No abstract

Multicenter standardization study may accelerate the implementation of ALK testing protocols across a country/region. Our data support the use of an appropriately validated IHC assay to screen for ALK+ lung cancers.

Almost all genomic studies of breast cancer have focused on well-established tumours because it is technically challenging to study the earliest mutational events occurring in human breast epithelial cells. To address this we created a unique dataset of epithelial samples ductoscopically obtained from ducts leading to breast carcinomas and matched samples from ducts on the opposite side of the nipple. Here, we demonstrate that perturbations in mRNA abundance, with increasing proximity to tumour, cannot be explained by copy number aberrations. Rather, we find a possibility of field cancerization surrounding the primary tumour by constructing a classifier that evaluates where epithelial samples were obtained relative to a tumour (cross-validated micro-averaged AUC = 0.74). We implement a spectral co-clustering algorithm to define biclusters. Relating to over-represented bicluster pathways, we further validate two genes with tissue microarrays and in vitro experiments. We highlight evidence suggesting that bicluster perturbation occurs early in tumour development.

BackgroundBreast cancer is the most common malignancy among women worldwide in terms of incidence and mortality. About 10% of North American women will be diagnosed with breast cancer during their lifetime and 20% of those will die of the disease. Breast cancer is a heterogeneous disease and biomarkers able to correctly classify patients into prognostic groups are needed to better tailor treatment options and improve outcomes. One powerful method used for biomarker discovery is sample screening with mass spectrometry, as it allows direct comparison of protein expression between normal and pathological states. The purpose of this study was to use a systematic and objective method to identify biomarkers with possible prognostic value in breast cancer patients, particularly in identifying cases most likely to have lymph node metastasis and to validate their prognostic ability using breast cancer tissue microarrays.Methods and FindingsDifferential proteomic analyses were employed to identify candidate biomarkers in primary breast cancer patients. These analyses identified decorin (DCN) and endoplasmin (HSP90B1) which play important roles regulating the tumour microenvironment and in pathways related to tumorigenesis. This study indicates that high expression of Decorin is associated with lymph node metastasis (p<0.001), higher number of positive lymph nodes (p<0.0001) and worse overall survival (p = 0.01). High expression of HSP90B1 is associated with distant metastasis (p<0.0001) and decreased overall survival (p<0.0001) these patients also appear to benefit significantly from hormonal treatment.ConclusionsUsing quantitative proteomic profiling of primary breast cancers, two new promising prognostic and predictive markers were found to identify patients with worse survival. In addition HSP90B1 appears to identify a group of patients with distant metastasis with otherwise good prognostic features.

Breast cancer is a heterogeneous disease, which comprises several molecular and genetic subtypes, each with characteristic clinicobiologic behavior and imaging patterns. Traditional classification of breast cancer is based on the histopathologic features but offers limited prognostic value. Novel molecular characterization of breast cancer with cellular markers has allowed a new classification that offers prognostic value, with predictive categories of disease aggressiveness. These molecular signatures also open the door to personalized therapeutic options, with new receptor-targeted therapies. For example, invasive cancer subtypes such as the luminal A and B subtypes show better prognosis and response to hormone receptor-targeted therapies compared with the triple-negative subtypes; on the other hand, triple-negative tumors respond better than luminal tumors to chemotherapy. Tumors that display amplification of the oncogene ERBB2 (also known as the HER2/neu oncogene) respond to drugs directed against this oncogene, such as trastuzumab. The imaging aspects of tumors correlate with molecular subgroups, as well as other pathologic features such as nuclear grade. Smooth tumor margins at mammography may be suggestive of a triple-negative breast cancer, and a human epidermal growth factor receptor 2 (HER2)-positive tumor is characteristically a spiculated mass with calcifications. Low-grade ductal carcinoma in situ (DCIS) is better detected with mammography, although magnetic resonance (MR) imaging may allow better characterization of high-grade DCIS. MR imaging diffusion sequences show higher values for the apparent diffusion coefficient for triple-negative and HER2-positive subtypes, compared with luminal A and B tumors. MR imaging is also a useful tool in the prediction of tumor response after chemotherapy, especially for triple-negative and HER2-positive subtypes.

Bone is a preferred site for breast cancer metastasis, causing pain, fractures, spinal cord compressions, and hypercalcemia, all of which can significantly diminish the patient's quality of life. We identified CCN3 as a novel factor that is highly expressed in bone metastatic breast cancer cells from a xenograft mouse model and in bone metastatic lesions from patients with breast cancer. We demonstrate that CCN3 overexpression enhances the ability of weakly bone metastatic breast cancer cells to colonize and grow in the bone without altering their growth in the mammary fat pad. We further demonstrated that human recombinant CCN3 inhibits osteoblast differentiation from primary bone marrow cultures, leading to a higher receptor activator of NF-B ligand (RANKL)/osteoprotegerin (OPG) ratio. In conjunction with its ability to impair osteoblast differentiation, we uncovered a novel role for CCN3 in promoting osteoclast differentiation from RANKL-primed monocyte precursors. CCN3 exerts its proosteoclastogenic effects by promoting calcium oscillations and nuclear factor of activated T cells c1 (NFATc1) nuclear translocation. Together, these results demonstrate that CCN3 regulates the differentiation of bone resident cells to create a resorptive environment that promotes the formation of osteolytic breast cancer metastases. Bone is the preferred site for breast cancer metastasis. 1,2Although patients with bone metastasis display better overall survival relative to patients with visceral metastases, their quality of life can be significantly diminished due to pain, fractures, spinal cord compressions, and hypercalcemia. Given the pivotal role of the osteoclast in bone breakdown associated with osteolytic lesions, bisphosphonates (a class of drugs that inhibit osteoclast-dependent bone resorption) are routinely given to patients with breast cancer bone metastases. 4 However, significant research efforts are now focused on the identification and development of targeted therapeutics to further enhance the management of breast cancer metastasis. 5,6

Lapatinib was well tolerated but like other EGFR- and HER2-targeted agents in advanced HRPC failed to show significant antitumor activity even in this very early stage hormonally untreated population.

Abl interactor 1 (Abi1) is an adaptor protein involved in cell migration. Previous in vitro work suggested that Abi1 is a regulator of breast cancer proliferation, migration, and invasion. In the present study, we explore the expression of Abi1 and its downstream effector phospho-Akt (p-Akt) in a series of breast cancers and correlate their expression with clinicopathological and survival data. Using tissue microarrays, 988 patients with invasive breast carcinoma were evaluated by immunohistochemistry. Statistical correlation was performed to determine associations between Abi1 and p-Akt expression and standard breast clinicopathological factors. The prognostic value of Abi1 and p-Akt for disease-free (DFS) and overall survival (OS) was also evaluated. Abi1 expression was demonstrated in 33.7% (314/933) of invasive carcinomas, while p-Akt was expressed in 46.7% (441/944). There was a significant association between Abi1 and p-Akt expression (P=0.001). Abi1 expression showed significant positive correlation with older age at diagnosis and the Ki67 index. Most importantly, it was demonstrated to be an independent predictor of both DFS and OS (HR = 1.6 and 1.5, P<0.001, respectively). There was no association between p-Akt expression and survival. To the best of our knowledge, this is the first study evaluating Abi1 expression in a large group of breast cancers. Our analysis demonstrated that tumors expressing high levels of Abi1 are significantly associated with early recurrence and worse survival on multivariate analysis. This suggests that Abi1 expression has potential as a molecular marker to refine outcome prediction in breast cancer patients.