Accurate identification of breast cancer margins in microenvironments of ex-vivo basal and luminal breast cancer tissues using Raman spectroscopy

Better knowledge of the breast tumor microenvironment is required for surgical resection and understanding the processes of tumor development. Raman spectroscopy is a promising tool that can assist in uncovering the molecular basis of disease and provide quantifiable molecular information for diagnosis and treatment evaluation. In this work, eighty-eight frozen breast tissue sections, including forty-four normal and forty-four tumor sections, were mapped in their entirety using a 250-μm-square measurement grid. Two or more smaller regions of interest within each tissue were additionally mapped using a 25 μm-square step size. A deep learning algorithm, convolutional neural network (CNN), was developed to distinguish histopathologic features with-in individual and across multiple tissue sections. Cancerous breast tissue were discriminated from normal breast tissue with 90 % accuracy, 88.8 % sensitivity and 90.8 % specificity with an excellent Area Under the Receiver Operator Curve (AUROC) of 0.96. Features that contributed significantly to the model were identified and used to generate RGB images of the tissue sections. For each grid point (pixel) on a Raman map, color was assigned to intensities at frequencies of 1002 cm-1 (Phenylalanine), 869 cm-1 (Proline, CC stretching of hydroxyproline-collagen assignment, single bond stretching vibrations for the amino acids proline, valine and polysaccharides) and 1309 cm-1 (CH3/CH2 twisting or bending mode of lipids). The Raman images clearly associate with hematoxylin and eosin stained tissue sections and allow clear visualization of boundaries between normal adipose, connective tissue and tumor. We demonstrated that this simple imaging technique allows high-resolution, straightforward molecular interpretation of Raman images. Raman spectroscopy provides rapid, label-free imaging of microscopic features with high accuracy. This method has application as laboratory tool and can assist with intraoperative tissue assessment during Breast Conserving surgery.

Intraoperative Raman Spectroscopy

Surgical excision of brain tumors provides a means of cytoreduction and diagnosis while minimizing neurologic deficit and improving overall survival. Despite advances in functional and three-dimensional stereotactic navigation and intraoperative MRI, delineating tissue in real time with physiologic confirmation is challenging. Raman spectroscopy has potential to be an important modality in the intraoperative evaluation of tissue during surgical resection. In vitro experimental studies have shown that this technique can be used to differentiate normal brain tissue from tissue with infiltrating cancer cells and dense cancerous masses with high specificity, indicating the feasibility of this method for in vivo application.

Ceramide changes in abdominal subcutaneous and visceral adipose tissue among diabetic and nondiabetic patients

BACKGROUND

This study profiles ceramides extracted from visceral and subcutaneous adipose tissue of human subjects by liquid chromatography-mass spectrometry to determine a correlation with status of diabetes and gender.

METHODS

Samples of visceral and abdominal wall subcutaneous adipose tissue (n = 36 and n = 31, respectively) were taken during laparoscopic surgery from 36 patients (14 nondiabetic, 22 diabetic and prediabetic) undergoing bariatric surgery with a body mass index (BMI) >35 kg/m² with ≥1 existing comorbidity or BMI ≥40 kg/m² . Sphingolipids were extracted and analyzed using liquid chromatography-mass spectrometry.

RESULTS

After logarithm 2 conversion, paired analysis of visceral to subcutaneous tissue showed differential accumulation of Cer(d18:1/16:0), Cer(d18:1/18:0), and Cer(d18:1/24:1) in visceral tissue of prediabetic/diabetic female subjects, but not in males. Within-tissue analysis showed higher mean levels of ceramide species linked to insulin resistance, such as Cer(d18:1/18:0) and Cer(d18:1/16:0), in visceral tissue of prediabetic/diabetic patients compared with nondiabetic subjects and higher content of Cer(d18:1/14:0) in subcutaneous tissue of insulin-resistant female patients compared with prediabetic/diabetic males. Statistically significant differences in mean levels of ceramide species between insulin-resistant African American and insulin-resistant Caucasian patients were not evident in visceral or subcutaneous tissue.

CONCLUSIONS

Analysis of ceramides is important for developing a better understanding of biological processes underlying type 2 diabetes, metabolic syndrome, and obesity. Knowledge of the accumulated ceramides/dihydroceramides may reflect on the prelipolytic state that leads the lipotoxic phase of insulin resistance and may shed light on the predisposition to insulin resistance by gender.

Avidin-biotin complex-based capture coating platform for universal Influenza virus immobilization and characterization

Influenza virus mutates quickly and unpredictably creating emerging pathogenic strains that are difficult to detect, diagnose, and characterize. Conventional tools to study and characterize virus, such as next generation sequencing, genome amplification (RT-PCR), and serological antibody testing, are not adequately suited to rapidly mutating pathogens like Influenza virus where the success of infection heavily depends on the phenotypic expression of surface glycoproteins. Bridging the gap between genome and pathogenic expression remains a challenge. Using sialic acid as a universal Influenza virus binding receptor, a novel virus avidin-biotin complex-based capture coating was developed and characterized that may be used to create future diagnostic and interrogation platforms for viable whole Influenza virus. First, fluorescent FITC probe studies were used to optimize coating component concentrations. Then atomic force microscopy (AFM) was used to profile the surface characteristics of the novel capture coating, acquire topographical imaging of Influenza particles immobilized by the coating, and calculate the capture efficiency of the coating (over 90%) for all four representative human Influenza virus strains tested.