Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer.

The Nottingham prognostic index plus (NPI+) is based on the assessment of biological class combined with established clinicopathologic prognostic variables providing improved patient outcome stratification for breast cancer superior to the traditional NPI. This study aimed to determine prognostic capability of the NPI+ in predicting risk of development of distant disease. A well-characterised series of 1073 primary early-stage BC cases treated in Nottingham and 251 cases from Budapest were immunohistochemically assessed for cytokeratin (Ck)5/6, Ck18, EGFR, oestrogen receptor (ER), progesterone receptor, HER2, HER3, HER4, Mucin 1 and p53 expression. NPI+ biological class and prognostic scores were assigned using individual algorithms for each biological class incorporating clinicopathologic parameters and investigated in terms of prediction of distant metastases-free survival (MFS). The NPI+ identified distinct prognostic groups (PG) within each molecular class which were predictive of MFS providing improved patient outcome stratification superior to the traditional NPI. NPI+ PGs, between series, were comparable in predicting patient outcome between series in luminal A, basal p53 altered and HER2+/ER+ (p > 0.01) tumours. The low-risk groups were similarly validated in luminal B, luminal N, basal p53 normal tumours (p > 0.01). Due to small patient numbers the remaining PGs could not be validated. NPI+ was additionally able to predict a higher risk of metastases at certain distant sites. This study may indicate the NPI+ as a useful tool in predicting the risk of metastases. The NPI+ provides accurate risk stratification allowing improved individualised clinical decision making for breast cancer.

HAGE (DDX43) is a biomarker for poor prognosis and a predictor of chemotherapy response in breast cancer.

BACKGROUND: HAGE protein is a known immunogenic cancer-specific antigen. METHODS: The biological, prognostic and predictive values of HAGE expression was studied using immunohistochemistry in three cohorts of patients with BC (n=2147): early primary (EP-BC; n=1676); primary oestrogen receptor-negative (PER-BC; n=275) treated with adjuvant anthracycline-combination therapies (Adjuvant-ACT); and primary locally advanced disease (PLA-BC) who received neo-adjuvant anthracycline-combination therapies (Neo-adjuvant-ACT; n=196). The relationship between HAGE expression and the tumour-infiltrating lymphocytes (TILs) in matched prechemotherapy and postchemotherapy samples were investigated. RESULTS: Eight percent of patients with EP-BC exhibited high HAGE expression (HAGE+) and was associated with aggressive clinico-pathological features (Ps<0.01). Furthermore, HAGE+expression was associated with poor prognosis in both univariate and multivariate analysis (Ps<0.001). Patients with HAGE+did not benefit from hormonal therapy in high-risk ER-positive disease. HAGE+and TILs were found to be independent predictors for pathological complete response to neoadjuvant-ACT; P<0.001. A statistically significant loss of HAGE expression following neoadjuvant-ACT was found (P=0.000001), and progression-free survival was worse in those patients who had HAGE+residual disease (P=0.0003). CONCLUSIONS: This is the first report to show HAGE to be a potential prognostic marker and a predictor of response to ACT in patients with BC.

Identification of key clinical phenotypes of breast cancer using a reduced panel of protein biomarkers.

BACKGROUND: Breast cancer is a heterogeneous disease characterised by complex molecular alterations underlying the varied behaviour and response to therapy. However, translation of cancer genetic profiling for use in routine clinical practice remains elusive or prohibitively expensive. As an alternative, immunohistochemical analysis applied to routinely processed tissue samples could be used to identify distinct biological classes of breast cancer. METHODS: In this study, 1073 archival breast tumours previously assessed for 25 key breast cancer biomarkers using immunohistochemistry and classified using clustering algorithms were further refined using naïve Bayes classification performance. Criteria for class membership were defined using the expression of a reduced panel of 10 proteins able to identify key molecular classes. We examined the association between these breast cancer classes with clinicopathological factors and patient outcome. RESULTS: We confirm patient classification similar to established genotypic biological classes of breast cancer in addition to novel sub-divisions of luminal and basal tumours. Correlations between classes and clinicopathological parameters were in line with expectations and showed highly significant association with patient outcome. Furthermore, our novel biological class stratification provides additional prognostic information to the Nottingham Prognostic Index. CONCLUSION: This study confirms that distinct molecular phenotypes of breast cancer can be identified using robust and routinely available techniques and both the luminal and basal breast cancer phenotypes are heterogeneous and contain distinct subgroups.

Lack of expression of the proteins GMPR2 and PPARα are associated with the basal phenotype and patient outcome in breast cancer.

UNLABELLED: Basal-like tumours (BP) are a poor prognostic class of breast cancer but remain a biologically and clinically heterogeneous group. We have previously identified two novel genes PPARα (positive) and GMPR2 (negative) whose expression was significantly associated with BP at the transcriptome level. In this study, using a large and well-characterised series of operable invasive breast carcinomas (1,043 cases) prepared as TMAs, we assessed these targets at the protein level using immunohistochemistry and investigated associations with clinicopathological variables and patient outcome. RESULTS: Lack of PPARα and GMPR2 protein expression was associated with BP, as defined by the expression of cytokeratin (CK) 5/6 and/or CK14, (p = 0.023, p = 0.001, respectively) or as triple-negative (ER-, PR-, HER2-) phenotype (p < 0.001 for both proteins). Positive expression of both markers was associated ER and PR positive status (p < 0.05) and with the good Nottingham Prognostic Index group (p = 0.012, p < 0.001, respectively). Univariate survival analysis showed an association between lack of expression of PPARα and GMPR2 and poor outcome in terms of shorter disease-free survival and shorter breast cancer-specific survival, respectively. However, multivariate analysis showed that these associations were not independent of other prognostic variables, namely tumour size, grade, and nodal stage. In conclusion, this study demonstrates that loss of expression of GMPR2 and PPARα is associated with BP at the protein level; indicating that they may play a role in carcinogenesis of this molecularly complex and clinically important subtype. Further studies into their relevance in further classification of BP are warranted.

The proteins FABP7 and OATP2 are associated with the basal phenotype and patient outcome in human breast cancer.

The basal-like or basal phenotype (BP) class of breast cancers have recently attracted attention as a poor prognostic form of breast cancer. However, BP appears to encompass biologically and clinically heterogeneous tumours, resulting in a lack of consensus definition of BP. We analysed 48,000 gene transcripts in 132 invasive breast carcinomas to identify two novel genes (OATP2 and FABP7) significantly associated with BP [defined by cytokeratin (CK)5/6 and/or CK14 positivity]. Using a series of invasive breast carcinoma cases (n = 899), prepared as tissue microarrays, we assessed OATP2 and FABP7 protein expression using immunohistochemistry to investigate associations with clinicopathological variables, patients' outcome and ability to refine BP classification. A total of 7.9 and 15.6% cases were OATP2 and FABP7 positive, respectively. OATP2 was associated with tumours of high histological grade (p < 0.01), ER and PgR negativity (p < 0.01) and shorter breast cancer-specific survival (p = 0.04). FABP7 expression was associated with lower lymph node stage (p < 0.01), ER and PgR negativity (p < 0.01). BP tumours which were FABP7 positive had a significantly longer BCSS (p = 0.05) and disease-free survival (p = 0.01) compared with FABP7 negative basal tumours (p < 0.01). OATP2 positive tumours were associated with adverse survival and increased risk of early recurrence. This study confirms the biological and clinical heterogeneity of the BP in breast cancer. We have identified a novel subgroup of basal tumours showing FABP7 expression that have significantly better clinical outcome. Further studies analysing the role of FABP7 are therefore warranted.

A validated gene expression profile for detecting clinical outcome in breast cancer using artificial neural networks.

Gene expression microarrays allow for the high throughput analysis of huge numbers of gene transcripts and this technology has been widely applied to the molecular and biological classification of cancer patients and in predicting clinical outcome. A potential handicap of such data intensive molecular technologies is the translation to clinical application in routine practice. In using an artificial neural network bioinformatic approach, we have reduced a 70 gene signature to just 9 genes capable of accurately predicting distant metastases in the original dataset. Upon validation in a follow-up cohort, this signature was an independent predictor of metastases free and overall survival in the presence of the 70 gene signature and other factors. Interestingly, the ANN signature and CA9 expression also split the groups defined by the 70 gene signature into prognostically distinct groups. Subsequently, the presence of protein for the principal prognosticator gene was categorically assessed in breast cancer tissue of an experimental and independent validation patient cohort, using immunohistochemistry. Importantly our principal prognosticator, CA9, showed that it is capable of selecting an aggressive subgroup of patients who are known to have poor prognosis.

High-throughput ultra-high-performance liquid chromatography/tandem mass spectrometry quantitation of insulin-like growth factor-I and leucine-rich alpha-2-glycoprotein in serum as biomarkers of recombinant human growth hormone administration.

Insulin-like growth factor-I (IGF-I) is a known biomarker of recombinant human growth hormone (rhGH) abuse, and is also used clinically to confirm acromegaly. The protein leucine-rich alpha-2-glycoprotein (LRG) was recently identified as a putative biomarker of rhGH administration. The combination of an ACN depletion method and a 5-min ultra-high-performance liquid chromatography/tandem mass spectrometry (uHPLC/MS/MS)-based selected reaction monitoring (SRM) assay detected both IGF-I and LRG at endogenous concentrations. Four eight-point standard addition curves of IGF-I (16-2000 ng/mL) demonstrated good linearity (r(2) = 0.9991 and coefficients of variance (CVs) <13%). Serum samples from two rhGH administrations were extracted and their uHPLC/MS/MS-derived IGF-I concentrations correlated well against immunochemistry-derived values. Combining IGF-I and LRG data improved the separation of treated and placebo states compared with IGF-I alone, further strengthening the hypothesis that LRG is a biomarker of rhGH administration. Artificial neural networks (ANNs) analysis of the LRG and IGF-I data demonstrated an improved model over that developed using IGF-I alone, with a predictive accuracy of 97%, specificity of 96% and sensitivity of 100%. Receiver operator characteristic (ROC) analysis gave an AUC value of 0.98. This study demonstrates the first large scale and high throughput uHPLC/MS/MS-based quantitation of a medium abundance protein (IGF-I) in human serum. Furthermore, the data we have presented for the quantitative analysis of IGF-I suggest that, in this case, monitoring a single SRM transition to a trypsin peptide surrogate is a valid approach to protein quantitation by LC/MS/MS.

Reading the prognosis of the individual with breast cancer.

AIM: To obtain better survival estimates for the individual than is provided by placement in an NPI group. METHOD: Consecutive primary operable breast cancers treated at Nottingham City Hospital 1990-1999. Ten year % actuarial survivals plotted for 10 ranges of NPI from 2.0 to 6.9. There is an excellent inverse correlation between median NPI value for each range and survival at 10 years. To enable estimation of survival for all individual values of NPI, a curve fitting technique applied to these results (by G.B.) gave the formula to estimate survival from the individual's NPI score: 10 year % survival for the individual=-3.0079 x NPI(2)+12.30 x NPI+83.84. This gave an r(2) of 0.98. RESULTS AND CONCLUSION: Greater accuracy in individual survival prediction is obtained by dividing women into 10 groups by NPI scores than in the originally described six groups; rank order of survival in relation to NPI score is preserved. A curve fitting technique has been applied to these data to give a formula for the prediction of 10 year survival for every 0.1 value of NPI.

Survival of invasive breast cancer according to the Nottingham Prognostic Index in cases diagnosed in 1990-1999.

UNLABELLED: The Nottingham Prognostic Index (NPI) is a well established and widely used method of predicting survival of operable primary breast cancer. AIMS: Primary: To present the updated survival figures for each NPI Group. Secondary: From the observations to suggest reasons for the reported fall in mortality from breast cancer. METHODS: The NPI is compiled from grade, size and lymph node status of the primary tumour. Consecutive cases diagnosed and treated at Nottingham City Hospital in 1980-1986 (n=892) and 1990-1999 (n=2,238) are compared. Changes in protocols towards earlier diagnosis and better case management were made in the late 1980s between the two data sets. RESULTS: Case survival (Breast Cancer Specific) at 10 years has improved overall from 55% to 77%. Within all Prognostic groups there are high relative and absolute risk reductions. The distribution of cases to Prognostic groups shows only a small increase in the numbers in better groups. CONCLUSION: The updated survival figures overall and for each Prognostic group for the NPI are presented.

Scanning laser Doppler vibrometry of the middle ear ossicles.

This paper describes measurements of the vibratory modes of the middle ear ossicles made with a scanning laser Doppler vibrometer. Previous studies of the middle ear ossicles with single-point laser Doppler measurements have raised questions regarding the vibrational modes of the ossicular chain. Single-point analysis methods do not have the ability to measure multiple points on the ossicles and, consequently, have limited ability to simultaneously record relative phase information at these points. Using a Polytec Model PSV-100, detailed measurements of the ossicular chain have been completed in the human temporal bone model. This model, when driven with a middle ear transducer, provides detailed three-dimensional data of the vibrational patterns of the middle ear ossicles. Implications for middle ear implantable devices are discussed.

Implantable hearing device performance measured by laser Doppler interferometry.

Recent application of the Doppler principle laser interferometry to audiology, acoustics and otology has facilitated the development of implantable hearing devices (IHDs). During the design and testing of two different electromagnetic middle ear implants for sensorineural hearing loss, we used single-point laser Doppler interferometry (LDI). A commercially available interferometer, internally calibrated and validated against a National Institute for Standards and Technology (NIST) standard, was used with both mechanical fixtures and fresh temporal bones to evaluate implant mass, shape and orientation, attachment, electromagnetic coupling and acoustic properties. At both Hough Ear Institute and Symphonix Devices, Inc., we have shown that high fidelity and amplitudes can be recorded in vitro over a frequency range of 500 Hz to 10 kHz. These data can provide greater assurance of safety and efficacy to regulatory agencies before entering clinical trials. We propose that LDI be considered as an international standard for accurate, consistent comparison of performances of all IHDs during development. Furthermore, the future availability of human IHD data will allow for the extrapolation of a mechanical bench model of the middle ear transfer function for use in quality control during manufacturing and diagnosis of failure in IHDs.