Journal: Research Square

Article Title: Lineage specific extracellular vesicle-associated protein biomarkers for the early detection of high grade serous ovarian cancer

doi: 10.21203/rs.3.rs-2814022/v1

Figure Lengend Snippet: Enrichment and characterization of cell line and tissue explant EVs. a) Surgical resections of healthy FT or tumor tissues were minced and used to initiate short-term tissue explants (cultured for 24 h) followed by collection of the conditioned media and processed by differential ultracentrifugation to enrich for EVs. Likewise, conditioned media from the FT and ovarian cancer cell lines shown was collected and processed. Created with BioRender.com b) Representative NTA data. c) Sixty (60) EV particles were imaged, and their size was measured for representative samples by TEM at x30K magnification. d) Shown are representative SP-IRIS and fluorescence (ExoView) data of FT tissue explant derived EVs displaying the common tetraspanins observed with cell-line derived EVs: CD9 (blue), CD63 (pink) and CD81 (green).

Article Snippet: For NTA data and IHC expression score analysis, GraphPad Prism version 8 was used for performing unpaired Mann-Whitney t-tests and calculating p-values to compare between the samples.

Techniques: Cell Culture, Fluorescence, Derivative Assay

Journal: EBioMedicine

Article Title: MELK promotes Endometrial carcinoma progression via activating mTOR signaling pathway

doi: 10.1016/j.ebiom.2019.102609

Figure Lengend Snippet: MELK is overexpressed and correlates with poor prognosis in EC. a. mRNA expression levels of MELK in 548 EC tissue samples and 35 non-tumor tissue samples in TCGA database (left panel); the expression levels of MELK in 91 EC and 12 nontumor tissue samples in the GEO database (middle); the MELK levels in the 22 paired samples in TCGA (right). Values are means ± SD, ** p < 0.01 (student's t -test). b. MELK expression in histological types. The median, upper and lower quartiles were plotted, and the whiskers that extend from each box indicate the range values that were outside of the intra-quartile range, * p < 0.05, ** p < 0.01(student's t -test). c. Differential mRNA expression of MELK by the histological grade (left), and FIGO stages (right) in TCGA database. The median, upper and lower quartiles were plotted, and the whiskers that extend from each box indicate the range values that were outside of the intra-quartile range, * p < 0.05(student's t -test). d. Overall survival Kaplan–Meier (left) and disease-free survival Kaplan–Meier (right) estimates in relation to MELK alterations in TCGA; the patients were ordered by MELK expression, the first 30% patients as the low-expression group ( n = 160), and the last 30% as the high-expression group ( n = 160). e. Representative cases of MELK expression in normal tissues and at different histological grades in the tissue microarray of EC. Scale bar, 50 μm. f. The proportion of MELK-expressing cells assessed by blinded IHC analysis in normal tissue samples ( n = 40) and EC samples ( n = 360), ** p < 0.01 (chi-square test). g. Comparisons of overall survival (OS) between MELK low- ( n = 114) and high- expression ( n = 129) groups of patients with EC. Some staining was omitted because of the stripping of the slide. h. Comparisons of the OS between MELK low- and high-expression groups in the histological grade 2 and 3 cohort. i. Comparisons of the OS between MELK low- and high-expression groups in the FIGO stage Ⅱ-Ⅳ cohort.

Article Snippet: Scale bar, 50 μm. f. The proportion of MELK-expressing cells assessed by blinded IHC analysis in normal tissue samples ( n = 40) and EC samples ( n = 360), ** p < 0.01 (chi-square test). g. Comparisons of overall survival (OS) between MELK low- ( n = 114) and high- expression ( n = 129) groups of patients with EC.

Techniques: Expressing, Microarray, Staining, Stripping Membranes

Journal: Journal of Pathology Informatics

Article Title: Integrating and validating automated digital imaging analysis of estrogen receptor immunohistochemistry in a fully digital workflow for clinical use

doi: 10.1016/j.jpi.2022.100122

Figure Lengend Snippet: Automated workflow of ER IHC digital imaging analysis (DIA) using Visiopharm coupled with whole slide images (WSI) in the Philips Image Management System (IMS). (A) Downloading case metadata for 1 ER IHC slide in Philips Imaging Managing System. (B) Streaming whole slide image of ER IHC slide by opening its metadata file in Visiopharm. (C) Selecting tumor detection and ER digital imaging analysis algorithms in Visiopharm app center. (D) Analyzing ER results using automated ER digital imaging analsysis algorithm.

Article Snippet: Automated workflow of ER IHC digital imaging analysis (DIA) using Visiopharm coupled with whole slide images (WSI) in the Philips Image Management System (IMS). (A) Downloading case metadata for 1 ER IHC slide in Philips Imaging Managing System. (B) Streaming whole slide image of ER IHC slide by opening its metadata file in Visiopharm. (C) Selecting tumor detection and ER digital imaging analysis algorithms in Visiopharm app center. (D) Analyzing ER results using automated ER digital imaging analsysis algorithm.

Techniques: Imaging