Relationship Between Clustered Ring Nonmass Enhancement of Breast MRI and Prognostic Molecular Biomarkers in Breast Cancer

BackgroundClustered ring enhancement (CRE) of breast MRI is a lexicon of nonmass enhancement (NME) representing tendency of breast cancer and molecular biomarkers are predictors of response to therapy. The purpose of this study was to retrospectively determine the relationship between CRE NME and prognostic molecular biomarkers in breast cancer.MethodsRetrospective analysis of 58 breast lesions in 56 female patients between July 2013 and December 2018 was performed in our institution. Cases with MRI reporting NME in the text were collected via searching the report database. The patterns of enhancement including CRE on breast MRI were reviewed by a radiologist blinded to pathology report. The pathological results and expression of molecular biomarkers were collected. Univariate analysis was applied to evaluate the association between MRI NME imaging features, pathological and IHC stain findings.Results58 Breast lesions were pathologically proven breast carcinoma, and 31 lesions with CRE and 27 lesions without CRE on breast MRI. The expression of estrogen receptor (ER) (P=0.017) and progesterone receptor (PR) (P=0.017) was significantly lower in lesions with CRE compared with those without CRE. The expression of Ki-67 (≥ 25%) was significantly higher in lesions with CRE(P=0.046). The lesions with CRE have a lower expression ratio of ER (50.71 ± 45.39% vs. 74.26 ± 33.59%, p= 0.028).ConclusionOur results indicated that lesions with CRE may possess different features from those without CRE in molecular expression. They tend to bear a more aggressive biological behavior.

Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC): A Bioinformatics Approach

Esophageal carcinoma (EsC) is a member of the cancer group that occurs in the esophagus; globally, it is known as one of the fatal malignancies. In this study, we used gene expression analysis to identify molecular biomarkers to propose therapeutic targets for the development of novel drugs. We consider EsC associated four different microarray datasets from the gene expression omnibus database. Statistical analysis is performed using R language and identified a total of 1083 differentially expressed genes (DEGs) in which 380 are overexpressed and 703 are underexpressed. The functional study is performed with the identified DEGs to screen significant Gene Ontology (GO) terms and associated pathways using the Database for Annotation, Visualization, and Integrated Discovery repository (DAVID). The analysis revealed that the overexpressed DEGs are principally connected with the protein export, axon guidance pathway, and the downexpressed DEGs are principally connected with the L13a-mediated translational silencing of ceruloplasmin expression, formation of a pool of free 40S subunits pathway. The STRING database used to collect protein-protein interaction (PPI) network information and visualize it with the Cytoscape software. We found 10 hub genes from the PPI network considering three methods in which the interleukin 6 (IL6) gene is the top in all methods. From the PPI, we found that identified clusters are associated with the complex I biogenesis, ubiquitination and proteasome degradation, signaling by interleukins, and Notch-HLH transcription pathway. The identified biomarkers and pathways may play an important role in the future for developing drugs for the EsC.

Molecular Biomarkers for Diagnosis of Oral Cancer: An Overview

Oral cancer is one of the six leading cancers in the world and is a constant threat to the health sector in developing countries as well as developed ones. Late presentation, due to lack of awareness and invasive incisional biopsy is the crucial factor for this. Nowadays, scientists are trying to find out an easy and reliable method of early diagnosis of oral cancer and molecular biomarkers might be very helpful for that. This review was aimed to evaluate the published literature on molecular biomarkers which are related to oral cancer. For this, advanced searching was applied by specific keywords in PubMed-Medline resource database and found 12466 publications were clinical trials on humans. Then after applying all inclusion criteria, 19 articles were included finally in the review. This paper uncovered that recognition of biomarkers will be useful for the early detection of oral cancer and their prognosis after treatment. We can suggest that p53, EGFR, miR-34a, miR-143 estimation is important to decide the conceivable risk of oral malignant growth advancement in the speculated oral lesion and after the curative procedure EGFR, Podoplanin and miR-21can aid us regarding the prognosis of patient.International Journal of Human and Health Sciences Vol. 06 No. 01 January’22 Page: 11-16

On the Road to Accurate Protein Biomarkers in Prostate Cancer Diagnosis and Prognosis: Current Status and Future Advances

Prostate cancer (PC) is a leading cause of morbidity and mortality among men worldwide. Molecular biomarkers work in conjunction with existing clinicopathologic tools to help physicians decide who to biopsy, re-biopsy, treat, or re-treat. The past decade has witnessed the commercialization of multiple PC protein biomarkers with improved performance, remarkable progress in proteomic technologies for global discovery and targeted validation of novel protein biomarkers from clinical specimens, and the emergence of novel, promising PC protein biomarkers. In this review, we summarize these advances and discuss the challenges and potential solutions for identifying and validating clinically useful protein biomarkers in PC diagnosis and prognosis. The identification of multi-protein biomarkers with high sensitivity and specificity, as well as their integration with clinicopathologic parameters, imaging, and other molecular biomarkers, bodes well for optimal personalized management of PC patients.

Molecular Biomarkers for Adrenoleukodystrophy: An Unmet Need

X-linked adrenoleukodystrophy (ALD) is an inherited progressive neurometabolic disease caused by mutations in the ABCD1 gene and the accumulation of very long-chain fatty acids in plasma and tissues. Patients present with heterogeneous clinical manifestations which can include adrenal insufficiency, myelopathy, and/or cerebral demyelination. In the absence of a genotype-phenotype correlation, the clinical outcome of an individual cannot be predicted and currently there are no molecular markers available to quantify disease severity. Therefore, there is an unmet clinical need for sensitive biomarkers to monitor and/or predict disease progression and evaluate therapy efficacy. The increasing amount of biological sample repositories (‘biobanking’) as well as the introduction of newborn screening creates a unique opportunity for identification and evaluation of new or existing biomarkers. Here we summarize and review the many studies that have been performed to identify and improve knowledge surrounding candidate molecular biomarkers for ALD. We also highlight several shortcomings of ALD biomarker studies, which often include a limited sample size, no collection of longitudinal data, and no validation of findings in an external cohort. Nonetheless, these studies have generated a list of interesting biomarker candidates and this review aspires to direct future biomarker research.