Machine learning survival models trained on clinical data to identify high risk patients with hormone responsive HER2 negative breast cancer.

For endocrine-positive Her2 negative breast cancer patients at an early stage, the benefit of adding chemotherapy to adjuvant endocrine therapy is not still confirmed. Several genomic tests are available on the market but are very expensive. Therefore, there is the urgent need to explore novel reliable and less expensive prognostic tools in this setting.

Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy.

To date, some artificial intelligence (AI) methods have exploited Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to identify finer tumor properties as potential earlier indicators of pathological Complete Response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). However, they work either for sagittal or axial MRI protocols. More flexible AI tools, to be used easily in clinical practice across various institutions in accordance with its own imaging acquisition protocol, are required.

A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients.

In breast cancer patients, an accurate detection of the axillary lymph node metastasis status is essential for reducing distant metastasis occurrence probabilities. In case of patients resulted negative at both clinical and instrumental examination, the nodal status is commonly evaluated performing the sentinel lymph-node biopsy, that is a time-consuming and expensive intraoperative procedure for the sentinel lymph-node (SLN) status assessment. The aim of this study was to predict the nodal status of 142 clinically negative breast cancer patients by means of both clinical and radiomic features extracted from primary breast tumor ultrasound images acquired at diagnosis.

Prognostic Value of NLRP3 Inflammasome and TLR4 Expression in Breast Cancer Patients.

Inflammasome complexes play a pivotal role in different cancer types. NOD-like receptor protein 3 (NLRP3) inflammasome is one of the most well-studied inflammasomes. Activation of the NLRP3 inflammasome induces abnormal secretion of soluble cytokines, generating advantageous inflammatory surroundings that support tumor growth.

The role of rapid on site evaluation on touch imprint cytology and brushing during conventional bronchoscopy.

Background: The increase in immunohistochemical and molecular predictive tests in lung cancer requires new strategies for managing small samples taken during bronchoscopic procedures. The value of Rapid On Site Evaluation (ROSE) during conventional bronchoscopic procedures on endobronchial neoplasms in optimizing small biopsies and cytologlogical tissue specimens for diagnostic testing, and ancillary studies was evaluated.

Method: ROSE on touch imprint cytology (TIC) and brushing was performed on 690 consecutive cases of patients undergoing biopsies, using fiber optic bronchoscopy.

Predicting of Sentinel Lymph Node Status in Breast Cancer Patients with Clinically Negative Nodes: A Validation Study.

In the absence of lymph node abnormalities detectable on clinical examination or imaging, the guidelines provide for the dissection of the first axillary draining lymph nodes during surgery. It is not always possible to arrive at surgery without diagnostic doubts, and machine learning algorithms can support clinical decisions. The web calculator CancerMath (CM) allows you to estimate the probability of having positive lymph nodes valued on the basis of tumor size, age, histologic type, grading, expression of estrogen receptor, and progesterone receptor.

Radiomic Analysis in Contrast-Enhanced Spectral Mammography for Predicting Breast Cancer Histological Outcome.

Contrast-Enhanced Spectral Mammography (CESM) is a recently introduced mammographic method with characteristics particularly suitable for breast cancer radiomic analysis. This work aims to evaluate radiomic features for predicting histological outcome and two cancer molecular subtypes, namely Human Epidermal growth factor Receptor 2 (HER2)-positive and triple-negative. From 52 patients, 68 lesions were identified and confirmed on histological examination.

Biomarker phenotyping drives clinical management in axillary sentinel node: A retrospective study on women with primary breast cancer in 2002.

The current study examined if cancer biomarker phenotyping could predict the clinical/pathological status of axillary nodes in women with primary breast cancer. Primary breast cancers from 2002 were analyzed for tumor size, estrogen receptor (ER), progesterone receptor (PgR), Ki-67MIB expression and Her2/neu amplification. Relationships between the clinical and pathological status of the axilla and the biological subtypes classification were analyzed using univariate, multivariate and regression tree analysis.

Tumor Infiltrating Lymphocytes and NHERF1 Impact on Prognosis of Breast Cancer Patients.

Background: Breast cancer (BC) is a heterogeneous disease, and patients with apparently similar clinicopathological characteristics in clinical practice show different outcome. This study evaluated in primary BCs and in the subgroup of the triple-negative breast cancers (TNBCs) the level of tumor infiltrating lymphocytes (TILs), Na/H exchanger regulatory factor 1 (NHERF1) expression, and their association respect to the clinical outcome of patients.

Material And Methods: NHERF1 expression was assessed by immunohistochemistry in 338 BC samples; the analysis of TILs was examined using hematoxylin and eosin stained slides, according to International TILs Working Group 2014.

NHERF1 and tumor microenvironment: a new scene in invasive breast carcinoma.

Background: Tumor microenvironment (TME) includes many factors such as tumor associated inflammatory cells, vessels, and lymphocytes, as well as different signaling molecules and extracellular matrix components. These aspects can be de-regulated and consequently lead to a worsening of cancer progression. In recent years an association between the scaffolding protein Na/H exchanger regulatory factor 1 (NHERF1) and tumor microenvironment changes in breast cancer (BC) has been reported.