Deregulation of cell adhesion molecules is associated with progression and poor outcomes in endometrial cancer: Analysis of The Cancer Genome Atlas data

It is time to implement molecular classification in endometrial cancer

A huge effort has been done in redefining endometrial cancer (EC) risk classes in the last decade. However, known prognostic factors (FIGO staging and grading, biomolecular classification and ESMO-ESGO-ESTRO risk classes stratification) are not able to predict outcomes and especially recurrences. Biomolecular classification has helped in re-classifying patients for a more appropriate adjuvant treatment and clinical studies suggest that currently used molecular classification improves the risk assessment of women with EC, however, it does not clearly explain differences in recurrence profiles. Furthermore, a lack of evidence appears in EC guidelines. Here, we summarize the main concepts why molecular classification is not enough in the management of endometrial cancer, by highlighting some promising innovative examples in scientific literature studies with a clinical potential significant impact.

Elevated of NDUFA4L2 expression in colon adenocarcinoma is correlated with an unfavorable prognosis and increased immune cell infiltration

Background

Colon adenocarcinoma (COAD) is a prevalent malignancy worldwide, yet, its underlying pathogenesis and genetic characteristics are still unclear. Previous studies have suggested that NADH dehydrogenase 1 alpha subcomplex subunit 4-like 2 (NDUFA4L2) may affect tumor progression across various cancers. However, this effect on COAD has rarely been reported. Thus, this study investigated NDUFA4L2's prognostic and diagnostic relevance and explored its potential connection with immune cell infiltration in COAD.

Methods

To achieve this, RNA sequencing data from Cancer Genome Atlas (TCGA) was analyzed to assess NDUFA4L2's prognostic value in COAD, and factors relevant to the prognosis of COAD, including NDUFA4L2, were scrutinized using Kaplan-Meier analyses as well as univariate and multivariate Cox regression. A nomogram model was created to project prognosis based on the results of multivariate Cox analysis. Furthermore, gene set enrichment analysis (GSEA) was employed to pinpoint key NDUFA4L2-related pathways, and single-sample GSEA (ssGSEA) on TCGA data was employed to investigate the connections of NDUFA4L2 with cancer immune infiltrations.

Results

Our findings revealed significant associations of high NDUFA4L2 expression with poor overall survival, progression-free interval, and disease-specific survival of COAD patients. GSEA indicated close links of NDUFA4L2 with several signaling pathways implicated in tumorigenesis, including extracellular matrix receptor interaction, the intestinal immune network for immunoglobulin A production, natural killer (NK) cell-mediated cytotoxicity, pathways in cancer, cell adhesion molecules, mitogen-activated protein kinase signaling pathway, Hedgehog signaling pathway, transforming growth factor beta signaling pathway, and chemokine signaling pathway. Additionally, ssGSEA identified a positive link between increased NDUFA4L2 expression and higher infiltration degree of various immune cells, such as immature dendritic cells, macrophages, NK cells and dendritic cells.

Conclusions

Collectively, our findings demonstrate the association of increased NDUFA4L2 expression with adverse prognosis and heightened immune cell infiltration in COAD patients.

Comprehending the Proteomic Landscape of Ovarian Cancer: A Road to the Discovery of Disease Biomarkers

Despite recent technological advancements allowing the characterization of cancers at a molecular level along with biomarkers for cancer diagnosis, the management of ovarian cancers (OC) remains challenging. Proteins assume functions encoded by the genome and the complete set of proteins, termed the proteome, reflects the health state. Comprehending the circulatory proteomic profiles for OC subtypes, therefore, has the potential to reveal biomarkers with clinical utility concerning early diagnosis or to predict response to specific therapies. Furthermore, characterization of the proteomic landscape of tumor-derived tissue, cell lines, and PDX models has led to the molecular stratification of patient groups, with implications for personalized therapy and management of drug resistance. Here, we review single and multiple marker panels that have been identified through proteomic investigations of patient sera, effusions, and other biospecimens. We discuss their clinical utility and implementation into clinical practice.

Large-Scale Proteomic Analysis of Follicular Lymphoma Reveals Extensive Remodeling of Cell Adhesion Pathway and Identifies Hub Proteins Related to the Lymphomagenesis

Simple Summary

Follicular lymphoma represents the major subtype of indolent B-cell non-Hodgkin lymphomas, ranging from about 20 to 30% of all B-NHLs cases in western countries. Yet, the global proteome profile of follicular lymphoma remains largely undocumented; thus, we aimed to employ for the first time a comprehensive proteomic analysis to outline its molecular landscape. A total of 15 lymphoma fine-needle aspiration biopsy samples and 14 controls were evaluated by label-free quantitative proteomics. Among the 7673 proteins identified in our dataset, 1186 proteins were differentially expressed between lymphoma and control samples. Importantly, dysregulated proteins were enriched in biological processes such as B-cell receptor signaling pathway, cellular adhesion molecules pathway, or membrane trafficking. Additionally, we identified several novel hub proteins related to lymphomagenesis. To summarize, we have determined the molecular characteristics of follicular lymphoma and discovered proteins which may hold potential for biomarkers or therapeutic targets.

Abstract

Follicular lymphoma (FL) represents the major subtype of indolent B-cell non-Hodgkin lymphomas (B-NHLs) and results from the malignant transformation of mature B-cells in lymphoid organs. Although gene expression and genomic studies have identified multiple disease driving gene aberrations, only a few proteomic studies focused on the protein level. The present work aimed to examine the proteomic profiles of follicular lymphoma vs. normal B-cells obtained by fine-needle aspiration biopsy (FNAB) to gain deep insight into the most perturbed pathway of FL. The cells of interest were purified by magnetic-activated cell sorting (MACS). High-throughput proteomic profiling was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and allowed to identify of 6724 proteins in at least 75% of each group of samples. The ‘Total Protein Approach’ (TPA) was applied to the absolute quantification of proteins in this study. We identified 1186 differentially abundant proteins (DAPs) between FL and control samples, causing an extensive remodeling of several molecular pathways, including the B-cell receptor signaling pathway, cellular adhesion molecules, and PPAR pathway. Additionally, the construction of protein–protein interactions networks (PPINs) and identification of hub proteins allowed us to indicate the key player proteins for FL pathology. Finally, ICAM1, CD9, and CD79B protein expression was validated in an independent cohort by flow cytometry (FCM), and the results were consistent with the mass spectrometry (MS) data.