Proteomic Analysis of Pre-Invasive Serous Lesions of the Endometrium and Fallopian Tube Reveals Their Metastatic Potential

Identification of Potentially Novel Molecular Targets of Endometrial Cancer Using a Non-Biased Proteomic Approach

The present study was aimed at identifying novel proteins in endometrial cancer (EC), employing proteomic analysis of tissues obtained after surgery. A differential MS-based proteomic analysis was conducted from whole tissues dissected from biopsies from post-menopausal women, histologically confirmed as endometrial cancer (two endometrioid and two serous; n = 4) or normal atrophic endometrium (n = 4), providing 888 differentially expressed proteins with 246 of these previously documented elsewhere as expressed in EC and 372 proteins not previously demonstrated to be expressed in EC but associated with other types of cancer. Additionally, 33 proteins not recorded previously in PubMed as being expressed in any forms of cancer were also identified, with only 26 of these proteins having a publication associated with their expression patterns or putative functions. The putative functions of the 26 proteins (GRN, APP, HEXA, CST3, CAD, QARS, SIAE, WARS, MYH8, CLTB, GOLIM4, SCARB2, BOD1L1, C14orf142, C9orf142, CCDC13, CNPY4, FAM169A, HN1L, PIGT, PLCL1, PMFBP1, SARS2, SCPEP1, SLC25A24 and ZC3H4) in other tissues point towards and provide a basis for further investigation of these previously unrecognised novel EC proteins. The developmental biology, disease, extracellular matrix, homeostatic, immune, metabolic (both RNA and protein), programmed cell death, signal transduction, molecular transport, transcriptional networks and as yet uncharacterised pathways indicate that these proteins are potentially involved in endometrial carcinogenesis and thus may be important in EC diagnosis, prognostication and treatment and thus are worthy of further investigation.

Endometrial cancer diagnostic and prognostic algorithms based on proteomics, metabolomics, and clinical data: a systematic review

Endometrial cancer is the most common gynaecological malignancy in developed countries. Over 382,000 new cases were diagnosed worldwide in 2018, and its incidence and mortality are constantly rising due to longer life expectancy and life style factors including obesity. Two major improvements are needed in the management of patients with endometrial cancer, i.e., the development of non/minimally invasive tools for diagnostics and prognostics, which are currently missing. Diagnostic tools are needed to manage the increasing number of women at risk of developing the disease. Prognostic tools are necessary to stratify patients according to their risk of recurrence pre-preoperatively, to advise and plan the most appropriate treatment and avoid over/under-treatment. Biomarkers derived from proteomics and metabolomics, especially when derived from non/minimally-invasively collected body fluids, can serve to develop such prognostic and diagnostic tools, and the purpose of the present review is to explore the current research in this topic. We first provide a brief description of the technologies, the computational pipelines for data analyses and then we provide a systematic review of all published studies using proteomics and/or metabolomics for diagnostic and prognostic biomarker discovery in endometrial cancer. Finally, conclusions and recommendations for future studies are also given.

Proteomic Profiling of Fallopian Tube-Derived Extracellular Vesicles Using a Microfluidic Tissue-on-Chip System

The human fallopian tube epithelium (hFTE) is the site of fertilization, early embryo development, and the origin of most high-grade serous ovarian cancers (HGSOCs). Little is known about the content and functions of hFTE-derived small extracellular vesicles (sEVs) due to the limitations of biomaterials and proper culture methods. We have established a microfluidic platform to culture hFTE for EV collection with adequate yield for mass spectrometry-based proteomic profiling, and reported 295 common hFTE sEV proteins for the first time. These proteins are associated with exocytosis, neutrophil degranulation, and wound healing, and some are crucial for fertilization processes. In addition, by correlating sEV protein profiles with hFTE tissue transcripts characterized using GeoMx® Cancer Transcriptome Atlas, spatial transcriptomics analysis revealed cell-type-specific transcripts of hFTE that encode sEVs proteins, among which, FLNA, TUBB, JUP, and FLNC were differentially expressed in secretory cells, the precursor cells for HGSOC. Our study provides insights into the establishment of the baseline proteomic profile of sEVs derived from hFTE tissue, and its correlation with hFTE lineage-specific transcripts, which can be used to evaluate whether the fallopian tube shifts its sEV cargo during ovarian cancer carcinogenesis and the role of sEV proteins in fallopian tube reproductive functions.

A Protocol for the Acquisition of Comprehensive Proteomics Data from Single Cases Using Formalin-Fixed Paraffin Embedded Sections

The molecular analysis of small or rare patient tissue samples is challenging and often limited by available technologies and resources, such as reliable antibodies against a protein of interest. Although targeted approaches provide some insight, here, we describe the workflow of two complementary mass spectrometry approaches, which provide a more comprehensive and non-biased analysis of the molecular features of the tissue of interest. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) generates spatial intensity maps of molecular features, which can be easily correlated with histology. Additionally, liquid chromatography tandem mass spectrometry (LC-MS/MS) can identify and quantify proteins of interest from a consecutive section of the same tissue. Here, we present data from concurrent precancerous lesions from the endometrium and fallopian tube of a single patient. Using this complementary approach, we monitored the abundance of hundreds of proteins within the precancerous and neighboring healthy regions. The method described here represents a useful tool to maximize the number of molecular data acquired from small sample sizes or even from a single case. Our initial data are indicative of a migratory phenotype in these lesions and warrant further research into their malignant capabilities.