A retrospective validation of CanAssist Breast in European early-stage breast cancer patient cohort.

CanAssist Breast (CAB), a prognostic test uses immunohistochemistry (IHC) approach coupled with artificial intelligence-based machine learning algorithm for prognosis of early-stage hormone-receptor positive, HER2/neu negative breast cancer patients. It was developed and validated in an Indian cohort. Here we report the first blinded validation of CAB in a multi-country European patient cohort.

Validation of CanAssist Breast immunohistochemistry biomarkers on an automated platform and its applicability in tissue microarray.

CanAssist Breast (CAB) is a prognostic test for early-stage hormone receptor-positive invasive breast cancer. The test involves performing immunohistochemical (IHC) analysis for five biomarkers, namely CD44, ABCC4, ABCC11, N-cadherin, and pan-cadherin. In addition to IHC grading information, three clinical features, i.

Comparison of breast cancer prognostic tests CanAssist Breast and Oncotype DX.

Background: CanAssist Breast (CAB) is a prognostic test for early stage hormone receptor-positive (HR+), human epidermal growth factor receptor 2 negative (HER2-) breast cancer patients, validated on Indian and Caucasian patients. The 21-gene signature Oncotype DX (ODX) is the most widely used commercially available breast cancer prognostic test. In the current study, risk stratification of CAB is compared with that done with ODX along with the respective outcomes of these patients.

Androgen Receptor mRNA levels determine the prognosis in triple-negative breast cancer patients.

Background: Anti-Androgen Receptor (AR) therapy holds promise for a subset of AR expressing triple-negative breast cancer (TNBC) patients. However, current AR assays are suboptimal in detecting the dynamic range of AR expression, contributing to its controversial role in TNBC disease prognosis. This study is aimed at evaluating the feasibility of qRT-PCR to sensitively and robustly detect AR mRNA levels for prognostication.

Analytical validation of CanAssist-Breast: an immunohistochemistry based prognostic test for hormone receptor positive breast cancer patients.

Background: CanAssist-Breast is an immunohistochemistry based test that predicts risk of distant recurrence in early-stage hormone receptor positive breast cancer patients within first five years of diagnosis. Immunohistochemistry gradings for 5 biomarkers (CD44, ABCC4, ABCC11, N-Cadherin and pan-Cadherins) and 3 clinical parameters (tumor size, tumor grade and node status) of 298 patient cohort were used to develop a machine learning based statistical algorithm. The algorithm generates a risk score based on which patients are stratified into two groups, low- or high-risk for recurrence.

Clinical validation of an immunohistochemistry-based CanAssist-Breast test for distant recurrence prediction in hormone receptor-positive breast cancer patients.

CanAssist-Breast (CAB) is an immunohistochemistry (IHC)-based prognostic test for early-stage Hormone Receptor (HR+)-positive breast cancer patients. CAB uses a Support Vector Machine (SVM) trained algorithm which utilizes expression levels of five biomarkers (CD44, ABCC4, ABCC11, N-Cadherin, and Pan-Cadherin) and three clinical parameters such as tumor size, grade, and node status as inputs to generate a risk score and categorizes patients as low- or high-risk for distant recurrence within 5 years of diagnosis. In this study, we present clinical validation of CAB.

Development of a Novel Proteomic Risk-Classifier for Prognostication of Patients With Early-Stage Hormone Receptor-Positive Breast Cancer.

Use of proteomic strategies to identify a risk classifier that estimates probability of distant recurrence in early-stage hormone receptor (HR)-positive breast cancer is relevant to physiological cellular function and therefore to intrinsic tumor biology. We used a 298-sample retrospective training set to develop an immunohistochemistry-based novel risk classifier called CanAssist-Breast (CAB) which combines 5 prognostically relevant biomarkers and 3 clinico-pathological parameters to arrive at probability of distant recurrence within 5 years from diagnosis. Five selected biomarkers, namely, CD44, ABCC4, ABCC11, N-cadherin, and pan-cadherin, were chosen based on their role in tumor metastasis.

High prevalence of maternal hypothyroidism despite adequate iodine status in Indian pregnant women in the first trimester.

Background: Iodine requirements are increased during pregnancy to maintain maternal and fetal euthyroidism. There have been recent improvements in iodized salt coverage in India, but whether iodized salt is sufficient to sustain iodine requirements during pregnancy remains uncertain. Our aims were to measure thyroid status in first trimester pregnant women in southern India and assess potential determinants of thyroid function, including iodine status, thyroid autoimmunity, dietary patterns, body weight, and anemia.

EGFR targeting monoclonal antibody combines with an mTOR inhibitor and potentiates tumor inhibition by acting on complementary signaling hubs.

Nimotuzumab, an anti-epidermal growth factor receptor (anti-EGFR) monoclonal antibody, has been used extensively in many solid tumors and confers significant survival advantage. The antibody has limited skin toxicity and is generally well tolerated. Similar to other anti-EGFR therapies, patients may relapse a few months after treatment.

Nimotuzumab with chemoradiation confers a survival advantage in treatment-naïve head and neck tumors over expressing EGFR.

Head and neck cancer associated with the chewing of betel preparations, including tobacco, is common to South East Asia. We report a Phase IIB study in which ninety-two treatment naïve patients with advanced squamous cell carcinoma received standard therapy with or without an anti-Epidermal Growth Factor Receptor (EGFR) monoclonal antibody (Nimotuzumab). In pretreatment samples, the tissue expression of ErbB family proteins and downstream molecules, including their association with clinical response and survival.