Recurrence patterns-analysis from a South Indian breast cancer patient cohort.

Background: The current study analyzes the pattern of recurrence/relapse in breast cancer patients belonging to different receptor subtypes to help enhance therapeutic and surveillance methods.

Methods: This is an observational prospective study of a cohort of 543 patients from South India. Associations between various factors and their significance in relapse were assessed by odds ratio (OR), Chi-square test, and two-sided P value.

The usefulness of CanAssist Breast over Ki67 in breast cancer recurrence risk assessment.

Background: Assessment of Ki67 by immunohistochemistry (IHC) has limited utility in clinical practice owing to analytical validity issues. According to International Ki67 Working Group (IKWG) guidelines, treatment should be guided by a prognostic test in patients expressing intermediate Ki67 range, >5%-<30%. The objective of the study is to compare the prognostic performance of CanAssist Breast (CAB) with that of Ki67 across various Ki67 prognostic groups.

A comparative analysis of recurrence risk predictions in ER+/HER2- early breast cancer using NHS Nottingham Prognostic Index, PREDICT, and CanAssist Breast.

Aims: Clinicians use multi-gene/biomarker prognostic tests and free online tools to optimize treatment in early ER+/HER2- breast cancer. Here we report the comparison of recurrence risk predictions by CanAssist Breast (CAB), Nottingham Prognostic Index (NPI), and PREDICT along with the differences in the performance of these tests across Indian and European cohorts.

Methods: Current study used a retrospective cohort of 1474 patients from Europe, India, and USA.

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.

The usefulness of CanAssist breast in the assessment of recurrence risk in patients of ethnic Indian origin.

Accurate recurrence risk assessment in hormone receptor positive, HER2/neu negative breast cancer is critical to plan precise therapy. CanAssist Breast (CAB) assesses recurrence risk based on tumor biology using artificial intelligence-based approach. We report CAB risk assessment correlating with disease outcomes in multiple clinically high- and low-risk subgroups.

CanAssist Breast Impacting Clinical Treatment Decisions in Early-Stage HR+ Breast Cancer Patients: Indian Scenario.

CanAssist Breast (CAB) has thus far been validated on a retrospective cohort of 1123 patients who are mostly Indians. Distant metastasis-free survival (DMFS) of more than 95% was observed with significant separation ( < 0.0001) between low-risk and high-risk groups.

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.

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.

Generation of multipotential mesendodermal progenitors from mouse embryonic stem cells via sustained Wnt pathway activation.

Pluripotent embryonic stem cells (ESCs) are capable of differentiating into cell types belonging to all three germ layers within the body, which makes them an interesting and intense field of research. Inefficient specific differentiation and contamination with unwanted cell types are the major issues in the use of ESCs in regenerative medicine. Lineage-specific progenitors generated from ESCs could be utilized to circumvent the issue.

Genomic and proteomic characterization of embryonic stem cells.

Stem cell biology, like all areas of cell biology, has been significantly affected by the arrival of the genomics era. The rendering of the human and mouse genome sequences and the development of attendant technologies have made it possible to comprehensively explore embryonic stem cell biology at the molecular level. Recently, there has been emphasis on global characterization of the transcriptome, epigenome, and proteome of embryonic stem cells.

Parathyroid hormone-related peptide is a naturally occurring, protein kinase A-dependent angiogenesis inhibitor.

Angiogenesis is a highly regulated process that results from the sequential actions of naturally occurring stimulators and inhibitors. Here, we show that parathyroid hormone-related peptide, a peptide hormone derived from normal and tumor cells that regulates bone metabolism and vascular tone, is a naturally occurring angiogenesis inhibitor. Parathyroid hormone-related peptide or a ten-amino-acid peptide from its N terminus inhibits endothelial cell migration in vitro and angiogenesis in vivo by activating endothelial cell protein kinase A.