Relation between the rate of tumour cell proliferation and latency time in radiation associated breast cancer.

Background: Patients with possible radiation induced cancer could be used to study if the rate of tumour cell proliferation is related to latency time. Such a finding could help researcher to find time periods when other initiating risk factors operate. Methods: Seventeen women with breast cancer, with a prior history of radiation treatment towards the parts or the whole breast, exclusive of the primary treatment of a breast cancer were identified. Most women had received treatment for benign disorders as hemangiomas, shoulder pain or skin infections. Three patients had been treated with mantle radiation for Hodgkin's disease prior to developing breast cancer. DNA analysis were performed, on remaining tumour tissue after hormone receptor analysis had been done, measuring the fraction of tumour cells in S-phase. Latency time (time between diagnosis and previous radiation treatment) was calculated and related to the S-phase fraction. Results: A significant inverse relationship between latency time and S-phase was found (p < 0.0025), indicating that tumours with a high S-phase had a short latency time and vice versa. Among the possible radiation induced tumours, median S-phase was 14%, comparable with a median latency time of 22 years. Very high S-phase values were associated with short latency times (eg a S-phase of 35% would be compatible with a latency time of 7 years). Conclusion: Our preliminary results indicate that S-phase is related to latency time and that the median latency time maybe as long as 22 years. Our data may also explain why breast cancer is rare before 30 years of age and if patients are diagnosed at early ages, tumours often show high S-phase values and bad prognostic signs. We postulate that these results from radiation induced breast cancer may be used to extrapolate possible latency times in patients with non radiation induced breast tumours in order to isolate possible time periods for research after other initiating events

RNA quality in frozen breast cancer samples and the influence on gene expression analysis – a comparison of three evaluation methods using microcapillary electrophoresis traces

<p>Abstract</p> <p>Background</p> <p>Assessing RNA quality is essential for gene expression analysis, as the inclusion of degraded samples may influence the interpretation of expression levels in relation to biological and/or clinical parameters. RNA quality can be analyzed by agarose gel electrophoresis, UV spectrophotometer, or microcapillary electrophoresis traces, and can furthermore be evaluated using different methods. No generally accepted recommendations exist for which technique or evaluation method is the best choice. The aim of the present study was to use microcapillary electrophoresis traces from the Bioanalyzer to compare three methods for evaluating RNA quality in 24 fresh frozen invasive breast cancer tissues: 1) Manual method = subjective evaluation of the electropherogram, 2) Ratio Method = the ratio between the 28S and 18S peaks, and 3) RNA integrity number (RIN) method = objective evaluation of the electropherogram. The results were also related to gene expression profiling analyses using 27K oligonucleotide microarrays, unsupervised hierarchical clustering analysis and ontological mapping.</p> <p>Results</p> <p>Comparing the methods pair-wise, Manual <it>vs</it>. Ratio showed concordance (good <it>vs</it>. degraded RNA) in 20/24, Manual <it>vs</it>. RIN in 23/24, and Ratio <it>vs</it>. RIN in 21/24 samples. All three methods were concordant in 20/24 samples. The comparison between RNA quality and gene expression analysis showed that pieces from the same tumor and with good RNA quality clustered together in most cases, whereas those with poor quality often clustered apart. The number of samples clustering in an unexpected manner was lower for the Manual (n = 1) and RIN methods (n = 2) as compared to the Ratio method (n = 5).</p> <p>Assigning the data into two groups, RIN ≥ 6 or RIN < 6, all but one of the top ten differentially expressed genes showed decreased expression in the latter group; <it>i.e</it>. when the RNA became degraded. Ontological mapping using GoMiner (p ≤ 0.05; ≥ 3 genes changed) revealed deoxyribonuclease activity, collagen, regulation of cell adhesion, cytosolic ribosome, and NADH dehydrogenase activity, to be the five categories most affected by RNA quality.</p> <p>Conclusion</p> <p>The results indicate that the Manual and RIN methods are superior to the Ratio method for evaluating RNA quality in fresh frozen breast cancer tissues. The objective measurement when using the RIN method is an advantage. Furthermore, the inclusion of samples with degraded RNA may profoundly affect gene expression levels.</p

Prognosis, stage and oestrogen receptor status of contralateral breast cancer in relation to characteristics of the first tumour, prior endocrine treatment and radiotherapy.

A contralateral breast cancer (CBC) is today treated as an independent primary tumour, although recent data suggest risk and prognosis of CBC to be influenced by characteristics of and treatment given for the first tumour (BC1). We hereby investigate phenotypical and prognostic features of the second tumour (BC2) in relation to prior endocrine treatment and radiotherapy

Training artificial neural networks directly on the concordance index for censored data using genetic algorithms.

OBJECTIVE: The concordance index (c-index) is the standard way of evaluating the performance of prognostic models in the presence of censored data. Constructing prognostic models using artificial neural networks (ANNs) is commonly done by training on error functions which are modified versions of the c-index. Our objective was to demonstrate the capability of training directly on the c-index and to evaluate our approach compared to the Cox proportional hazards model. METHOD: We constructed a prognostic model using an ensemble of ANNs which were trained using a genetic algorithm. The individual networks were trained on a non-linear artificial data set divided into a training and test set both of size 2000, where 50% of the data was censored. The ANNs were also trained on a data set consisting of 4042 patients treated for breast cancer spread over five different medical studies, 2/3 used for training and 1/3 used as a test set. A Cox model was also constructed on the same data in both cases. The two models' c-indices on the test sets were then compared. The ranking performance of the models is additionally presented visually using modified scatter plots. RESULTS: Cross validation on the cancer training set did not indicate any non-linear effects between the covariates. An ensemble of 30 ANNs with one hidden neuron was therefore used. The ANN model had almost the same c-index score as the Cox model (c-index=0.70 and 0.71, respectively) on the cancer test set. Both models identified similarly sized low risk groups with at most 10% false positives, 49 for the ANN model and 60 for the Cox model, but repeated bootstrap runs indicate that the difference was not significant. A significant difference could however be seen when applied on the non-linear synthetic data set. In that case the ANN ensemble managed to achieve a c-index score of 0.90 whereas the Cox model failed to distinguish itself from the random case (c-index=0.49). CONCLUSIONS: We have found empirical evidence that ensembles of ANN models can be optimized directly on the c-index. Comparison with a Cox model indicates that near identical performance is achieved on a real cancer data set while on a non-linear data set the ANN model is clearly superior

Traveling dark-bright solitons in a reduced spin-orbit coupled system: application to Bose-Einstein condensates

In the present work, we explore the potential of spin-orbit (SO) coupled Bose-Einstein condensates to support multi-component solitonic states in the form of dark-bright (DB) solitons. In the case where Raman linear coupling between components is absent, we use a multiscale expansion method to reduce the model to the integrable Mel'nikov system. The soliton solutions of the latter allow us to reconstruct approximate traveling DB solitons for the reduced SO coupled system. For small values of the formal perturbation parameter, the resulting waveforms propagate undistorted, while for large values thereof, they shed some dispersive radiation, and subsequently distill into a robust propagating structure. After quantifying the relevant radiation effect, we also study the dynamics of DB solitons in a parabolic trap, exploring how their oscillation frequency varies as a function of the bright component mass and the Raman laser wavenumber

Claudin-2 is an independent negative prognostic factor in breast cancer and specifically predicts early liver recurrences.

Predicting any future metastatic site of early-stage breast cancer is important as it significantly influences the prognosis of advanced disease. This study aimed at investigating the potential of claudin-2, over-expressed in breast cancer liver metastases, as a biomarker for predicting liver metastatic propensity in primary breast cancer

Prognostic and predictive impact of stroma cells defned by PDGFRb expression in early breast cancer: results from the randomized SweBCG91RT trial

Purpose Predictive biomarkers are needed to aid the individualization of radiotherapy (RT) in breast cancer. Cancer-associated fibroblasts have been implicated in tumor radioresistance and can be identified by platelet-derived growth factor receptor-beta (PDGFRb). This study aims to analyze how PDGFRb expression affects RT benefit in a large randomized RT trial. Methods PDGFRb was assessed by immunohistochemistry on tissue microarrays from 989 tumors of the SweBCG91RT trial, which enrolled lymph node-negative, stage I/IIA breast cancer patients randomized to RT after breast-conserving surgery. Outcomes were analyzed at 10 years for ipsilateral breast tumor recurrence (IBTR) and any recurrence and 15 years for breast cancer specific death (BCSD). Results PDGFRb expression correlated with estrogen receptor negativity and younger age. An increased risk for any recurrence was noted in univariable analysis for the medium (HR 1.58, CI 95% 1.11–2.23, p = 0.011) or PDGFRb high group (1.49, 1.06–2.10, p = 0.021) compared to the low group. No differences in IBTR or BCSD risk were detected. RT benefit regarding IBTR risk was significant in the PDGFRb low (0.29, 0.12–0.67, p = 0.004) and medium (0.31, 0.16–0.59, p < 0.001) groups but not the PDGFRb high group (0.64, 0.36–1.11, p = 0.110) in multivariable analysis. Likewise, risk reduction for any recurrence was less pronounced in the PDGFRb high group. No significant interaction between RT and PDGFRb-score could be detected. Conclusion A higher PDGFRb-score conferred an increased risk of any recurrence, which partly can be explained by its association with estrogen receptor negativity and young age. Reduced RT benefit was noted among patients with high PDGFRb, however without significant interaction.publishedVersio

Histological grade provides significant prognostic information in addition to breast cancer subtypes defined according to St Gallen 2013

Background: The St Gallen surrogate definition of the intrinsic subtypes of breast cancer consist of five subgroups based on estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor type 2 (HER2), and Ki-67. PgR and Ki-67 are used for discriminating between the ‘Luminal A-like’ and ‘Luminal B-like (HER2-negative)’ subtypes. Histological grade (G) has prognostic value in breast cancer; however, its relationship to the St Gallen subtypes is not clear. Based on a previous pilot study, we hypothesized that G could be a primary discriminator for ER-positive/HER2-negative breast cancers that were G1 or G3, whereas Ki-67 and PgR could provide additional prognostic information specifically for patients with G2 tumors. To test this hypothesis, a larger patient cohort was examined. Patients and methods: Six hundred seventy-one patients (≥35 years of age, pT1-2, pN0-1) with ER-positive/HER2-negative breast cancer and complete data for PgR, Ki-67, G, lymph node status, tumor size, age, and distant disease-free survival (DDFS; median follow-up 9.2 years) were included. Results: ‘Luminal A-like’ tumors were mostly G1 or G2 (90%) whereas ‘Luminal B-like’ tumors were mostly G2 or G3 (87%) and corresponded with good and poor DDFS, respectively. In ‘Luminal B-like’ tumors that were G1 (n = 23), no metastasis occurred, whereas 14 of 40 ‘Luminal A-like’ tumors that were G3 metastasized. In the G2 subgroup, low PgR and high Ki-67 were associated with an increased risk of distant metastases, hazard ratio (HR) and 95% confidence interval (CI) 1.8 (0.95–3.4) and 1.5 (0.80–2.8), respectively. Conclusions: Patients with ER-positive/HER2-negative/G1 breast cancer have a good prognosis, similar to that of ‘Luminal A-like’, while those with ER-positive/HER2-negative/G3 breast cancer have a worse prognosis, similar to that of ‘Luminal B-like’, when assessed independently of PgR and Ki-67. Therapy decisions based on Ki-67 and PgR might thus be restricted to the subgroup G2

A Molecular Taxonomy for Urothelial Carcinoma.

PURPOSE: Even though urothelial cancer is the fourth most common tumor type among males, progress in treatment has been scarce. A problem in day-to-day clinical practice is that precise assessment of individual tumors is still fairly uncertain; consequently efforts have been undertaken to complement tumor evaluation with molecular biomarkers. An extension of this approach would be to base tumor classification primarily on molecular features. Here, we present a molecular taxonomy for urothelial carcinoma based on integrated genomics. EXPERIMENTAL DESIGN: We use gene expression profiles from 308 tumor cases to define five major urothelial carcinoma subtypes: urobasal A, genomically unstable, urobasal B, squamous cell carcinoma like, and an infiltrated class of tumors. Tumor subtypes were validated in three independent publically available data sets. The expression of 11 key genes was validated at the protein level by immunohistochemistry. RESULTS: The subtypes show distinct clinical outcomes and differ with respect to expression of cell-cycle genes, receptor tyrosine kinases particularly FGFR3, ERBB2, and EGFR, cytokeratins, and cell adhesion genes, as well as with respect to FGFR3, PIK3CA, and TP53 mutation frequency. The molecular subtypes cut across pathologic classification, and class-defining gene signatures show coordinated expression irrespective of pathologic stage and grade, suggesting the molecular phenotypes as intrinsic properties of the tumors. Available data indicate that susceptibility to specific drugs is more likely to be associated with the molecular stratification than with pathologic classification. CONCLUSIONS: We anticipate that the molecular taxonomy will be useful in future clinical investigations. Clin Cancer Res; 1-10. ©2012 AACR

Galectin-1-Binding Glycoforms of Haptoglobin with Altered Intracellular Trafficking, and Increase in Metastatic Breast Cancer Patients

Sera from 25 metastatic breast cancer patients and 25 healthy controls were subjected to affinity chromatography using immobilized galectin-1. Serum from the healthy subjects contained on average 1.2 mg per ml (range 0.7–2.2) galectin-1 binding glycoproteins, whereas serum from the breast cancer patients contained on average 2.2 mg/ml (range 0.8–3.9), with a higher average for large primary tumours. The major bound glycoproteins were α-2-macroglobulin, IgM and haptoglobin. Both the IgM and haptoglobin concentrations were similar in cancer compared to control sera, but the percentage bound to galectin-1 was lower for IgM and higher for haptoglobin: about 50% (range 20–80) in cancer sera and about 30% (range 25–50) in healthy sera. Galectin-1 binding and non-binding fractions were separated by affinity chromatography from pooled haptoglobin from healthy sera. The N-glycans of each fraction were analyzed by mass spectrometry, and the structural differences and galectin-1 mutants were used to identify possible galectin-1 binding sites. Galectin-1 binding and non-binding fractions were also analyzed regarding their haptoglobin function. Both were similar in forming complex with haemoglobin and mediate its uptake into alternatively activated macrophages. However, after uptake there was a dramatic difference in intracellular targeting, with the galectin-1 non-binding fraction going to a LAMP-2 positive compartment (lysosomes), while the galectin-1 binding fraction went to larger galectin-1 positive granules. In conclusion, galectin-1 detects a new type of functional biomarker for cancer: a specific type of glycoform of haptoglobin, and possibly other serum glycoproteins, with a different function after uptake into tissue cells