Basal-like. The PAM50 gene set is often used for gene expression-based subtyping; however, surrogate subtyping using panels of immunohistochemical (IHC) markers are still widely used clinically. Discrepancies between these methods may lead to different treatment decisions. Methods We used the PAM50 RT-qPCR assay to expression profile 814 tumors from the GEICAM/9906 phase III clinical trial that enrolled women with locally advanced primary invasive breast cancer. All samples were scored at a single site by IHC for estrogen receptor (ER), progesterone receptor (PR), and Her2/neu (HER2) protein expression. Equivocal HER2 cases were confirmed by chromogenic in situ hybridization (CISH). Single gene scores by IHC/CISH were compared with RT-qPCR continuous gene expression values and “intrinsic” subtype assignment by the PAM50. High, medium, and low expression for ESR1 , PGR , ERBB2 , and proliferation were selected using quartile cut-points from the continuous RT-qPCR data across the PAM50 subtype assignments. Results ESR1 , PGR , and ERBB2 gene expression had high agreement with established binary IHC cut-points (area under the curve (AUC) ≥ 0.9). Estrogen receptor positivity by IHC was strongly associated with Luminal (A and B) subtypes (92%), but only 75% of ER negative tumors were classified into the HER2-E and Basal-like subtypes. Luminal A tumors more frequently expressed PR than Luminal B (94% vs 74%) and Luminal A tumors were less likely to have high proliferation (11% vs 77%). Seventy-seven percent (30/39) of ER-/HER2+ tumors by IHC were classified as the HER2-E subtype. Triple negative tumors were mainly comprised of Basal-like (57%) and HER2-E (30%) subtypes. Single gene scoring for ESR1 , PGR , and ERBB2 was more prognostic than the corresponding IHC markers as shown in a multivariate analysis. Conclusions The standard immunohistochemical panel for breast cancer (ER, PR, and HER2) does not adequately identify the PAM50 gene expression subtypes. Although there is high agreement between biomarker scoring by protein immunohistochemistry and gene expression, the gene expression determinations for ESR1 and ERBB2 status was more prognostic.

Gene expression profiling of breast cancer delineates a particularly aggressive subtype referred to as ‘basal-like’, which comprises ∼15% of all breast cancers, afflicts younger women and is refractory to endocrine and anti-HER2 therapies. Immunohistochemical surrogate definitions for basal-like breast cancer, such as the clinical ER/PR/HER2 triple-negative phenotype and models incorporating positive expression for CK5 (CK5/6) and/or EGFR are heavily cited. However, many additional biomarkers for basal-like breast cancer have been described in the literature. A parallel comparison of 46 proposed immunohistochemical biomarkers of basal-like breast cancer was performed against a gene expression profile gold standard on a tissue microarray containing 42 basal-like and 80 non-basal-like breast cancer cases. Ki67 and PPH3 were the most sensitive biomarkers (both 92%) positively expressed in the basal-like subtype, whereas CK14, IMP3 and NGFR were the most specific (100%). Among biomarkers surveyed, loss of INPP4B (a negative regulator of phosphatidylinositol signaling) was 61% sensitive and 99% specific with the highest odds ratio (OR) at 108, indicating the strongest association with basal-like breast cancer. Expression of nestin, a common marker of neural progenitor cells that is also associated with the triple-negative/basal-like phenotype and poor breast cancer prognosis, possessed the second highest OR at 29 among the 46 biomarkers surveyed, as well as 54% sensitivity and 96% specificity. As a positively expressed biomarker, nestin possesses technical advantages over INPP4B that make it a more ideal biomarker for identification of basal-like breast cancer. The comprehensive immunohistochemical biomarker survey presented in this study is a necessary step for determining an optimized surrogate immunopanel that best defines basal-like breast cancer in a practical and clinically accessible way.

Ewing's sarcoma is a common malignancy of bone and soft tissue that occurs most often in children and young adults. Differentiating Ewing's sarcoma from other round blue cell tumors can be a diagnostic challenge because of their similarity in histology and clinical presentation. Thus, ancillary molecular tests for detecting disease-defining translocations are important for confirming the diagnosis. We analyzed 65 round blue cell tumors, including 53 Ewing's sarcoma samples from 50 unique cases. Samples were processed for RNA from archived formalin-fixed paraffin-embedded tissue blocks. Real-time RT-PCR assays specific for Ewing's sarcoma (EWS-FLI1, EWS-ERG, EWS-ETV1, EWS-ETV4, and EWS-FEV), synovial sarcoma (SYT-SSX1 and SYT-SSX2), and rhabdomyosarcoma (PAX3-FKHR and PAX7-FKHR) were tested across the samples. The translocation panel had a sensitivity of 81% (43 out of 53 samples) for diagnosing Ewing's sarcoma when using the histological criteria as the ‘gold' standard. None of the Ewing's specific translocations were found in the non-Ewing's samples (100% specificity). Of the 43 samples with translocations detected, 26 (60%) had an EWS-FLI1 type 1 translocation, 13 (30%) had an EWS-FLI1 type 2 translocation, 3 (7%) had an EWS-ERG translocation, 1 had an EWS-ETV1 translocation, and 1 sample had both an EWS-FLI1 type 1 and type 2 translocation. Our real-time RT-PCR assay for detecting sarcoma translocations has high sensitivity and specificity for Ewing's sarcoma and has clinical utility in differentiating small round blue cell tumors in the clinical lab.

By implementing the conditions for orthotopic implantation of different types of human breast tumors, the authors have created a publicly available bank of new mouse models that more faithfully recreate individual tumor properties and provide individualized information about tumor behavior and prognosis. Development and preclinical testing of new cancer therapies is limited by the scarcity of in vivo models that authentically reproduce tumor growth and metastatic progression. We report new models for breast tumor growth and metastasis in the form of transplantable tumors derived directly from individuals undergoing treatment for breast cancer. These tumor grafts illustrate the diversity of human breast cancer and maintain essential features of the original tumors, including metastasis to specific sites. Co-engraftment of primary human mesenchymal stem cells maintains phenotypic stability of the grafts and increases tumor growth by promoting angiogenesis. We also report that tumor engraftment is a prognostic indicator of disease outcome for women with newly diagnosed breast cancer; orthotopic breast tumor grafting is a step toward individualized models for tumor growth, metastasis and prognosis. This bank of tumor grafts also serves as a publicly available resource for new models in which to study the biology of breast cancer.