A Molecular Signature of the Nottingham Prognostic Index in Breast Cancer

The effect of chemotherapy on survival in oldest old patients with nonmetastatic triple negative breast cancer: A populationbased observational study

WHAT IS KNOWN AND OBJECTIVE

Chemotherapy is the primary pharmacotherapy of triple-negative breast cancer (TNBC). But the benefit of adjuvant chemotherapy in the oldest old TNBC patients remains controversial. Hence, we designed this population based observational study in order to assess the survival benefit of adjuvant chemotherapy in oldest old TNBC patients with early-stage disease.

METHODS

TNBC patients aged 80 years and older that with stage I to III invasive disease were identified in the surveillance, epidemiology, and end results cancer database from 2010 to 2016.

RESULTS AND DISCUSSION

Of 1611 patients enrolled, 1356 (84.17%) did not receive chemotherapy. Age, race, histology, grade, T stage, N stage, and radiation were found to be strong predictors of chemotherapy recipient by multivariate logistic regression analysis. Chemotherapy significantly prolonged overall survival (OS) (HR, 0.62, 95% CI: 0.49-0.79, p < 0.001), but did not significantly reduce breast cancer specific death (BCSD) (HR, 0.92, 95% CI: 0.63-1.35, p = 0.675). These results were further confirmed by propensity score matching analysis. Chemotherapy was associated with better OS in the subgroup of patients aged 80-84 years old (HR, 0.54, 95% CI: 0.40-0.74, p < 0.001), T2-4 stage disease (HR, 0.58, 95% CI: 0.44-0.76, p < 0.001), or grade 3-4 disease (HR, 0.54, 95% CI: 0.41-0.71, p < 0.001). However, chemotherapy did not reduce the cumulative incidence of BCSD in any subgroup.

WHAT IS NEW AND CONCLUSION

Chemotherapy should be considered for TNBC patients aged 80-84 years old, T2-4 disease, or grade 3-4 disease.

Nomogram for predicting overall survival in patients with triple-negative apocrine breast cancer: Surveillance, epidemiology, and end results-based analysis

PURPOSE

Triple-negative apocrine carcinoma (TNAC) is a sort of triple-negative breast cancer (TNBC) that is rare and prognosis of these patients is unclear. The present study constructed an effective nomogram to assist in predicting TNAC patients overall survival (OS).

METHODS

A total of 373 TNAC patients from the surveillance, epidemiology, and end results (SEER) got extracted from 2010 to 2016 and were divided into training (n = 261) and external validation (n = 112) groups (split ratio, 7:3) randomly. A Cox regression model was utilized to creating a nomogram according to the risk factors affecting prognosis. The predictive capability of the nomogram was estimated with receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).

RESULTS

Multivariate Cox regression analysis revealed age, surgery, chemotherapy, stage, and first malignant primary as independent predictors of OS. A prediction model was constructed and virtualized using the nomogram. The time-dependent area under the curve (AUC) showed satisfactory discrimination of the nomogram. Good consistency was shown on the calibration curves in OS between actual observations and the nomogram prediction. What's more, DCA showed that the nomogram had incredible clinical utility. Through separating the patients into groups of low and high risk group that connects with the risk system that shows a huge difference between the low-risk and high risk OS (P < 0.001).

CONCLUSION

To predict the OS in TNAC patients, the nomogram utilizing the risk stratification system that is corresponding. These tools may help to evaluate patient prognosis and guide treatment decisions.

Multiplex immunohistochemistry and high-throughput image analysis for evaluation of spatial tumor immune cell markers in human breast cancer

BACKGROUND

The clinicopathological significance of spatial tumor-infiltrating lymphocytes (TILs) subpopulations is not well studied due to lack of high-throughput scalable methodology for studies with large human sample sizes.

OBJECTIVE

Establishing a cyclic fluorescent multiplex immunohistochemistry (mIHC/IF) method coupled with computer-assisted high-throughput quantitative analysis to evaluate associations of six TIL markers (CD3, CD8, CD20, CD56, FOXP3, and PD-L1) with clinicopathological factors of breast cancer.

METHODS

Our 5-plex mIHC/IF staining was shown to be reliable and highly sensitive for labeling three biomarkers per tissue section. Through repetitive cycles of 5-plex mIHC/IF staining, more than 12 biomarkers could be detected per single tissue section. Using open-source software CellProfiler, the measurement pipelines were successfully developed for high-throughput multiplex evaluation of intratumoral and stromal TILs.

RESULTS

In analyses of 188 breast cancer samples from the Nashville Breast Health Study, high-grade tumors showed significantly increased intratumoral CD3+CD8+ CTL density (P= 0.0008, false discovery rate (FDR) adjusted P= 0.0168) and intratumoral PD-L1 expression (P= 0.0061, FDR adjusted P= 0.0602) compared with low-grade tumors.

CONCLUSIONS

The high- and low-grade breast cancers exhibit differential immune responses which may have clinical significances. The multiplexed imaging quantification strategies established in this study are reliable, cost-efficient and applicable in regular laboratory settings for high-throughput tissue biomarker studies, especially retrospective and population-based studies using archived paraffin tissues.

Chemokines in Triple-Negative Breast Cancer Heterogeneity: New Challenges for Clinical Implications

Tumor heterogeneity is a hallmark of cancer and one of the primary causes of resistance to therapies. Triple-negative breast cancer (TNBC), which accounts for 15% to 20% of all breast cancers and is the most aggressive subtype, is very diverse, connected to metastatic potential and response to therapy. It is a very diverse disease at the molecular, pathologic, and clinical levels. TNBC is substantially more likely to recur and has a worse overall survival rate following diagnosis than other breast cancer subtypes. Chemokines, low molecular weight proteins that stimulate chemotaxis, have been shown to control the cues responsible for TNBC heterogeneity. In this review, we have focused on tumor heterogeneity and the role of chemokines in modulating tumor heterogeneity, since this is the most critical issue in treating TNBC. Additionally, we examined numerous cues mediated by chemokine networks that contribute to the heterogeneity of TNBC. Recent developments in our knowledge of the chemokine networks that regulate TNBC heterogeneity may pave the door for developing difficult-to-treat TNBC treatment options.

Grading of invasive breast carcinoma: the way forward

Histologic grading has been a simple and inexpensive method to assess tumor behavior and prognosis of invasive breast cancer grading, thereby identifying patients at risk for adverse outcomes, who may be eligible for (neo)adjuvant therapies. Histologic grading needs to be performed accurately, on properly fixed specimens, and by adequately trained dedicated pathologists that take the time to diligently follow the protocol methodology. In this paper, we review the history of histologic grading, describe the basics of grading, review prognostic value and reproducibility issues, compare performance of grading to gene expression profiles, and discuss how to move forward to improve reproducibility of grading by training, feedback and artificial intelligence algorithms, and special stains to better recognize mitoses. We conclude that histologic grading, when adequately carried out, remains to be of important prognostic value in breast cancer patients.

Triple-negative apocrine carcinoma: A rare pathologic subtype with a better prognosis than other triple-negative breast cancers

BACKGROUND AND METHODS

Apocrine adenocarcinoma is a rare subtype of breast cancer. We sought to compare the characteristics and survival of patients diagnosed with triple-negative apocrine adenocarcinoma to those of patients diagnosed with triple-negative invasive ductal carcinoma. Utilizing data from the National Cancer Database between 2004 and 2013, 70 524 eligible female patients with triple-negative breast cancer were identified including 566 patients with apocrine adenocarcinomas and 69 958 patients with invasive ductal carcinoma. Descriptive statistics for each variable were reported. A comparison of each covariate between the study cohorts was assessed in univariate and multivariate analysis. Cox proportional models were used to calculate hazard ratios. Additionally, the propensity score matching method was implemented to reduce treatment selection bias.

RESULTS

Patients with triple-negative apocrine tumors were more likely to be older, Caucasian, and have smaller, moderately to well-differentiated tumors. Multivariable analysis noted a significantly improved survival for patients with triple-negative apocrine carcinoma (TNAC) vs triple-negative invasive ductal carcinoma (TNBC) (hazard ratio [HR] 0.65 [95% confidence interval [CI] [0.53-0.81], P = 0 < .001). Propensity score matching analysis confirmed a significant difference in overall survival for patients with TNAC in comparison to TNBC (HR 0.79 [95% CI [0.63-1.00], P = .05).

DISCUSSION

Triple-negative apocrine adenocarcinomas have a modestly improved long-term survival when compared with triple-negative invasive ductal cancers.

Visual histological assessment of morphological features reflects the underlying molecular profile in invasive breast cancer: a morphomolecular study

AIMS

Tumour genotype and phenotype are related and can predict outcome. In this study, we hypothesised that the visual assessment of breast cancer (BC) morphological features can provide valuable insight into underlying molecular profiles.

METHODS AND RESULTS

The Cancer Genome Atlas (TCGA) BC cohort was used (n = 743) and morphological features, including Nottingham grade and its components and nucleolar prominence, were assessed utilising whole-slide images (WSIs). Two independent scores were assigned, and discordant cases were utilised to represent cases with intermediate morphological features. Differentially expressed genes (DEGs) were identified for each feature, compared among concordant/discordant cases and tested for specific pathways. Concordant grading was observed in 467 of 743 (63%) of cases. Among concordant case groups, eight common DEGs (UGT8, DDC, RGR, RLBP1, SPRR1B, CXorf49B, PSAPL1 and SPRR2G) were associated with overall tumour grade and its components. These genes are related mainly to cellular proliferation, differentiation and metabolism. The number of DEGs in cases with discordant grading was larger than those identified in concordant cases. The largest number of DEGs was observed in discordant grade 1:3 cases (n = 1185). DEGs were identified for each discordant component. Some DEGs were uniquely associated with well-defined specific morphological features, whereas expression/co-expression of other genes was identified across multiple features and underlined intermediate morphological features.

CONCLUSION

Morphological features are probably related to distinct underlying molecular profiles that drive both morphology and behaviour. This study provides further evidence to support the use of image-based analysis of WSIs, including artificial intelligence algorithms, to predict tumour molecular profiles and outcome.

An integrated bioinformatics analysis of potential therapeutic targets among matrix metalloproteinases in breast cancer

Breast cancer (BC) is one of the most aggressive malignancies worldwide among females. Matrix metalloproteinases (MMPs), as the most abundant class of non-serine proteases present in invasive and metastatic tumors, can regulate a variety of alterations in the microenvironment during tumor progression. However, the differential expression of MMPs and its prognostic values in BC is yet to be elucidated. In this research, using the ONCOMINE dataset, The Cancer Genome Atlas, Breast Cancer Gene-Expression Miner v4.1 (Bc-GenExMiner), Kaplan-Meier Plotter and cBioPortal, the transcriptional MMPs and survival outcome data of patients with BC was compared. It was indicated that mRNA levels of MMP1/3/9/10/11/12/13 were increased compared with non-tumor tissues, whereas mRNA expression of MMP2/16/19/23B/28 was lower in BC tissues. Kaplan-Meier plots showed that high mRNA levels of MMP2/10/16/19/20/23B/27 in patients with BC were associated with better recurrence-free survival. In contrast, high MMP1/8/9/11/12 conferred worse RFS rate. Meanwhile, high transcription levels of MMP1/3/11/12/13 predicted shorter distant metastasis-free survival, while high levels of MMP1/12 demonstrated worse overall survival in patients with BC. From Bc-GenExMiner, it was indicated that high expression of MMP16/20 was correlated with better prognosis, while MMP1/9/11/12/13/14/15 exerted a negative effect on patient prognosis. The integrative bioinformatics analysis performed in the present study suggests that MMP1/9/12/16, compared with other MMPs, are potentially appropriate targets for targeted therapy in patients with BC.

Synchronous bilateral breast cancer: A case report of heterogeneous estrogen receptor status

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Hormone receptors are established biomarkers for treatment and prognosis of patients with breast cancer.

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Receptor status change is dynamic and unstable throughout tumour progression and during advance stage disease.

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Four mechanisms of breast cancer heterogeneity have been described which includes differentiation of state of cell origin, cell plasticity, genetic evolution of cancer and tumour microenvironment.

Introduction

Tumour heterogeneity is important in the management of breast cancer. Hormone receptors are established biomarkers for treatment and prognosis of patients with breast cancer.

There are three immunohistochemical biomarkers: estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor 2 (HER2).

We explore whether heterogeneity in hormone receptor status in synchronous bilateral breast alters therapeutic management.

Case presentation

This case details a 54 year old woman who was referred to our clinic by her general practitioner for investigation of bilateral breast pain that she had for 6 months.

On clinical examination pathological nodes were palpated in bilateral axilla. There was left sided nipple inversion with a palpable mass in the upper outer quadrant of approximately 3 cm diameter.

On examination of the right breast there was skin tethering of the nipple and 3 masses were palpated, the largest being in the upper inner quadrant at 5 cm diameter.

Ultrasound and mammography of bilateral breasts demonstrated advanced bilateral breast cancer with axillary node metastases.

Core biopsies demonstrated invasive carcinoma. The right breast lesion was ER negative whilst the left breast lesion was ER positive.

Discussion

In patients with synchronous bilateral breast cancer ER discordance in patients have been associated with higher mortality than ER concordant positive patients and lower mortality than ER concordant negative patients within the first 5 years of surveillance [1].

Conclusion

Heterogeneity in hormone receptor status alters the therapeutic management of patients with synchronous bilateral breast cancer. Both hormone therapy and chemotherapy should be considered in these patients.

It is of utmost importance to evaluate the tumor receptor status in cases of synchronous bilateral breast tumour and to assess for change in relation to tumour progression or treatment. Further study in the status change of receptors could open up new treatment modalities.

Tumor Heterogeneity in Breast Cancer

Breast cancer is a heterogeneous disease and differs greatly among different patients (intertumor heterogeneity) and even within each individual tumor (intratumor heterogeneity). Clinical and morphologic intertumor heterogeneity is reflected by staging systems and histopathologic classification of breast cancer. Heterogeneity in the expression of established prognostic and predictive biomarkers, hormone receptors, and human epidermal growth factor receptor 2 oncoprotein is the basis for targeted treatment. Molecular classifications are indicators of genetic tumor heterogeneity, which is probed with multigene assays and can lead to improved stratification into low- and high-risk groups for personalized therapy. Intratumor heterogeneity occurs at the morphologic, genomic, transcriptomic, and proteomic levels, creating diagnostic and therapeutic challenges. Understanding the molecular and cellular mechanisms of tumor heterogeneity that are relevant to the development of treatment resistance is a major area of research. Despite the improved knowledge of the complex genetic and phenotypic features underpinning tumor heterogeneity, there has been only limited advancement in diagnostic, prognostic, or predictive strategies for breast cancer. The current guidelines for reporting of biomarkers aim to maximize patient eligibility for targeted therapy, but do not take into account intratumor heterogeneity. The molecular classification of breast cancer is not implemented in routine clinical practice. Additional studies and in-depth analysis are required to understand the clinical significance of rapidly accumulating data. This review highlights inter- and intratumor heterogeneity of breast carcinoma with special emphasis on pathologic findings, and provides insights into the clinical significance of molecular and cellular mechanisms of heterogeneity.

The Utility of Phosphohistone H3 in Breast Cancer Grading

The commonly used Nottingham Grading System in breast cancer takes into consideration the presence of tubular formation, nuclear pleomorphism, and the mitotic index (MI), among which the latter has been shown to be the most powerful prognostic factor. In practice, histologic grading is highly subjective, with only moderate interobserver reproducibility. Phosphorylation of histone H3 has been demonstrated to be a specific event in the mitotic phase, and is negligible during interphase. In this study, we evaluated the efficacy of Phosphohistone H3 (PHH3) in the breast cancer grading of 97 consecutive biopsy specimens. PHH3 antibodies clearly revealed discrete, strong nuclear immunoreactivity in mitotically active cells even under low magnification. The PHH3 MI showed a significant correlation with that derived by hematoxylin and eosin (H&E) staining as well as the Ki-67 proliferation index. Further, the pairwise κ-value of the MI was significantly increased, and the pairwise agreement was also markedly improved by PHH3 immunostaining, although a significant proportion of breast cancer cases were upgraded by use of the PHH3 MI. Our data showed that PHH3 provided a more sensitive and accurate MI with less interobserver variability when compared with conventional H&E staining, thus emphasizing its potentially increased value in practice. Reconsideration of breast cancer grading with integration of PHH3 should be considered if it continues to demonstrate superiorly to traditional H&E staining.

Study of the influence of the ph of water in the initiation of digestive tract injury in cadmium poisoning in rats

Cancer has genetic and environmental causes, one of which is the ingestion of heavy metals such as cadmium.

Objective

To evaluate the lesions caused by cadmium poisoning in the digestive tract and the possible effect of the drinking water pH in the initiation of these lesions.

Methods

90 male Wistar rats were used, divided into six groups (n = 15): A – received 400 mg/l cadmium chloride (CdCl2) in drinking water at a neutral pH of 7.0; B – received CdCl2 (400 mg/l) in drinking water at an acidic pH of 5.0; C – received CdCl2 (400 mg/l) in drinking water at a basic pH of 8.0; D – received water at an acidic pH of 5.0; E – received water at a basic pH of 8.0; and F – received water at a neutral pH of 7.0. Animals were euthanized after 6 months. Samples of the esophagus, stomach, small intestine and large intestine of each rat were removed for microscopic analysis.

Results

There were no microscopic changes in either the esophagus or small and large intestines. Only cadmium-exposed animals showed mild dysplasia of the gastric mucosa (p = 0.012), regardless of the pH (p > 0.05).

Conclusion

Cadmium exposure led to the formation of dysplastic lesions in the gastric glandular epithelium, regardless of the water pH.

p63/MT1-MMP axis is required for in situ to invasive transition in basal-like breast cancer

The transition of ductal carcinoma in situ (DCIS) to invasive breast carcinoma requires tumor cells to cross the basement membrane (BM). However, mechanisms underlying BM transmigration are poorly understood. Here, we report that expression of membrane-type 1 (MT1)-matrix metalloproteinase (MMP), a key component of the BM invasion program, increases during breast cancer progression at the in situ to invasive breast carcinoma transition. In the intraductal xenograft model, MT1-MMP is required for BM transmigration of MCF10DCIS.com breast adenocarcinoma cells and is overexpressed in cell clusters overlying focal BM disruptions and at the invasive tumor front. Mirrored upregulation of p63 and MT1-MMP is observed at the edge of MCF10DCIS.com xenograft tumors and p63 is required for induction of MT1-MMP-dependent invasive program in response to microenvironmental signals. Immunohistochemistry and analysis of public database reveal that p63 and MT1-MMP are upregulated in human basal-like breast tumors suggesting that p63/MT1-MMP axis contributes to progression of basal-like breast cancers with elevated p63 and MT1-MMP levels.

Correlation between Nottingham Prognostic Index and Adjuvant! Online prognostic tools in patients with early-stage breast cancer in Mid-Western Ireland

BACKGROUND

Prognostic tools are widely used in the practice of oncology and have been developed to help stratify patients into specific risk-related grouping. We sought to apply tool such tools used for patients with early-stage breast cancer (EBC) and correlate them to actual outcomes.

METHODS

A retrospective analysis was designed to include EBC cases seen at the Mid-Western Regional Hospital from January 1, 2002, to December 31, 2002. Information was derived from the patients' records, and indices were derived from prognostic tools. Information was analyzed using descriptive statistics and chi-square or Fisher exact test.

RESULTS

A total of 77 patients were found, with a median age of 52.2 years. A median overall survival (OS) of 84 months was observed. The majority presented with moderately differentiated estrogen receptor positive invasive ductal carcinoma and lymph node involvement (60%). Sixty-four percent of patients underwent mastectomy as opposed to breast conservation. Adjuvant cytotoxic chemotherapy uptake was 61%, which was comparable to the proportion of node positive disease. The Nottingham Prognostic Index and Adjuvant! Online (AO) tools were both correlated with actual survival, with the AO showing better correlation.

CONCLUSIONS

This report underscores that these predicting tools were both underestimations consistent with the actual OS and highlights the importance of further work in validating these tools within our own population.

Comparison of Oncotype DX and Mammostrat risk estimations and correlations with histologic tumor features in low-grade, estrogen receptor-positive invasive breast carcinomas

Several molecular tests have been developed to estimate risk of distant recurrence and help clinical decision-making regarding adjuvant chemotherapy in patients with early stage breast carcinoma. Both Oncotype DX, a 21-gene expression profile, and Mammostrat, an immunohistochemistry-based assay, are validated to stratify patients into groups with low, intermediate and high risk of distant recurrence. However, they have not been compared head-to-head and little data are available regarding their correlation with clinicopathologic tumor features. In this study, we compared the clinicopathologic tumor features with risk estimations by Oncotype DX and Mammostrat in 106 low-grade estrogen receptor (ER)-positive breast carcinomas. Double immunohistochemical stain for pancytokeratin and Ki-67 was performed to assess cell proliferation in cancer vs stromal/inflammatory cells. Tumors showing intermediate/high risk by Oncotype DX, but not by Mammostrat, showed increased stromal cellularity, presence of inflammatory cells and increased proliferation in stromal/inflammatory cells. Discrepant cases showing intermediate/high risk by Oncotype DX but low risk by Mammostrat were associated with increased stromal cellularity, presence of inflammatory cells and increased proliferation in stromal/inflammatory cells, compared with concordant cases showing low risk by both assays. Our results suggest that low-grade ER-positive breast carcinomas with increased stromal/inflammatory cell proliferation may show an apparent increased risk of distant recurrence as assessed by Oncotype DX, which uses RNA extracted from a mixture of tumor and stromal/inflammatory cells in the assay. Mammostrat, which examines cancer cells only, may provide a better estimation of likely tumor behavior in a subgroup of low-grade breast carcinomas.

Modeling of breast cancer prognostic factors using a parametric log-logistic model in Fars province, Southern Iran

In general, breast cancer is the most common malignancy among women in developed as well as some developing countries, often being the second leading cause of cancer mortality after lung cancer. Using a parametric log-logistic model to consider the effects of prognostic factors, the present study focused on the 5-year survival of women with the diagnosis of breast cancer in Southern Iran. A total of 1,148 women who were diagnosed with primary invasive breast cancer from January 2001 to January 2005 were included and divided into three prognosis groups: poor, medium, and good. The survival times as well as the hazard rates of the three different groups were compared. The log-logistic model was employed as the best parametric model which could explain survival times. The hazard rates of the poor and the medium prognosis groups were respectively 13 and 3 times greater than in the good prognosis group. Also, the difference between the overall survival rates of the poor and the medium prognosis groups was highly significant in comparison to the good prognosis group. Use of the parametric log-logistic model - also a proportional odds model - allowed assessment of the natural process of the disease based on hazard and identification of trends.

MicroRNAs and metastasis-related gene expression in Egyptian breast cancer patients

AIM AND BACKGROUND

MicroRNAs (miRNAs) are a class of naturally occurring small noncoding RNAs that regulate gene expression, cell growth, differentiation and apoptosis by targeting mRNAs for translational repression or cleavage. The present study was conducted to study miRNAs in Egyptian breast cancer (BC) and their relation to metastasis, tumor invasion and apoptosis in addition to their association with the ER and PR statuses.

METHODS

Real Time RT-PCR was performed to identify the miRNA expression level of eight miRNAs and eight metastatic-related genes in 40 breast cancer samples and their adjacent non-neoplastic tissues. The expression levels of each miRNA relative to U6 RNA were determined. Also, miRNA expression profiles of the BC and their corresponding ANT were evaluated.

RESULTS

The BC patients showed an up-regulation in miRNAs (mir-155, mir-10, mir-21 and mir-373) with an upregulation in MMP2, MMp9 and VEGF genes. We found down regulation in mir-17p, mir-126, mir-335, mir-30b and also TIMP3, TMP1 and PDCD4 genes in the cancer tissue compared to the adjacent non-neoplastic tissues. Mir -10b, mir -21, mir-155 and mir373 and the metastatic genes MMP2, MMP9 and VEGF were significantly associated with an increase in tumor size (P<0.05). No significant difference was observed between any of the studied miRNAs regarding lymph node metastasis. Mir-21 was significantly over-expressed in ER-/PR- cases.

CONCLUSION

Specific miRNAs (mir-10, mir-21, mir-155, mir-373, mir-30b, mir-126, mir-17p, mir-335) are associated with tumor metastasis and other clinical characteristics for BC, facilitating identification of individuals who are at risk.

A mitotically active, cellular tumor stroma and/or inflammatory cells associated with tumor cells may contribute to intermediate or high Oncotype DX Recurrence Scores in low-grade invasive breast carcinomas

Oncotype DX is an RT-PCR-based 21-gene assay validated to provide prognostic and predictive information in the form of a Recurrence Score in patients with estrogen receptor-positive, lymph node-negative breast cancer. Although the Recurrence Score was shown to correlate with several histopathological tumor features, there is a significant proportion of cases showing an apparent discrepancy between Recurrence Score and risk estimates based on the traditional clinicopathological tumor features. In this study, we tested whether a proliferating, cellular stroma and/or admixed inflammatory cells may result in an artificially increased Recurrence Score in low-grade invasive breast cancers. We analyzed the histopathological features in 141 low-grade invasive breast carcinomas, including 41 special type (tubular, cribriform and mucinous) carcinomas, with available Recurrence Score. The tumor stroma was evaluated for increased cellularity and presence of inflammatory cells. Double immunohistochemical stains for pancytokeratin and Ki-67 was performed to assess the cell proliferation in tumor vs stromal/inflammatory cells. The clinicopathological features of tumors with Recurrence Score <18 (low risk) were compared with those with Recurrence Score ≥18 (intermediate/high risk). Carcinomas associated with Recurrence Score ≥18 showed lower progesterone receptor immunoreactivity, increased stromal cellularity and presence of inflammatory cells associated with the tumor. Double immunohistochemical stains showed significantly increased proliferation in stromal/inflammatory cells compared with carcinoma cells in cases associated with Recurrence Score ≥18. A Ki-67-positive stromal/tumor cells ratio of >1 predicted Recurrence Score ≥18 with an area under the curve of 0.8967 on receiver operator curve analysis (P<0.0001). Our results suggest that the presence of increased stromal cellularity and/or associated inflammatory cells in low-grade invasive breast carcinomas may contribute to an apparently increased risk of recurrence according to Oncotype DX Recurrence Score. Careful assessment and correlation with histopathological features in such cases may help in determining the appropriate patient management.

Protein-protein interaction reveals synergistic discrimination of cancer phenotype

Cancer is a disease associated with the deregulation of multiple gene networks. Microarray data has permitted researchers to identify gene panel markers for diagnosis or prognosis of cancer but these are not sufficient to make specific mechanistic assertions about phenotype switches. We propose a strategy to identify putative mechanisms of cancer phenotypes by protein-protein interactions (PPI). We first extracted the logic status of a PPI via the relative expression of the corresponding gene pair. The joint association of a gene pair on a cancer phenotype was calculated by entropy minimization and assessed using a support vector machine. A typical predictor is “If Src high-expression, and Cav-1 low-expression, then cancer.” We achieved 90% accuracy on test data with a majority of predictions associated with the MAPK pathway, focal adhesion, apoptosis and cell cycle. Our results can aid in the development of phenotype discrimination biomarkers and identification of putative therapeutic interference targets for drug development.

Cellular processes of v-Src transformation revealed by gene profiling of primary cells--implications for human cancer

Background

Cell transformation by the Src tyrosine kinase is characterized by extensive changes in gene expression. In this study, we took advantage of several strains of the Rous sarcoma virus (RSV) to characterize the patterns of v-Src-dependent gene expression in two different primary cell types, namely chicken embryo fibroblasts (CEF) and chicken neuroretinal (CNR) cells. We identified a common set of v-Src regulated genes and assessed if their expression is associated with disease-free survival using several independent human tumor data sets.

Methods

CEF and CNR cells were infected with transforming, non-transforming, and temperature sensitive mutants of RSV to identify the patterns of gene expression in response to v-Src-transformation. Microarray analysis was used to measure changes in gene expression and to define a common set of v-Src regulated genes (CSR genes) in CEF and CNR cells. A clustering enrichment regime using the CSR genes and two independent breast tumor data-sets was used to identify a 42-gene aggressive tumor gene signature. The aggressive gene signature was tested for its prognostic value by conducting survival analyses on six additional tumor data sets.

Results

The analysis of CEF and CNR cells revealed that cell transformation by v-Src alters the expression of 6% of the protein coding genes of the genome. A common set of 175 v-Src regulated genes (CSR genes) was regulated in both CEF and CNR cells. Within the CSR gene set, a group of 42 v-Src inducible genes was associated with reduced disease- and metastasis-free survival in several independent patient cohorts with breast or lung cancer. Gene classes represented within this group include DNA replication, cell cycle, the DNA damage and stress responses, and blood vessel morphogenesis.

Conclusion

By studying the v-Src-dependent changes in gene expression in two types of primary cells, we identified a set of 42 inducible genes associated with poor prognosis in breast and lung cancer. The identification of these genes provides a set of biomarkers of aggressive tumor behavior and a framework for the study of cancer cells characterized by elevated Src kinase activity.

Multiple biomarkers in molecular oncology. II. Molecular diagnostics applications in breast cancer management

In recent years, the application of genomic and proteomic technologies to the problem of breast cancer prognosis and the prediction of therapy response have begun to yield encouraging results. Independent studies employing transcriptional profiling of primary breast cancer specimens using DNA microarrays have identified gene expression profiles that correlate with clinical outcome in primary breast biopsy specimens. Recent advances in microarray technology have demonstrated reproducibility, making clinical applications more achievable. In this regard, one such DNA microarray device based upon a 70-gene expression signature was recently cleared by the US FDA for application to breast cancer prognosis. These DNA microarrays often employ at least 70 gene targets for transcriptional profiling and prognostic assessment in breast cancer. The use of PCR-based methods utilizing a small subset of genes has recently demonstrated the ability to predict the clinical outcome in early-stage breast cancer. Furthermore, protein-based immunohistochemistry methods have progressed from using gene clusters and gene expression profiling to smaller subsets of expressed proteins to predict prognosis in early-stage breast cancer. Beyond prognostic applications, DNA microarray-based transcriptional profiling has demonstrated the ability to predict response to chemotherapy in early-stage breast cancer patients. In this review, recent advances in the use of multiple markers for prognosis of disease recurrence in early-stage breast cancer and the prediction of therapy response will be discussed.

Four miRNAs associated with aggressiveness of lymph node-negative, estrogen receptor-positive human breast cancer

In this study, we quantified 249 mature micro-RNA (miRNA) transcripts in estrogen receptor-positive (ER(+)) primary breast tumors of patients with lymph node-negative (LNN) disease to identify miRNAs associated with metastatic capability. In addition, the prognostic value of the candidate miRNAs was determined in ER(-)/LNN breast cancer. Unsupervised analysis in a prescreening set of 38 patients identified three subgroups predominantly driven by three miRNA signatures: an ER-driven luminal B-associated miRNA signature, a stromal miRNA signature, and an overexpressed miRNA cluster located on chromosome 19q23, but these intrinsic miRNA signatures were not associated with tumor aggressiveness. Supervised analysis in the initial subset and subsequent analysis in additional tumors significantly linked four miRNAs (miR-7, miR-128a, miR-210, and miR-516-3p) to ER(+)/LNN breast cancer aggressiveness (n = 147) and one miRNA (miR-210) to metastatic capability in ER(-)/LNN breast cancer (n = 114) and in the clinically important triple-negative subgroup (n = 69) (all P < 0.05). Bioinformatic analysis coupled miR-210 to hypoxia/VEGF signaling, miR-7 and miR-516-3p to cell cycle progression and chromosomal instability, and miR-128a to cytokine signaling. In conclusion, our work connects four miRNAs to breast cancer progression and to several distinct biological processes involved therein.

Prognostic significance of Nottingham histologic grade in invasive breast carcinoma

PURPOSE

The three strongest prognostic determinants in operable breast cancer used in routine clinical practice are lymph node (LN) stage, primary tumor size, and histologic grade. However, grade is not included in the recent revision of the TNM staging system of breast cancer as its value is questioned in certain settings.

MATERIALS AND METHODS

This study is based on a large and well-characterized consecutive series of operable breast cancer (2,219 cases), treated according to standard protocols in a single institution, with a long-term follow-up (median, 111 months) to assess the prognostic value of routine assessment of histologic grade using Nottingham histologic grading system.

RESULTS

Histologic grade is strongly associated with both breast cancer-specific survival (BCSS) and disease-free survival (DFS) in the whole series as well as in different subgroups based on tumor size (pT1a, pT1b, pT1c, and pT2) and LN stages (pN0 and pN1 and pN2). Differences in survival were also noted between different individual grades (1, 2, and 3). Multivariate analyses showed that histologic grade is an independent predictor of both BCSS and DFS in operable breast cancer as a whole as well as in all studied subgroups.

CONCLUSION

Histologic grade, as assessed by the Nottingham grading system, provides a strong predictor of outcome in patients with invasive breast cancer and should be incorporated in breast cancer staging systems.

Gene-expression microarrays provide new prognostic and predictive tests for breast cancer

Wide availability of systemic therapy agents has led to a considerable decline in mortality from breast cancer. However, the biology of breast cancer remains poorly understood. Currently, highly accurate markers to predict prognosis and probability of response to a given systemic therapy on an individual basis are lacking, and routinely used clinicopathologic variables fail to fully capture the heterogeneity of breast cancer. As a result, many patients are overtreated, whereas others may not receive the necessary therapy. It has been hypothesized that molecular differences in breast cancers might account for the heterogeneous potential in growth, invasion and metastasis in each individual tumor. Gene-expression microarrays have been extensively applied in breast cancer research in the hope that a combination of multiple genes (i.e., gene signatures) will more informatively predict disease outcome and response to a specific systemic therapy. This technique holds substantial promise for optimizing clinical decision making and tailoring therapeutic regimens to individual patients in the near future. This review focuses on the recent progression in feasibility and reliability of gene-expression microarrays in identifying new prognostic and predictive indicators of breast cancer.

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

A modular analysis of breast cancer reveals a novel low-grade molecular signature in estrogen receptor-positive tumors

PURPOSE

Previous reports using genome-wide gene expression data to classify breast tumors have typically used standard unsupervised or supervised techniques, both of which have known limitations. We hypothesized that novel clinically relevant information could be revealed in these data sets by an alternative analytic approach. Using a recently described algorithm, signature analysis (SA), we identified "modules," comprising groups of tightly coexpressed genes that are conditionally linked to particular tumors, in a series of breast tumor gene expression profiles.

EXPERIMENTAL DESIGN AND RESULTS

The SA successfully identified multiple breast cancer modules specifically linked to distinct biological functions. We identified a novel module, TuM1, whose presence was not readily discernible by conventional clustering techniques. The TuM1 module is expressed in a subset of estrogen receptor (ER)-positive tumors and is significantly enriched with genes involved in apoptosis and cell death. Clinically, TuM1-expressing tumors are associated with low histopathologic grade, and this association is independent of the inherent ER status of a tumor. We confirmed the robustness and general applicability of TuM1 module by demonstrating its association with low tumor grade in multiple independent breast cancer data sets generated using different array technologies. In vitro, the TuM1 module is down-regulated in ER+ MCF7 cells upon treatment with tamoxifen, suggesting that TuM1 expression may be dependent on active signaling by ER. Initial data is also suggestive that TuM1 expression may be clinically associated with a patient's response to antihormonal therapy.

CONCLUSION

Our results suggest that modular-based approaches toward gene expression data can prove useful in identifying novel, robust, and biologically relevant signatures even from data sets that have been the subject of substantial prior analysis.

Minichromosome maintenance proteins 2 and 5 in non-benign epithelial ovarian tumours: relationship with cell cycle regulators and prognostic implications

Minichromosome maintenance proteins (MCM) have recently emerged as novel proliferation markers with prognostic implications in several tumour types. This is the first study investigating MCM-2 and MCM-5 immunohistochemical expression in a series of ovarian adenocarcinomas and low malignant potential (LMP) tumours aiming to determine possible associations with clinicopathological parameters, the conventional proliferation index Ki-67, cell cycle regulators (p53, p27(Kip1), p21(WAF1) and pRb) and patients' outcome. Immunohistochemistry was applied in a series of 43 cases of ovarian LMP tumours and 85 cases of adenocarcinomas. Survival analysis was restricted to adenocarcinomas. The median MCM-2 and MCM-5 labelling indices (LIs) were significantly higher in adenocarcinomas compared to LMP tumours (P<0.0001 for both associations). In adenocarcinomas, the levels of MCM-2 and MCM-5 increased significantly with advancing tumour stage (P=0.0052 and P=0.0180, respectively), whereas both MCM-2 and MCM-5 increased significantly with increasing tumour grade (P=0.0002 and P=0.0006, respectively) and the presence of bulky residual disease (P<0.0001 in both relationships). A strong positive correlation was established between MCM-2 or MCM-5 expression level and Ki-67 LI (P<0.0001) as well as p53 protein (P=0.0038 and P=0.0500, respectively). Moreover, MCM-2 LI was inversely correlated with p27(Kip-1) LI (P=0.0068). Finally, both MCM-2 and MCM-5 were associated significantly with adverse patients' outcome in both univariate (> or =20 vs >20%, P=0.0011 and > or =25 vs <25%, P=0.0100, respectively) and multivariate (P=0.0001 and 0.0090, respectively) analysis. An adequately powered independent group of 45 patients was used in order to validate our results in univariate survival analysis. In this group, MCM-2 and MCM-5 expression retained their prognostic significance (P<0.0001 in both relationships). In conclusion, MCM-2 and MCM-5 proteins appear to be promising as prognostic markers in patients with ovarian adenocarcinomas.

Consensus genes of the literature to predict breast cancer recurrence

BACKGROUND

Extensive efforts have been undertaken to discover genes relevant for breast cancer prognosis. Yet, in current opinion, with little overlap in findings. We aimed to reanalyze molecular prediction of breast cancer recurrence.

METHODS

From 44 published gene lists relevant for breast cancer prognosis, we extracted 374 genes, which, besides other quality criteria, are recorded at least twice. From eight published microarray datasets, a single dataset of 1,067 breast cancer patients was created, using transformation to 'probability of expression' scale. For recurrence analysis, the Cox proportional hazards model was applied.

RESULTS

The 374 genes, termed '374 Gene Set', are highly enriched in cell cycle genes. The '374 Gene Set' is significantly associated with breast cancer recurrence (p = 2 x 10(-12), log-rank test) in the meta set of 1,067 patients, showing an estimated Hazard Ratio of recurrence for the 'poor' prognosis group compared to the 'good' prognosis group of 2.03 (95% confidence interval, 1.66-2.48). Notably, the '374 Gene Set' is significantly associated with recurrence in untreated patients. In multivariate analysis, including the standard histopathological parameters, only tumor size and the '374 Gene Set' remain independent predictors of recurrence. External validation further confirmed the prognostic relevance of the gene set (253 patients, p = 0.001, log-rank test).

CONCLUSIONS

The '374 Gene Set' comprises a molecular basis of metastatic breast cancer progression. Starting from this gene set it might be possible to construct a clinically relevant classifier, which then again needs to be validated.

Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer

Background

Published prognostic gene signatures in breast cancer have few genes in common. Here we provide a rationale for this observation by studying the prognostic power and the underlying biological pathways of different gene signatures.

Methods

Gene signatures to predict the development of metastases in estrogen receptor-positive and estrogen receptor-negative tumors were identified using 500 re-sampled training sets and mapping to Gene Ontology Biological Process to identify over-represented pathways. The Global Test program confirmed that gene expression profilings in the common pathways were associated with the metastasis of the patients.

Results

The apoptotic pathway and cell division, or cell growth regulation and G-protein coupled receptor signal transduction, were most significantly associated with the metastatic capability of estrogen receptor-positive or estrogen-negative tumors, respectively. A gene signature derived of the common pathways predicted metastasis in an independent cohort. Mapping of the pathways represented by different published prognostic signatures showed that they share 53% of the identified pathways.

Conclusion

We show that divergent gene sets classifying patients for the same clinical endpoint represent similar biological processes and that pathway-derived signatures can be used to predict prognosis. Furthermore, our study reveals that the underlying biology related to aggressiveness of estrogen receptor subgroups of breast cancer is quite different.

Transcriptomic signatures in breast cancer

High throughput DNA microarray technology has been broadly applied to the study of breast cancer to classify molecular subtypes, to predict outcome, survival, response to treatment, and for the identification of novel therapeutic targets. Although results are promising, this technology will not have a full impact on routine clinical practice until there is further standardization of techniques and optimal clinical trial design. Due to substantial disease heterogeneity and the number of genes being analyzed, collaborative, multi-institutional studies are required to accrue enough patients for sufficient statistical power. Newer bioinformatic approaches are being developed to assist with the analysis of this important data.

Gene expression profiles as biomarkers for the prediction of chemotherapy drug response in human tumour cells

Genome profiling approaches such as cDNA microarray analysis and quantitative reverse transcription polymerase chain reaction are playing ever-increasing roles in the classification of human cancers and in the discovery of biomarkers for the prediction of prognosis in cancer patients. Increasing research efforts are also being directed at identifying set of genes whose expression can be correlated with response to specific drugs or drug combinations. Such genes hold the prospect of tailoring chemotherapy regimens to the individual patient, based on tumour or host gene expression profiles. This review outlines recent advances and challenges in using genome profiling for the identification of tumour or host genes whose expression correlates with response to chemotherapy drugs both in vitro and in clinical studies. Genetic predictors of response to a variety of anticancer agents are discussed, including the anthracyclines, taxanes, topoisomerase I and II inhibitors, nucleoside analogs, alkylating agents, and vinca alkaloids.

Geminin is essential for the development of preimplantation mouse embryos

Replication of DNA is strictly controlled to ensure that it occurs only once per cell cycle. Geminin has been thought to serve as a central mediator of this licensing mechanism by binding to and antagonizing the function of Cdt1 and thereby preventing re-replication during S and G2 phases. We have now generated mice deficient in geminin to elucidate the physiologic role of this protein during development. Lack of geminin was shown to result in preimplantation mortality. A delay in the development of homozygous mutant embryos was first apparent at the transition from the four- to eight-cell stages, concomitant with the disappearance of maternal geminin protein, and development was arrested at the eight-cell stage. The mutant embryos manifest morphological abnormalities such as dispersed blastomeres with nuclei that are irregular both in size and shape as well as impaired cell-cell adhesion. DNA replication occurs but mitosis was not detected in the mutant embryos. The abnormal blastomeres contain damaged DNA and undergo apoptosis, likely as a consequence of the deregulation of DNA replication. Our results suggest that geminin is essential for cooperative progression of the cell cycle through S phase to M phase during the preimplantation stage of mouse development.

The medulloblastoma cell line DAOY but not eleven other tumor cell lines expresses minichromosome maintenance protein 4

Minichromosome maintenance proteins (MCM) are required for initiation and elongation of chromosomal DNA, ensuring that DNA replication takes place only once. Although MCMs are considered of utmost importance in tumor biology and as potential marker proteins, they were not unambiguously identified at the protein level and we therefore aimed to characterize MCM 4 in a medulloblastoma cell line and provide a protein chemical analytical tool. In addition, we searched for this protein in twelve tumor cell lines and a series of non-tumor cells. The DAOY medulloblastoma cell line was cultivated, lysed, proteins extracted and run on two-dimensional gel electrophoresis with subsequent in-gel digestion and mass spectrometrical (MS/MS) analysis of protein spots. One spot at pI 6.2 with an observed molecular weight of 98 kDa was identified as minichromosome maintenance protein 4 by peptide fingerprinting. Sequence coverage of 35% along with 25 matched peptides and MS/MS analyses of three matching peptides warranted unambiguous identification. The use of mass spectrometrical identification unequivocally allowed determination of MCM 4 expression in a medulloblastoma cell line exclusively. Given the biological and probable clinical importance of this molecule as a tentative marker protein, a fair analytical tool, independent of antibody availability and specificity is mandatory and determinations at the transcriptional level cannot be extrapolated to protein levels per se, as there is a long and unpredictable way from mRNA to protein.

Topological and functional discovery in a gene coexpression meta-network of gastric cancer

Gastric cancer is a leading cause of global cancer mortality, but comparatively little is known about the cellular pathways regulating different aspects of the gastric cancer phenotype. To achieve a better understanding of gastric cancer at the levels of systems topology, functional modules, and constituent genes, we assembled and systematically analyzed a consensus gene coexpression meta-network of gastric cancer incorporating >300 tissue samples from four independent patient populations (the "gastrome"). We find that the gastrome exhibits a hierarchical scale-free architecture, with an internal structure comprising multiple deeply embedded modules associated with diverse cellular functions. Individual modules display distinct subtopologies, with some (cellular proliferation) being integrated within the primary network, and others (ribosomal biosynthesis) being relatively isolated. One module associated with intestinal differentiation exhibited a remarkably high degree of autonomy, raising the possibility that its specific topological features may contribute towards the frequent occurrence of intestinal metaplasia in gastric cancer. At the single-gene level, we discovered a novel conserved interaction between the PLA2G2A prognostic marker and the EphB2 receptor, and used tissue microarrays to validate the PLA2G2A/EphB2 association. Finally, because EphB2 is a known target of the Wnt signaling pathway, we tested and provide evidence that the Wnt pathway may also similarly regulate PLA2G2A. Many of these findings were not discernible by studying the single patient populations in isolation. Thus, besides enhancing our knowledge of gastric cancer, our results show the broad utility of applying meta-analytic approaches to genome-wide data for the purposes of biological discovery.

Molecular Subtyping of Breast Cancer from Traditional Tumor Marker Profiles Using Parallel Clustering Methods

PURPOSE

Recent small-sized genomic studies on the identification of breast cancer bioprofiles have led to profoundly dishomogenous results. Thus, we sought to identify distinct tumor profiles with possible clinical relevance based on clusters of immunohistochemical molecular markers measured on a large, single institution, case series.

EXPERIMENTAL DESIGN

Tumor biological profiles were explored on 633 archival tissue samples analyzed by immunohistochemistry. Five validated markers were considered, i.e., estrogen receptors (ER), progesterone receptors (PR), Ki-67/MIB1 as a proliferation marker, HER2/NEU, and p53 in their original scale of measurement. The results obtained were analyzed by three different clustering algorithms. Four different indices were then used to select the different profiles (number of clusters).

RESULTS

The best classification was obtained creating four clusters. Notably, three clusters were identified according to low, intermediate, and high ER/PR levels. A further subdivision in two biologically distinct subtypes was determined by the presence/absence of HER2/NEU and of p53. As expected, the cluster with high ER/PR levels was characterized by a much better prognosis and response to hormone therapy compared to that with the lowest ER/PR values. Notably, the cluster characterized by high HER2/NEU levels showed intermediate prognosis, but a rather poor response to hormone therapy.

CONCLUSIONS

Our results show the possibility of profiling breast cancers by means of traditional markers, and have novel clinical implications on the definition of the prognosis of cancer patients. These findings support the existence of a tumor subtype that responds poorly to hormone therapy, characterized by HER2/NEU overexpression.

Preoperative Profiling of Symptomatic Breast Cancer by Diagnostic Core Biopsy

BACKGROUND

Precise preoperative profiling of breast tumors could facilitate fuller consideration of (neo)adjuvant therapies.

METHODS

Diagnostic core biopsy (DCB) accuracy in profiling the primary tumor was prospectively studied in 95 patients with operable breast cancer. The histological type and grade (hematoxylin and eosin staining) and membrane receptor status (semiquantitative immunohistochemistry for estrogen [ER] and progesterone [PR] receptors, as well as Her-2 antigen expression) were assigned by the DCB before surgery. These measures were then compared with those of the definitive surgical specimen available after operation.

RESULTS

DCB correctly ascribed tumor type and grade and ER, PR, and Her-2 receptor status in most cases (correlating exactly in 97.5%, 77%, 68%, 71%, and 60%, respectively) with at least moderate concordance (weighted kappa, >.41). When miscategorized, DCB consistently tended to upscore the receptor stain intensity compared with the surgical specimen (22%, 19%, and 27% had higher ER, PR, and Her-2 categorical scores, respectively). ER H-scores correlated best in specimens that stained strongly (224.4 +/- 3 vs. 215.5 +/- 5) and were significantly higher on DCB in those that stained either moderately (195.6 +/- 8.2 vs. 156.8 +/- 5.1; P < .0001) or weakly (157.1 +/- 24.8 vs. 81.4 +/- 4; P = .02). DCB accurately identified all tumors with clinically important ER and Her-2 expression. Furthermore, it promoted three patients into the therapeutically significant range of ER (n = 1) or Her-2 (n = 2) expression. ER negativity on DCB (n = 25) indicated a high-grade tumor (88%), although 11 (44%) patients also overexpressed Her-2. Significant Her-2 expression (n = 16) on DCB predicted the tumor as being poorly differentiated (80%) and both ER and PR negative (67%).

CONCLUSIONS

DCB accurately profiles clinically relevant measures of primary tumor cell differentiation. It also reliably categorizes patients with regard to (neo)adjuvant therapy before radical surgery is attempted.

cDNA microarray analysis of isogenic paclitaxel- and doxorubicin-resistant breast tumor cell lines reveals distinct drug-specific genetic signatures of resistance

cDNA microarray analysis is a highly useful tool for the classification of tumors and for prediction of patient prognosis to specific cancers based on this classification. However, to date, there is little evidence that microarray approaches can be used to reliably predict patient response to specific chemotherapy drugs or regimens. This is likely due to an inability to differentiate between genes affecting patient prognosis and genes that play a role in response to specific drugs. Thus, it would be highly useful to identify genes whose expression correlates with tumor cell sensitivity to specific chemotherapy agents in a drug-specific manner. Using cDNA microarray analysis of wildtype MCF-7 breast tumor cells and isogenic paclitaxel-resistant (MCF-7(TAX)) or doxorubicin-resistant (MCF-7(DOX)) derivative cell lines, we have uncovered drug-specific changes in gene expression that accompany the establishment of paclitaxel or doxorubicin resistance. These changes in gene expression were confirmed by quantitative reverse transcription polymerase chain reaction and immunoblotting experiments, with a confirmation rate of approximately 91-95%. The genes identified may prove highly useful for prediction of response to paclitaxel or doxorubicin in patients with breast cancer. To our knowledge this is the first report of drug-specific genetic signatures of resistance to paclitaxel or doxorubicin, based on a comparison of gene expression between isogenic wildtype and drug-resistant tumor cell lines. Moreover, this study provides significant insight into the wide variety of mechanisms through which resistance to these agents may be acquired in breast cancer.

Control of DNA replication and its potential clinical exploitation

Multiple conserved mechanisms limit DNA replication to once per cell cycle. One vital level of control focuses on the loading of the heterohexameric ring of minichromosome maintenance proteins (MCMs) onto chromatin in the hierarchical assembly of the pre-replication complex at origins of replication. An essential role in proliferation for MCMs and their regulators makes them potentially important biomarkers for routine clinical use in cancer detection and prognosis.

Breast cancer gene expression profiling: clinical trial and practice implications

The advent of high-throughput array-based technology and the sequencing of the human genome has provided the opportunity to begin comprehensive molecular and genetic profiling of cancers. Such efforts have, in a limited time, given us new insights into breast cancer biology and confirmed that the disease is considerably more heterogeneous than can be predicted by traditional histopathological methods. The estrogen receptor has been found to be the most dominant factor influencing the molecular composition of breast cancer and, in addition, novel subgroups of breast cancer with differing clinical outcomes have been observed. These may have substantial management implications for breast cancer patients and facilitate individualized rather than empirical oncological prescription. Furthermore, new methods of prognostic classification have been developed using array technology. The challenges ahead lie in refining the use of the technology, proper validation of discoveries, and the large-scale collaborative efforts necessary for the incorporation of genomic knowledge into the design and conduct of clinical trials. This will lead, ultimately, to the application of user-friendly tools derived from this technology to everyday patient care.

Cell-cycle-dependent regulation of DNA replication and its relevance to cancer pathology

The highly orchestrated process of DNA replication ensures the accurate inheritance of genetic information from one cell generation to the next. The exact execution of DNA replication depends on a large number of proteins that are being studied extensively in the cell cycle field. Some of these proteins, such as the minichromosome maintenance proteins (MCMs), are essential for the process of DNA replication itself. Others such as geminin are specifically required to limit DNA replication to once per cell cycle. Together, these proteins protect the stability of the human genome in cycling cells. Their expression has been compared with routinely used proliferation markers, such as Ki-67 (MIB-1) and proliferating cell nuclear antigen (PCNA), which fulfil the requirements of molecular tumour markers to varying extents. However, it is with regard to the depth of our understanding of antigen biology that the MCM proteins and geminin qualify exceptionally well as novel cell-cycle biomarkers for routine use in clinical practice, particularly in cancer detection and estimation of prognosis. Expression microarray analysis has also independently identified MCMs and their interacting proteins as determinants of the inherent aggressiveness of a wide range of epithelial malignancies.