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Globally, 9 million women are diagnosed with cancer each year. Breast cancer is the most commonly diagnosed cancer worldwide, followed by colorectal cancer in high-income countries and cervical cancer in low-income countries. Survival from cancer is improving and more women are experiencing long-term effects of cancer treatment, such as premature ovarian insufficiency or early menopause. Managing menopausal symptoms after cancer can be challenging, and more severe than at natural menopause. Menopausal symptoms can extend beyond hot flushes and night sweats (vasomotor symptoms). Treatment-induced symptoms might include sexual dysfunction and impairment of sleep, mood, and quality of life. In the long term, premature ovarian insufficiency might increase the risk of chronic conditions such as osteoporosis and cardiovascular disease. Diagnosing menopause after cancer can be challenging as menopausal symptoms can overlap with other common symptoms in patients with cancer, such as fatigue and sexual dysfunction. Menopausal hormone therapy is an effective treatment for vasomotor symptoms and seems to be safe for many patients with cancer. When hormone therapy is contraindicated or avoided, emerging evidence supports the efficacy of non-pharmacological and non-hormonal treatments, although most evidence is based on women older than 50 years with breast cancer. Vaginal oestrogen seems safe for most patients with genitourinary symptoms, but there are few non-hormonal options. Many patients have inadequate centralised care for managing menopausal symptoms after cancer treatment, and more information is needed about cost-effective and patient-focused models of care for this growing population., Competing Interests: Declaration of interests MH declares salary funding from the Australian National Health and Medical Research Council, support for meeting attendance from the UK National Institute for Health and Care Excellence, and the following roles: principal investigator for a clinical trial of salpingectomy vs salpingo-oophorectomy for prevention of ovarian cancer (TUBA-WISP II); board member for Breastscreen Victoria; editor for the Cochrane Collaboration; recipient of a fellowship from the Lundbeck Foundation (2022-23); site investigator for a clinical trial of a non-hormonal agent (Q-122) for vasomotor symptoms in patients with breast cancer (QUE Oncology, 2020-22); and site investigator for a clinical trial of a medical device for treating vaginal dryness (Madorra). JS is a site investigator for neurokinin B antagonist for vasomotor symptoms and has received travel grants for conference attendance from Mylan and Besins. AHP has received royalties for coauthorship of the breast cancer survivorship section of UpToDate. DJB acknowledges financial support from Precision Oncology Ireland, which is part-funded by the Science Foundation Ireland Strategic Partnership Programme (grant number 18/SPP/3522), and has received co-funding from AstraZeneca. DJB is the principal investigator of an investigator-initiated clinical trial of digital cognitive behavioural therapy and gabapentin for treatment of menopause symptoms after cancer, supported by the Irish Cancer Society (WHIBREN2020). DJB has received speaker fees or honoraria from Bayer, GSK, MSD, Olympus, and AstraZeneca and has participated on a data safety monitoring board or advisory board for Astellas, Bayer, and GSK. All other authors declare no competing interests., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In the Republic of Ireland (ROI), BRCA1/BRCA2 genetic testing has been traditionally undertaken in eligible individuals, after pre-test counselling by a Clinical Geneticist/Genetic Counsellor. Clinical Genetics services in ROI are poorly resourced, with routine waiting times for appointments at the time of this pilot often extending beyond a year. The consequent prolonged waiting times are unacceptable where therapeutic decision-making depends on the patient's BRCA status. "Mainstreaming" BRCA1/BRCA2 testing through routine oncology/surgical clinics has been implemented successfully in other centres in the UK and internationally. We aimed to pilot this pathway in three Irish tertiary centres. A service evaluation project was undertaken over a 6-month period between January and July 2017. Eligible patients, fulfilling pathology and age-based inclusion criteria defined by TGL clinical, were identified, and offered constitutional BRCA1/BRCA2 testing after pre-test counselling by treating clinicians. Tests were undertaken by TGL Clinical. Results were returned to clinicians by secure email. Onward referrals of patients with uncertain/pathogenic results, or suspicious family histories, to Clinical Genetics were made by the treating team. Surveys assessing patient and clinician satisfaction were sent to participating clinicians and a sample of participating patients. Data was collected with respect to diagnostic yield, turnaround time, onward referral rates, and patient and clinician feedback. A total of 101  patients underwent diagnostic germline BRCA1/BRCA2 tests through this pathway. Pathogenic variants were identified in 12 patients (12%). All patients in whom variants were identified were appropriately referred to Clinical Genetics. At least 12 additional patients with uninformative BRCA1/BRCA2 tests were also referred for formal assessment by Clinical Geneticist or Genetic Counsellor. Issues were noted in terms of time pressures and communication of results to patients. Results from a representative sample of participants completing the satisfaction survey indicated that the pathway was acceptable to patients and clinicians. Mainstreaming of constitutional BRCA1/BRCA2 testing guided by age- and pathology-based criteria is potentially feasible for patients with breast cancer as well as patients with ovarian cancer in Ireland., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

Up to 80% of endometrial and breast cancers express oestrogen receptor alpha (ERα). Unlike breast cancer, anti-oestrogen therapy has had limited success in endometrial cancer, raising the possibility that oestrogen has different effects in both cancers. We investigated the role of oestrogen in endometrial and breast cancers using data from The Cancer Genome Atlas (TCGA) in conjunction with cell line studies. Using phosphorylation of ERα (ERα-pSer118) as a marker of transcriptional activation of ERα in TCGA datasets, we found that genes associated with ERα-pSer118 were predominantly unique between tumour types and have distinct regulators. We present data on the alternative and novel roles played by SMAD3, CREB-pSer133 and particularly XBP1 in oestrogen signalling in endometrial and breast cancer.

G9a is an epigenetic regulator that methylates H3K9, generally causing repression of gene expression, and participates in diverse cellular functions. G9a is genetically deregulated in a variety of tumor types and can silence tumor suppressor genes and, therefore, is important for carcinogenesis. Although hypoxia is recognized to be an adverse factor in tumor growth and metastasis, the role of G9a in regulating gene expression in hypoxia has not been described extensively. Here, we show that G9a protein stability is increased in hypoxia via reduced proline hydroxylation and, hence, inefficient degradation by the proteasome. This inefficiency leads to an increase in H3K9me2 at its target promoters. Blocking the methyltransferase activity of G9a inhibited cellular proliferation and migration in vitro and tumor growth in vivo. Furthermore, an increased level of G9a is a crucial factor in mediating the hypoxic response by down-regulating the expression of specific genes, including ARNTL , CEACAM7 , GATA2 , HHEX , KLRG1 , and OGN This down-regulation can be rescued by a small molecule inhibitor of G9a. Based on the hypothesis that the changes in gene expression would influence patient outcomes, we have developed a prognostic G9a-suppressed gene signature that can stratify breast cancer patients. Together, our findings provide an insight into the role G9a plays as an epigenetic mediator of hypoxic response, which can be used as a diagnostic marker, and proposes G9a as a therapeutic target for solid cancers., Competing Interests: The authors declare no conflict of interest.

Introduction: Peroxiredoxin-1 (PRDX1) is a multifunctional protein, acting as a hydrogen peroxide (H2O2) scavenger, molecular chaperone and immune modulator. Although differential PRDX1 expression has been described in many tumors, the potential role of PRDX1 in breast cancer remains highly ambiguous. Using a comprehensive antibody-based proteomics approach, we interrogated PRDX1 protein as a putative biomarker in estrogen receptor (ER)-positive breast cancer., Methods: An anti-PRDX1 antibody was validated in breast cancer cell lines using immunoblotting, immunohistochemistry and reverse phase protein array (RPPA) technology. PRDX1 protein expression was evaluated in two independent breast cancer cohorts, represented on a screening RPPA (n = 712) and a validation tissue microarray (n = 498). In vitro assays were performed exploring the functional contribution of PRDX1, with oxidative stress conditions mimicked via treatment with H2O2, peroxynitrite, or adenanthin, a PRDX1/2 inhibitor., Results: In ER-positive cases, high PRDX1 protein expression is a biomarker of improved prognosis across both cohorts. In the validation cohort, high PRDX1 expression was an independent predictor of improved relapse-free survival (hazard ratio (HR) = 0.62, 95% confidence interval (CI) = 0.40 to 0.96, P = 0.032), breast cancer-specific survival (HR = 0.44, 95% CI = 0.24 to 0.79, P = 0.006) and overall survival (HR = 0.61, 95% CI = 0.44 to 0.85, P = 0.004). RPPA screening of cancer signaling proteins showed that ERα protein was upregulated in PRDX1 high tumors. Exogenous H2O2 treatment decreased ERα protein levels in ER-positive cells. PRDX1 knockdown further sensitized cells to H2O2- and peroxynitrite-mediated effects, whilst PRDX1 overexpression protected against this response. Inhibition of PRDX1/2 antioxidant activity with adenanthin dramatically reduced ERα levels in breast cancer cells., Conclusions: PRDX1 is shown to be an independent predictor of improved outcomes in ER-positive breast cancer. Through its antioxidant function, PRDX1 may prevent oxidative stress-mediated ERα loss, thereby potentially contributing to maintenance of an ER-positive phenotype in mammary tumors. These results for the first time imply a close connection between biological activity of PRDX1 and regulation of estrogen-mediated signaling in breast cancer.

Background: Although omic-based discovery approaches can provide powerful tools for biomarker identification, several reservations have been raised regarding the clinical applicability of gene expression studies, such as their prohibitive cost. However, the limited availability of antibodies is a key barrier to the development of a lower cost alternative, namely a discrete collection of immunohistochemistry (IHC)-based biomarkers. The aim of this study was to use a systematic approach to generate and screen affinity-purified, mono-specific antibodies targeting progression-related biomarkers, with a view towards developing a clinically applicable IHC-based prognostic biomarker panel for breast cancer., Methods: We examined both in-house and publicly available breast cancer DNA microarray datasets relating to invasion and metastasis, thus identifying a cohort of candidate progression-associated biomarkers. Of these, 18 antibodies were released for extended analysis. Validated antibodies were screened against a tissue microarray (TMA) constructed from a cohort of consecutive breast cancer cases (n = 512) to test the immunohistochemical surrogate signature., Results: Antibody screening revealed 3 candidate prognostic markers: the cell cycle regulator, Anillin (ANLN); the mitogen-activated protein kinase, PDZ-Binding Kinase (PBK); and the estrogen response gene, PDZ-Domain Containing 1 (PDZK1). Increased expression of ANLN and PBK was associated with poor prognosis, whilst increased expression of PDZK1 was associated with good prognosis. A 3-marker signature comprised of high PBK, high ANLN and low PDZK1 expression was associated with decreased recurrence-free survival (p < 0.001) and breast cancer-specific survival (BCSS) (p < 0.001). This novel signature was associated with high tumour grade (p < 0.001), positive nodal status (p = 0.029), ER-negativity (p = 0.006), Her2-positivity (p = 0.036) and high Ki67 status (p < 0.001). However, multivariate Cox regression demonstrated that the signature was not a significant predictor of BCSS (HR = 6.38; 95% CI = 0.79-51.26, p = 0.082)., Conclusions: We have developed a comprehensive biomarker pathway that extends from discovery through to validation on a TMA platform. This proof-of-concept study has resulted in the identification of a novel 3-protein prognostic panel. Additional biochemical markers, interrogated using this high-throughput platform, may further augment the prognostic accuracy of this panel to a point that may allow implementation into routine clinical practice.

Purpose: Here, we describe an integrated bioinformatics, functional analysis, and translational pathology approach to identify novel miRNAs involved in breast cancer progression., Experimental Design: Coinertia analysis (CIA) was used to combine a database of predicted miRNA target sites and gene expression data. Using two independent breast cancer cohorts, CIA was combined with correspondence analysis and between group analysis to produce a ranked list of miRNAs associated with disease progression. Ectopic expression studies were carried out in MCF7 cells and miRNA expression evaluated in two additional cohorts of patients with breast cancer by in situ hybridization on tissue microarrays., Results: CIA identified miR-187 as a key miRNA associated with poor outcome in breast cancer. Ectopic expression of miR-187 in breast cancer cells resulted in a more aggressive phenotype. In a test cohort (n = 117), high expression of miR-187 was associated with a trend toward reduced breast cancer-specific survival (BCSS; P = 0.058), and a significant association with reduced BCSS in lymph node-positive patients (P = 0.036). In a validation cohort (n = 470), high miR-187 was significantly associated with reduced BCSS in the entire cohort (P = 0.021) and in lymph node-positive patients (P = 0.012). Multivariate Cox regression analysis revealed that miR-187 is an independent prognostic factor in both cohorts [cohort 1: HR, 7.37; 95% confidence interval (CI), 2.05-26.51; P = 0.002; cohort 2: HR, 2.80; 95% CI, 1.52-5.16; P = 0.001] and in lymph node-positive patients in both cohorts (cohort 1: HR, 13.74; 95% CI, 2.62-72.03; P = 0.002; cohort 2: HR, 2.77; 95% CI, 1.32-5.81; P = 0.007)., Conclusions: miR-187 expression in breast cancer leads to a more aggressive, invasive phenotype and acts as an independent predictor of outcome., (©2012 AACR.)

Unlabelled: Immune-regulated pathways influence multiple aspects of cancer development. In this article we demonstrate that both macrophage abundance and T-cell abundance in breast cancer represent prognostic indicators for recurrence-free and overall survival. We provide evidence that response to chemotherapy is in part regulated by these leukocytes; cytotoxic therapies induce mammary epithelial cells to produce monocyte/macrophage recruitment factors, including colony stimulating factor 1 (CSF1) and interleukin-34, which together enhance CSF1 receptor (CSF1R)-dependent macrophage infiltration. Blockade of macrophage recruitment with CSF1R-signaling antagonists, in combination with paclitaxel, improved survival of mammary tumor-bearing mice by slowing primary tumor development and reducing pulmonary metastasis. These improved aspects of mammary carcinogenesis were accompanied by decreased vessel density and appearance of antitumor immune programs fostering tumor suppression in a CD8+ T-cell-dependent manner. These data provide a rationale for targeting macrophage recruitment/response pathways, notably CSF1R, in combination with cytotoxic therapy, and identification of a breast cancer population likely to benefit from this novel therapeutic approach., Significance: These findings reveal that response to chemotherapy is in part regulated by the tumor immune microenvironment and that common cytotoxic drugs induce neoplastic cells to produce monocyte/macrophage recruitment factors, which in turn enhance macrophage infiltration into mammary adenocarcinomas. Blockade of pathways mediating macrophage recruitment, in combination with chemotherapy, significantly decreases primary tumor progression, reduces metastasis, and improves survival by CD8+ T-cell-dependent mechanisms, thus indicating that the immune microenvironment of tumors can be reprogrammed to instead foster antitumor immunity and improve response to cytotoxic therapy.

Introduction: We previously reported an association between tumor-specific 3-hydroxy-3-methylglutharyl-coenzyme A reductase (HMG-CoAR) expression and a good prognosis in breast cancer. Here, the predictive value of HMG-CoAR expression in relation to tamoxifen response was examined., Methods: HMG-CoAR protein and RNA expression was analyzed in a cell line model of tamoxifen resistance using western blotting and PCR. HMG-CoAR mRNA expression was examined in 155 tamoxifen-treated breast tumors obtained from a previously published gene expression study (Cohort I). HMG-CoAR protein expression was examined in 422 stage II premenopausal breast cancer patients, who had previously participated in a randomized control trial comparing 2 years of tamoxifen with no systemic adjuvant treatment (Cohort II). Kaplan-Meier analysis and Cox proportional hazards modeling were used to estimate the risk of recurrence-free survival (RFS) and the effect of HMG-CoAR expression on tamoxifen response., Results: HMG-CoAR protein and RNA expression were decreased in tamoxifen-resistant MCF7-LCC9 cells compared with their tamoxifen-sensitive parental cell line. HMG-CoAR mRNA expression was decreased in tumors that recurred following tamoxifen treatment (P < 0.001) and was an independent predictor of RFS in Cohort I (hazard ratio = 0.63, P = 0.009). In Cohort II, adjuvant tamoxifen increased RFS in HMG-CoAR-positive tumors (P = 0.008). Multivariate Cox regression analysis demonstrated that HMG-CoAR was an independent predictor of improved RFS in Cohort II (hazard ratio = 0.67, P = 0.010), and subset analysis revealed that this was maintained in estrogen receptor (ER)-positive patients (hazard ratio = 0.65, P = 0.029). Multivariate interaction analysis demonstrated a difference in tamoxifen efficacy relative to HMG-CoAR expression (P = 0.05). Analysis of tamoxifen response revealed that patients with ER-positive/HMG-CoAR tumors had a significant response to tamoxifen (P = 0.010) as well as patients with ER-positive or HMG-CoAR-positive tumors (P = 0.035). Stratification according to ER and HMG-CoAR status demonstrated that ER-positive/HMG-CoAR-positive tumors had an improved RFS compared with ER-positive/HMG-CoAR-negative tumors in the treatment arm (P = 0.033); this effect was lost in the control arm (P = 0.138), however, suggesting that HMG-CoAR predicts tamoxifen response., Conclusions: HMG-CoAR expression is a predictor of response to tamoxifen in both ER-positive and ER-negative disease. Premenopausal patients with tumors that express ER or HMG-CoAR respond to adjuvant tamoxifen.

Background: Conflicting data exist regarding the prognostic and predictive impact of survivin (BIRC5) in breast cancer. We previously reported survivin cytoplasmic-to-nuclear ratio (CNR) as an independent prognostic indicator in breast cancer. Here, we validate survivin CNR in a separate and extended cohort. Furthermore, we present new data suggesting that a low CNR may predict outcome in tamoxifen-treated patients., Methods: Survin expression was assessed using immunhistochemistry on a breast cancer tissue microarray (TMA) containing 512 tumours. Whole slide digital images were captured using an Aperio XT scanner. Automated image analysis was used to identify tumour from stroma and then to quantify tumour-specific nuclear and cytoplasmic survivin. A decision tree model selected using a 10-fold cross-validation approach was used to identify prognostic subgroups based on nuclear and cytoplasmic survivin expression., Results: Following optimisation of the staining procedure, it was possible to evaluate survivin protein expression in 70.1% (n = 359) of the 512 tumours represented on the TMA. Decision tree analysis predicted that nuclear, as opposed to cytoplasmic, survivin was the most important determinant of overall survival (OS) and breast cancer-specific survival (BCSS). The decision tree model confirmed CNR of 5 as the optimum threshold for survival analysis. Univariate analysis demonstrated an association between a high CNR (>5) and a prolonged BCSS (HR 0.49, 95% CI 0.29-0.81, p = 0.006). Multivariate analysis revealed a high CNR (>5) was an independent predictor of BCSS (HR 0.47, 95% CI 0.27-0.82, p = 0.008). An increased CNR was associated with ER positive (p = 0.045), low grade (p = 0.007), Ki-67 (p = 0.001) and Her2 (p = 0.026) negative tumours. Finally, a high CNR was an independent predictor of OS in tamoxifen-treated ER-positive patients (HR 0.44, 95% CI 0.23-0.87, p = 0.018)., Conclusion: Using the same threshold as our previous study, we have validated survivin CNR as a marker of good prognosis in breast cancer in a large independent cohort. These findings provide robust evidence of the importance of survivin CNR as a breast cancer biomarker, and its potential to predict outcome in tamoxifen-treated patients.

Using transgenic mouse models of breast cancer that ablate Src homology and collagen A (ShcA) expression or oncogene-coupled ShcA signaling, we previously showed that this adaptor is critical for mammary tumor onset and progression. We now provide the first evidence that ShcA regulates mammary tumorigenesis, in part, through its ability to regulate the adaptive immune response. Inactivation of ShcA signaling within tumor cells results in extensive CD4(+) T-cell infiltration and induction of a humoral immune response in mammary tumors. This is associated with a robust CTL response in preneoplastic lesions that are deficient in ShcA signaling. Moreover, mammary tumor progression of ShcA-deficient hyperplasias is accelerated in a T cell-deficient background. We also uncover a clinically relevant correlation between high ShcA expression and low CTL infiltration in human breast cancers. Finally, we define a novel ShcA-regulated immune signature that functions as an independent prognostic marker of survival in human epidermal growth factor receptor 2(+) and basal breast cancers. We reveal a novel role for tumor cell-derived ShcA in the establishment and maintenance of an immunosuppressive state., (©2010 AACR.)

Twenty-nine single-nucleotide polymorphisms (SNPs) from previously published genome-wide association studies (GWAS) and multiple ancestry informative markers were genotyped in the Carolina Breast Cancer Study (CBCS) (742 African-American (AA) cases, 1230 White cases; 658 AA controls, 1118 White controls). In the entire study population, 9/10 SNPs in fibroblast growth factor receptor 2 (FGFR2) were significantly associated with breast cancer after adjusting for age, race and European ancestry [odds ratios (OR) range 1.17-1.81]. Associations were observed for SNPs in FGFR2, LSP1, H19, TLR1/TLR6 and RELN for AA; FGFR2, TNRC9, H19 and MAP3K1 for Whites; FGFR2, TNRC9, Msc5A1 and chromosome 8q for women > or =50 years old and FGFR2 and TNRC9 for women <50 years old. FGFR2 haplotypes based upon rs11200014, rs2981579, rs1219648 and rs2420946 were associated with increased risk of breast cancer, including the GTGT haplotype in AAs [OR = 1.27, 95% confidence interval (CI) 1.04-1.56] and younger women of either race [OR = 1.35, 95% CI 1.02-1.78) and the ATGT haplotype in Whites (OR = 1.30, 95% CI 1.15-1.46). Recent GWAS hits for breast cancer in Europeans and Whites (i.e. women of European descent) thus showed evidence of replication among AAs and Whites in the CBCS. Several new haplotypes were associated with breast cancer in AA and younger women, particularly the FGFR2 GTGT haplotype. These results highlight the need to conduct GWAS among younger women and in a variety of racial-ethnic populations.

Background: Previous studies have shown that the ADIPOR1, ADORA1, BTG2 and CD46 genes differ significantly between long-term survivors of breast cancer and deceased patients, both in levels of gene expression and DNA copy numbers. The aim of this study was to characterize the expression of the corresponding proteins in breast carcinoma and to determine their correlation with clinical outcome., Methods: Protein expression was evaluated using immunohistochemistry in an independent breast cancer cohort of 144 samples represented on tissue microarrays. Fisher's exact test was used to analyze the differences in protein expression between dead and alive patients. We used Cox-regression multivariate analysis to assess whether the new markers predict the survival status of the patients better than the currently used markers., Results: BTG2 expression was demonstrated in a significantly lower proportion of samples from dead patients compared to alive patients, both in overall expression (P = 0.026) and cell membrane specific expression (P = 0.013), whereas neither ADIPOR1, ADORA1 nor CD46 showed differential expression in the two survival groups. Furthermore, a multivariate analysis showed that a model containing BTG2 expression in combination with HER2 and Ki67 expression along with patient age performed better than a model containing the currently used prognostic markers (tumour size, nodal status, HER2 expression, hormone receptor status, histological grade, and patient age). Interestingly, BTG2 has previously been described as a tumour suppressor gene involved in cell cycle arrest and p53 signalling., Conclusions: We conclude that high-level BTG2 protein expression correlates with prolonged survival in patients with breast carcinoma.

Introduction: The homeobox-containing transcription factor muscle segment homeobox 2 (Msx2) plays an important role in mammary gland development. However, the clinical implications of Msx2 expression in breast cancer are unclear. The aims of this study were to investigate the potential clinical value of Msx2 as a breast cancer biomarker and to clarify its functional role in vitro., Methods: Msx2 gene expression was first examined in a well-validated breast cancer transcriptomic dataset of 295 patients. Msx2 protein expression was then evaluated by immunohistochemistry in a tissue microarray (TMA) containing 281 invasive breast tumours. Finally, to assess the functional role of Msx2 in vitro, Msx2 was ectopically expressed in a highly invasive breast tumour cell line (MDA-MB-231) and an immortalised breast cell line (MCF10a), and these cell lines were examined for changes in growth rate, cell death and cell signalling., Results: Examination of Msx2 mRNA expression in a breast cancer transcriptomic dataset demonstrated that increased levels of Msx2 were associated with good prognosis (P = 0.011). Evaluation of Msx2 protein expression on a TMA revealed that Msx2 was detectable in both tumour cell nuclei and cytoplasm. Cytoplasmic Msx2 expression was associated with low grade tumours (P = 0.012) and Ki67 negativity (P = 0.018). Nuclear Msx2 correlated with low-grade tumours (P = 0.015), estrogen receptor positivity (P = 0.038), low Ki67 (P = 0.005) and high cyclin D1 expression (P = 0.037). Increased cytoplasmic Msx2 expression was associated with a prolonged breast cancer-specific survival (P = 0.049), recurrence-free survival (P = 0.029) and overall survival (P = 0.019). Ectopic expression of Msx2 in breast cell lines resulted in radically decreased cell viability mediated by induction of cell death via apoptosis. Further analysis of Msx2-expressing cells revealed increased levels of p21 and phosphorylated extracellular signal-regulated kinase (ERK) and decreased levels of Survivin and the 'split ends' (SPEN) protein family member RBM15., Conclusions: We conclude that increased Msx2 expression results in improved outcome for breast cancer patients, possibly by increasing the likelihood of tumour cell death by apoptosis.

Single-strand RNA-binding proteins (RBPs) are involved in many aspects of RNA metabolism and in the regulation of gene transcription. The RBP RBM3 was recently suggested to be a proto-oncogene in colorectal cancer; however, such a role has not been corroborated by previous studies in the colon or other tumor types, and the prognostic implications of tumor-specific RBM3 expression remain unclear. Mono-specific antibodies against RBM3 were generated. Antibody specificity was confirmed using siRNA gene silencing, western blotting and immunohistochemistry on a panel of breast cancer cell lines. Using tissue microarrays and IHC, RBM3 protein expression was examined in 48 normal tissues and in 20 common cancers. Additional analysis in two independent breast cancer cohorts (n=1016) with long-term follow-up was also carried out. RBM3 was upregulated in cancer compared to normal tissues. The nuclear expression of RBM3 in breast cancer was associated with low grade (P<0.001), small tumors (P<0.001), estrogen receptor (ER) positivity (P<0.001) and Ki-67 negativity (P<0.001) in both the breast cancer cohorts. An increased nuclear expression of RBM3 was associated with a prolonged overall and recurrence-free survival. The prognostic value was particularly pronounced in hormone receptor-positive tumors and remained significant in multivariate interaction analysis after controlling for tamoxifen treatment (HR: 0.49, 95% CI: 0.30-0.79, P=0.004). These data strongly indicate that nuclear RBM3 is an independent favorable prognostic factor in breast cancer, and seems to have a specific role in ER-positive tumors.

The cell-cell adhesion protein junctional adhesion molecule-A (JAM-A) influences epithelial cell morphology and migration. As migration is required for tumor cell invasion and metastasis, we sought to elucidate the role of JAM-A in invasive breast cancer. A breast cancer tissue microarray was analyzed for JAM-A protein expression, in parallel with analysis of JAM-A gene expression data from a breast cancer clinical dataset. Our data demonstrate a novel association between JAM-A gene and protein upregulation and poor prognosis in breast cancer. To mechanistically dissect this process, we used lentiviral technology to stably knock down JAM-A gene expression by shRNA in MCF7 breast cancer cells, which express high-endogenous levels of JAM-A. We also antagonized JAM-A function in wild-type MCF7 cells using an inhibitory antibody that blocks JAM-A dimerization. Knockdown or functional antagonism of JAM-A decreased breast cancer cell migration in scratch-wound assays. Reductions in beta1-integrin protein levels were observed after JAM-A-knockdown in MCF7 cells, suggesting a mechanism for reduced motility after loss of JAM-A. Consistent with this hypothesis, tissue microarray analysis of beta1-integrin protein expression in invasive breast cancer tissues revealed a trend toward high beta1-integrin protein levels being indicative of poor prognosis. Twenty-two percent of patients were observed to coexpress high levels of JAM-A and beta1-integrin protein, and MDA-MB-231 breast cells stably overexpressing JAM-A showed an increase in beta1-integrin protein expression. Our results are consistent with a previously unreported role for JAM-A overexpression as a possible mechanism contributing to progression in primary breast cancer; and a potential therapeutic target., (2009 UICC)

This study systematically analyzes platelet-derived growth factor (PDGF) receptor expression in six types of common tumors as well as examines associations between PDGF beta-receptor status and clinicopathological characteristics in breast cancer. PDGF receptor expression was determined by immunohistochemistry on tumor tissue microarrays. Breast tumor data were combined with prognostic factors and related to outcome endpoints. PDGF alpha- and beta-receptors were independently expressed, at variable frequencies, in the tumor stroma of all tested tumor types. There was a significant association between PDGF beta-receptor expression on fibroblasts and perivascular cells in individual colon and prostate tumors. In breast cancer, high stromal PDGF beta-receptor expression was significantly associated with high histopathological grade, estrogen receptor negativity, and high HER2 expression. High stromal PDGF beta-receptor expression was correlated with significantly shorter recurrence-free and breast cancer-specific survival. The prognostic significance of stromal PDGF beta-receptor expression was particularly prominent in tumors from premenopausal women. Stromal PDGF alpha- and beta-receptor expression is a common, but variable and independent, property of solid tumors. In breast cancer, stromal PDGF beta-receptor expression significantly correlates with less favorable clinicopathological parameters and shorter survival. These findings highlight the prognostic significance of stromal markers and should be considered in ongoing clinical development of PDGF receptor inhibitors.

The role of intercellular tight junctions in breast epithelial cells is traditionally thought to be in maintaining polarity and barrier function. However, claudin-4, a tight junction protein, is overexpressed in breast tumour cells compared to normal epithelial cells, which generally corresponds to a loss in polarity. The aim of this study was to investigate the distribution and potential clinical value of claudin-4 in breast cancer, and to evaluate its usefulness as a prognostic and predictive biomarker. Expression of claudin-4 was initially examined by Western blot analysis in a cohort of 88 breast tumours, and was found to correlate positively with tumour grade and negatively with ER. Claudin-4 expression was then evaluated by immunohistochemistry in a larger cohort of 299 tumours represented on a tissue microarray. Claudin-4 expression correlated positively with tumour grade and Her2, and negatively with ER. High claudin-4 expression was also associated with worse breast cancer-specific survival (p = 0.003), recurrence-free survival (p = 0.025) and overall survival (p = 0.034). Multivariate analysis revealed that claudin-4 independently predicted survival in the entire cohort (HR 1.95; 95%CI 1.01-3.79; p = 0.047) and in the ER positive subgroup treated with adjuvant tamoxifen (HR 4.34; 95%CI 1.14-16.53; p = 0.032). This relationship between increased claudin-4 expression and adverse outcome was validated at the mRNA level in a DNA microarray dataset of 295 breast tumours. We conclude that high levels of claudin-4 protein are associated with adverse outcome in breast cancer patients, including the subgroup of patients treated with adjuvant tamoxifen., ((c) 2008 Wiley-Liss, Inc.)

Purpose: Survivin (BIRC5) is a promising tumor biomarker. Conflicting data exist on its prognostic effect in breast cancer. These data may at least be partly due to the manual interpretation of immunohistochemical staining, especially as survivin can be located in both the nucleus and cytoplasm. Quantitative determination of survivin expression using image analysis offers the opportunity to develop alternative scoring models for survivin immunohistochemistry. Here, we present such a model., Experimental Design: A breast cancer tissue microarray containing 102 tumors was stained with an anti-survivin antibody. Whole-slide scanning was used to capture high-resolution images. These images were analyzed using automated algorithms to quantify the staining., Results: Increased nuclear, but not cytoplasmic, survivin was associated with a reduced overall survival (OS; P = 0.038) and disease-specific survival (P = 0.0015). A high cytoplasmic-to-nuclear ratio (CNR) of survivin was associated with improved OS (P = 0.005) and disease-specific survival (P = 0.05). Multivariate analysis revealed that the survivin CNR was an independent predictor of OS (hazard ratio, 0.09; 95% confidence interval, 0.01-0.76; P = 0.027). A survivin CNR of >5 correlated positively with estrogen receptor (P = 0.019) and progesterone receptor (P = 0.033) levels, whereas it was negatively associated with Ki-67 expression (P = 0.04), p53 status (P = 0.005), and c-myc amplification (P = 0.016)., Conclusion: Different prognostic information is supplied by nuclear and cytoplasmic survivin in breast cancer. Nuclear survivin is a poor prognostic marker in breast cancer. Moreover, CNR of survivin, as determined by image analysis, is an independent prognostic factor.

Introduction: We have previously reported that tumour-specific expression of the rate-limiting enzyme, 3-hydroxy-3-methylglutharyl-coenzyme A reductase (HMG-CoAR), in the mevalonate pathway is associated with more favourable tumour parameters in breast cancer. In the present study, we examined the prognostic value of HMG-CoAR expression in a large cohort of primary breast cancer patients with long-term follow up., Methods: The expression of HMG-CoAR was assessed by immunohistochemistry on tissue microarrays with tumour specimens from 498 consecutive cases of breast cancer with a median follow-up of 128 months. Kaplan Meier analysis and Cox proportional hazards modelling were used to estimate the rate of recurrence-free survival (RFS) and breast cancer specific survival (BCSS)., Results: In line with our previous findings, tumour-specific HMG-CoAR expression was associated with low grade (p < 0.001), small size (p = 0.007), oestrogen receptor (ER) positive (p = 0.01), low Ki-67 (p = 0.02) tumours. Patients with tumours expressing HMG-CoAR had a significantly prolonged RFS, even when adjusted for established prognostic factors (relative risk [RR] = 0.60, 95% confidence interval [CI] 0.40 to 0.92; p = 0.02). In ER-negative tumours, however, there was a trend, that was not significantly significant, towards a shorter RFS in HMG-CoAR expressing tumours., Conclusions: HMG-CoAR expression is an independent predictor of a prolonged RFS in primary breast cancer. This may, however, not be true for ER-negative tumours. Further studies are needed to shed light on the value of HMG-CoAR expression as a surrogate marker of response to statin treatment, especially with respect to hormone receptor status.

Introduction: Manual interpretation of immunohistochemistry (IHC) is a subjective, time-consuming and variable process, with an inherent intra-observer and inter-observer variability. Automated image analysis approaches offer the possibility of developing rapid, uniform indicators of IHC staining. In the present article we describe the development of a novel approach for automatically quantifying oestrogen receptor (ER) and progesterone receptor (PR) protein expression assessed by IHC in primary breast cancer., Methods: Two cohorts of breast cancer patients (n = 743) were used in the study. Digital images of breast cancer tissue microarrays were captured using the Aperio ScanScope XT slide scanner (Aperio Technologies, Vista, CA, USA). Image analysis algorithms were developed using MatLab 7 (MathWorks, Apple Hill Drive, MA, USA). A fully automated nuclear algorithm was developed to discriminate tumour from normal tissue and to quantify ER and PR expression in both cohorts. Random forest clustering was employed to identify optimum thresholds for survival analysis., Results: The accuracy of the nuclear algorithm was initially confirmed by a histopathologist, who validated the output in 18 representative images. In these 18 samples, an excellent correlation was evident between the results obtained by manual and automated analysis (Spearman's rho = 0.9, P < 0.001). Optimum thresholds for survival analysis were identified using random forest clustering. This revealed 7% positive tumour cells as the optimum threshold for the ER and 5% positive tumour cells for the PR. Moreover, a 7% cutoff level for the ER predicted a better response to tamoxifen than the currently used 10% threshold. Finally, linear regression was employed to demonstrate a more homogeneous pattern of expression for the ER (R = 0.860) than for the PR (R = 0.681)., Conclusions: In summary, we present data on the automated quantification of the ER and the PR in 743 primary breast tumours using a novel unsupervised image analysis algorithm. This novel approach provides a useful tool for the quantification of biomarkers on tissue specimens, as well as for objective identification of appropriate cutoff thresholds for biomarker positivity. It also offers the potential to identify proteins with a homogeneous pattern of expression.

Completion of the human genome project has revolutionised translational medicine. High-throughput technology now permits investigators to systematically interrogate the genome, transcriptome, proteome and metabolome. It is expected that these advances will eventually be translated into new more sensitive diagnostic tests and less toxic therapeutics. A major shift is expected in clinical oncology over the next few decades as we start to move away from currently practiced, population-based approaches to personalised medicine. In this emerging approach, the molecular and pathophysiological characteristics of an individual patient and tumour will be measured and tailored therapeutic regimens will be administered based on these profiles. One of the key steps in this process will be the identification and validation of biomarkers. Whilst great advances have been made in the discovery of putative biomarkers, disappointingly few have been translated into clinically applicable assays. It is widely believed that this is due to a lack of well-designed, thorough validation studies. Here, we review the role of DNA microarrays and tissue microarrays in the validation of biomarkers in breast cancer, with emphasis on their potential application to determine mode of personalised therapy in the future.

DNA microarrays have the potential to classify tumors according to their transcriptome. Tissue microarrays (TMAs) facilitate the validation of biomarkers by offering a high-throughput approach to sample analysis. We reanalyzed a high profile breast cancer DNA microarray dataset containing 96 tumor samples using a powerful statistical approach, between group analyses. Among the genes we identified was centromere protein-F (CENP-F), a gene associated with poor prognosis. In a published follow-up breast cancer DNA microarray study, comprising 295 tumour samples, we found that CENP-F upregulation was significantly associated with worse overall survival (p<0.001) and reduced metastasis-free survival (p<0.001). To validate and expand upon these findings, we used 2 independent breast cancer patient cohorts represented on TMAs. CENP-F protein expression was evaluated by immunohistochemistry in 91 primary breast cancer samples from cohort I and 289 samples from cohort II. CENP-F correlated with markers of aggressive tumor behavior including ER negativity and high tumor grade. In cohort I, CENP-F was significantly associated with markers of CIN including cyclin E, increased telomerase activity, c-Myc amplification and aneuploidy. In cohort II, CENP-F correlated with VEGFR2, phosphorylated Ets-2 and Ki67, and in multivariate analysis, was an independent predictor of worse breast cancer-specific survival (p=0.036) and overall survival (p=0.040). In conclusion, we identified CENP-F as a biomarker associated with poor outcome in breast cancer and showed several novel associations of biological significance., ((c) 2006 Wiley-Liss, Inc.)

Breast cancer is the one of leading causes of cancer-related deaths in women within economically developed regions of the world. A major focus of present research into this malignancy is the identification of new biomarkers and drug targets to improve detection and treatment. Proteomics represents one of the latest technological developments in this context. It aims to analyse the complex circuitry of the breast cancer proteome. Here, the authors review how breast cancer proteomics has progressed so far, with emphasis on its potential application to clinically relevant scenarios.

Purpose: Hypoxia in breast cancer is associated with poor prognosis and down-regulation of the estrogen receptor. Carbonic anhydrase IX (CA IX) is a hypoxia-inducible gene that has been associated with poor outcome in many epithelial cancers. Previous studies of CA IX in breast cancer have been carried out on mixed cohorts of premenopausal and postmenopausal patients with locally advanced disease and varying treatment regimens. We examined the potential prognostic and predictive role of CA IX in premenopausal breast cancer patients., Experimental Design: Using tissue microarrays, we analyzed CA IX expression in 400 stage II breast cancers from premenopausal women. The patients had previously participated in a randomized control trial comparing 2 years of tamoxifen to no systemic adjuvant treatment. Median follow-up was 13.9 years., Results: CA IX expression correlated positively with tumor size, grade, hypoxia-inducible factor 1alpha, Ki-67, cyclin E, and cyclin A2 expression. CA IX expression correlated negatively with cyclin D1, estrogen receptor, and progesterone receptor. CA IX expression was associated with a reduced relapse-free survival (P=0.032), overall survival (P=0.022), and breast cancer-specific survival (P=0.005). Multivariate analysis revealed that CA IX was an independent prognostic marker in untreated patients with one to three positive lymph nodes (hazard ratio, 3.2; 95% confidence interval, 1.15-9.13; P=0.027)., Conclusion: CA IX is marker of poor prognosis in premenopausal breast cancer patients and it is an independent predictor of survival in patients with one to three positive lymph nodes. As all these patients received locoregional radiation therapy, CA IX may be associated with resistance to radiotherapy.

There are > 1.15 million cases of breast cancer diagnosed worldwide annually, and it is the second leading cause of cancer death in the European Union. The optimum management of patients with breast cancer requires accurate prognostic and predictive factors. At present, only a small number of such factors are used clinically. DNA microarrays have the potential to measure the expression of tens of thousands of genes simultaneously. Recent preliminary findings suggest that DNA microarray-based gene expression profiling can provide powerful and independent prognostic information in patients with newly diagnosed breast cancer. As well as providing prognostic information, emerging results suggest that DNA microarrays can also be used for predicting response or resistance to treatment, especially to neoadjuvant chemotherapy. Prior to clinical application, these preliminary findings must be validated using large-scale prospective studies. This article reviews these advances and also examines the role of DNA microarrays in reducing the number of patients who receive inappropriate chemotherapy. The most recent data supporting the integration of various publicly available data sets is also reviewed in detail.