Relationships between mammographic density, tissue microvessel density, and breast biopsy diagnosis

Association between microvessel density (MVD) and tumor characteristics among breast cancer cases (n = 44). (DOC 54 kb

Artificial intelligence in cancer imaging: Clinical challenges and applications

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care

Adjuvant tamoxifen in breast cancer : clinical and preclinical studies on the prediction value of estrogen receptor

Breast cancer (BC) exhibits great heterogeneity at histophatological, clinical and molecular levels. However, the different clinical outcomes in patients with seemingly similar breast cancer have led scientists to search for subgroups or for factors and characteristics related to the tumor or the patient that could anticipate clinical course (prognosis) of disease and/or response to given therapy (prediction). Estrogen receptor (ER) is the first molecule identified that has had great influence on the management of breast cancer. This thesis focuses on the role of ER and its significance in breast cancer. In one study, we compared the potential of ER-positive tamoxifen sensitive cells (MCF-7) versus ER- negative cells (MDA-231) to handle DNA repair, transmit signals from DNA damage, initiate apoptosis, control transmitted signals from the cell cycle and synthesize growth factors and receptors. Genes related to these processes were studied by cDNA microarray. We found that the ER-negative cells were characterized by a higher expression of growth factors and cell cycle regulation components, and improved DNA repair. We explored the long-term pattern of disease recurrence among pre-and post-menopausal patients with primary BC according to ER status. The patients were randomly given tamoxifen versus no systemic therapy. The results showed a reduction of locoregional, distant metastases and breast cancer death in ER-positive patients who received tamoxifen. The pattern of metastases was not different in these two groups. The conclusion was that the differences in term of gene expression appeared mainly to be related to endocrine sensitivity and not metastatic potential. Some more events in the first 5 years in ER-negative patients suggested that ER negativity in some cases is correlated with an increased tumour growth rate. ER had been measured by cytosol assays prior to around 1990 when these assays substituted of immunohistochemical (IHC) assay. However, ER predictive ability of response to tamoxifen has been assessed based on ER measurement by cytosol assays. We compared these two assays in a clinical trial and found a high concordance between the assays and concluded that IHC is as accurate as cytosol assays to predict long term response to adjuvant tamoxifen. The introduction of microarray technique a decade ago already has changed our knowledge of BC but it has some pitfalls that question its potential. In two methodical studies we showed the importance of tissue handling, the effect of heterogeneity of BC and standardization on the result from cDNA microarray. This thesis confirms the importance of ER in BC but also indicates a more complex phenotypic beyond that which can be explained purely by ER content or endocrine sensitivity. Microarray technique can provide useful information besides the traditional one but requires standardization of sample collection, storage, processing, normalization, interpretation of data and requires validation by large studies

Breast dynamic contrast-enhanced-magnetic resonance imaging and radiomics: State of art

Breast cancer represents the most common malignancy in women, being one of the most frequent cause of cancer-related mortality. Ultrasound, mammography, and magnetic resonance imaging (MRI) play a pivotal role in the diagnosis of breast lesions, with different levels of accuracy. Particularly, dynamic contrast-enhanced MRI has shown high diagnostic value in detecting multifocal, multicentric, or contralateral breast cancers. Radiomics is emerging as a promising tool for quantitative tumor evaluation, allowing the extraction of additional quantitative data from radiological imaging acquired with different modalities. Radiomics analysis may provide novel information through the quantification of lesions heterogeneity, that may be relevant in clinical practice for the characterization of breast lesions, prediction of tumor response to systemic therapies and evaluation of prognosis in patients with breast cancers. Several published studies have explored the value of radiomics with good-to-excellent diagnostic and prognostic performances for the evaluation of breast lesions. Particularly, the integrations of radiomics data with other clinical and histopathological parameters have demonstrated to improve the prediction of tumor aggressiveness with high accuracy and provided precise models that will help to guide clinical decisions and patients management. The purpose of this article in to describe the current application of radiomics in breast dynamic contrast-enhanced MRI

Triple-negative breast cancer microenvironments: Molecular and histologic portraits

Triple-negative breast cancer (TNBC), comprised predominantly of the basal-like (BBC) and claudin-low (CLBC) intrinsic subtypes, is a proliferative, invasive disease that accounts for 15-20% of breast cancer cases. Unlike with other breast cancer subtypes, TNBC treatment modalities are generally limited to surgery, radiation, and cytotoxic chemotherapy. Therefore, identification of molecular contributors to TNBC initiation and progression, including signals with relevance to the tumor microenvironment, is important for development of biologically targeted therapies. It is well accepted that the tumor microenvironment, the non-cancerous cells and tissues in proximity to the frank cancer cells, plays a critical role in breast cancer initiation and progression. However, little is known about the evolution of stromal-epithelial communication during breast tumorigenesis, or how specific signaling mediators alter subtype-specific tumor behavior. To this end, this work leveraged a suite of model systems to better understand how specific components of TNBC microenvironments influence tumor phenotypes and stromal-epithelial interactions. Following a literature review in Chapter 1, Chapter 2 describes research that used three-dimensional culture models of a pre-invasive BBC cell line panel, together with novel imaging technology, to evaluate cancer cell-fibroblast interactions during early stages of tumor initiation. Relative to wild-type cells, pre-invasive BBC cells lacking the TP53 tumor suppressor gene exhibited accelerated and unique responses to fibroblast co-culture. In Chapter 3, the role of the immune microenvironment in TNBC progression was evaluated using a novel animal model. Myeloid-specific Glut1 knockout mice were used to demonstrate that alterations in myeloid cell metabolism reduced the inflammatory potential of mammary tissue macrophages (MTMs) and impeded CLBC progression. Chapter 4 leveraged observational studies of human tissue to develop a digital algorithm to identify histologically stained endothelial cells in cancer-adjacent breast. This algorithm will be used in future studies to quantitatively characterize the vascular microenvironment both across breast cancer subtypes, and for TNBCs in particular. Finally, Chapter 5 integrates insights from all three investigations to identify future directions for studies of TNBC microenvironments. This work reveals previously uncharacterized relationships between TNBCs and their associated stromal cells, some of which may represent plausible therapeutic targets for this tumor subtype.Doctor of Philosoph

Zinc transporter HKE4 as a new target in antihormone resistance of breast cancer

Background Oestrogen receptor-positive breast cancers develop resistance to anti-oestrogens by utilising alternative growth factor pathways as observed in our tamoxifen-resistant cell line (TAMR). These include EGFR, IGF1-R and Src signalling as well as increased growth and invasion. Zinc is elevated in breast cancer tissue and has been demonstrated to activate certain growth factor signalling pathways. We have tested the expression level of members of the LIV-1 family of zinc influx transporters and discovered that HKE4 (SLC39A7, ZIP7), previously shown by us capable of increasing the intracellular zinc levels, has increased expression in TAMR. We have therefore investigated whether the development of the more aggressive phenotype observed in our TAMR cells, including activation of these signalling pathways as well as increased growth and invasion, is due to an increase of intracellular zinc and as a direct result of increased expression of HKE4. Methods All nine members of the LIV-1 subfamily of ZIP transporters were measured in our model of tamoxifen-resistant breast cancer using Affymetrix arrays. Zinc-induced activation of growth factor signalling pathway components was investigated by western blot and/or fluorescent microscopy. Short-term (15-min) treatments with 20 μM zinc included ionophore, whereas long-term (hours/days) did not. Recombinant LIV-1 family members with a V5 tag were expressed using pcDNA3.1/V5-His-TOPO vector, and siRNA (Dharmacon smartpools with relevant controls) was used to reduce endogenous expression. Results HKE4 (SLC39A7), a ZIP transporter from the LIV-1 subfamily, was discovered to be elevated in TAMR cells by Affymetrix analysis and confirmed by PCR and western blot. We have observed that our TAMR cells have a twofold increase in intracellular zinc compared with wild-type cells, using the zinc-specific fluorescent dye Newport Green. Short-term zinc treatment of TAMR cells activates the signalling pathways implicated in antihormone-resistant proliferation and is reduced by both the zinc chelator TPEN and the Src kinase inhibitor SU6556. The same effects are observed after longer term (6 days) zinc treatment with additional increases in cell growth and invasion through Matrigel. Since we have previously demonstrated that HKE4 is capable of increasing intracellular zinc in cells and, more recently, that these TAMR have elevated intracellular zinc levels, we have tested the hypothesis that elevated HKE4 expression is directly responsible for the aggressive phenotype observed in our TAMR cells. Reducing HKE4 levels by siRNA demonstrated a role for this molecule in driving the zinc-induced activation of multiple signalling pathways. In the presence of siRNA for HKE4, the previously observed zinc-induced activation of EGFR, Src, and IGF1-R was eradicated and the EGF-stimulated activation was also decreased. Additionally, we have demonstrated the converse by transfecting recombinant HKE4 into wild-type cells and/or treating them with zinc to observe the activation of these signalling pathways and increases in invasive capability. Interestingly, we have observed a similar role of HKE4 in our model of faslodex-resistant breast cancer. Conclusion The presented results propose that HKE4, a member of the LIV-1 subfamily of ZIP transporters, is directly involved in the activation of the aggressive phenotype observed with the development of antihormone resistance, and as such is a potential new target for the prevention of resistance to antihormones in breast cancer progression