Comprehensive proteomic profiling of serum extracellular vesicles in patients with colorectal liver metastases identifies a signature for non-invasive risk stratification and early-response evaluation

Tumor-derived extracellular vesicle proteins as new biomarkers and targets in precision oncology

Extracellular vesicles (EVs) are important carriers of signaling molecules, such as nucleic acids, proteins, and lipids, and have become a focus of increasing interest due to their numerous physiological and pathological functions. For a long time, most studies on EV components focused on noncoding RNAs; however, in recent years, extracellular vesicle proteins (EVPs) have been found to play important roles in diagnosis, treatment, and drug resistance and thus have been considered favorable biomarkers and therapeutic targets for various tumors. In this review, we describe the general protocols of research on EVPs and summarize their multifaceted roles in precision medicine applications, including cancer diagnosis, dynamic monitoring of therapeutic efficacy, drug resistance research, tumor microenvironment interaction research, and anticancer drug delivery.

The multifaceted role of extracellular vesicles (EVs) in colorectal cancer: metastasis, immune suppression, therapy resistance, and autophagy crosstalk

Extracellular vesicles (EVs) are lipid bilayer structures released by all cells and widely distributed in all biological fluids. EVs are implicated in diverse physiopathological processes by orchestrating cell-cell communication. Colorectal cancer (CRC) is one of the most common cancers worldwide, with metastasis being the leading cause of mortality in CRC patients. EVs contribute significantly to the advancement and spread of CRC by transferring their cargo, which includes lipids, proteins, RNAs, and DNAs, to neighboring or distant cells. Besides, they can serve as non-invasive diagnostic and prognostic biomarkers for early detection of CRC or be harnessed as effective carriers for delivering therapeutic agents. Autophagy is an essential cellular process that serves to remove damaged proteins and organelles by lysosomal degradation to maintain cellular homeostasis. Autophagy and EV release are coordinately activated in tumor cells and share common factors and regulatory mechanisms. Although the significance of autophagy and EVs in cancer is well established, the exact mechanism of their interplay in tumor development is obscure. This review focuses on examining the specific functions of EVs in various aspects of CRC, including progression, metastasis, immune regulation, and therapy resistance. Further, we overview emerging discoveries relevant to autophagy and EVs crosstalk in CRC.

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum, and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1), and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.

A novel machine learning algorithm selects proteome signature to specifically identify cancer exosomes

Non-invasive early cancer diagnosis remains challenging due to the low sensitivity and specificity of current diagnostic approaches. Exosomes are membrane-bound nanovesicles secreted by all cells that contain DNA, RNA, and proteins that are representative of the parent cells. This property, along with the abundance of exosomes in biological fluids makes them compelling candidates as biomarkers. However, a rapid and flexible exosome-based diagnostic method to distinguish human cancers across cancer types in diverse biological fluids is yet to be defined. Here, we describe a novel machine learning-based computational method to distinguish cancers using a panel of proteins associated with exosomes. Employing datasets of exosome proteins from human cell lines, tissue, plasma, serum and urine samples from a variety of cancers, we identify Clathrin Heavy Chain (CLTC), Ezrin, (EZR), Talin-1 (TLN1), Adenylyl cyclase-associated protein 1 (CAP1) and Moesin (MSN) as highly abundant universal biomarkers for exosomes and define three panels of pan-cancer exosome proteins that distinguish cancer exosomes from other exosomes and aid in classifying cancer subtypes employing random forest models. All the models using proteins from plasma, serum, or urine-derived exosomes yield AUROC scores higher than 0.91 and demonstrate superior performance compared to Support Vector Machine, K Nearest Neighbor Classifier and Gaussian Naive Bayes. This study provides a reliable protein biomarker signature associated with cancer exosomes with scalable machine learning capability for a sensitive and specific non-invasive method of cancer diagnosis.

Tumour-derived exosomes in liver metastasis: A Pandora's box

The liver is a common secondary metastasis site of many malignant tumours, such as the colorectum, pancreas, stomach, breast, prostate, and lung cancer. The clinical management of liver metastases is challenging because of their strong heterogeneity, rapid progression, and poor prognosis. Now, exosomes, small membrane vesicles that are 40-160 nm in size, are released by tumour cells, namely, tumour-derived exosomes (TDEs), and are being increasingly studied because they can retain the original characteristics of tumour cells. Cell-cell communication via TDEs is pivotal for liver pre-metastatic niche (PMN) formation and liver metastasis; thus, TDEs can provide a theoretical basis to intensively study the potential mechanisms of liver metastasis and new insights into the diagnosis and treatment of liver metastasis. Here, we systematically review current research progress about the roles and possible regulatory mechanisms of TDE cargos in liver metastasis, focusing on the functions of TDEs in liver PMN formation. In addition, we discuss the clinical utility of TDEs in liver metastasis, including TDEs as potential biomarkers, and therapeutic approaches for future research reference in this field.

Current Applications of Liquid Biopsy in Gastrointestinal Cancer Disease-From Early Cancer Detection to Individualized Cancer Treatment

Worldwide, gastrointestinal (GI) cancers account for a significant amount of cancer-related mortality. Tests that allow an early diagnosis could lead to an improvement in patient survival. Liquid biopsies (LBs) due to their non-invasive nature as well as low risk are the current focus of cancer research and could be a promising tool for early cancer detection. LB involves the sampling of any biological fluid (e.g., blood, urine, saliva) to enrich and analyze the tumor's biological material. LBs can detect tumor-associated components such as circulating tumor DNA (ctDNA), extracellular vesicles (EVs), and circulating tumor cells (CTCs). These components can reflect the status of the disease and can facilitate clinical decisions. LBs offer a unique and new way to assess cancers at all stages of treatment, from cancer screenings to prognosis to management of multidisciplinary therapies. In this review, we will provide insights into the current status of the various types of LBs enabling early detection and monitoring of GI cancers and their use in in vitro diagnostics.

Prognostic circulating proteomic biomarkers in colorectal liver metastases

The liver is the most common site of metastasis in colorectal cancer. Multimodal treatment, including liver resection, is potentially curative and prolongs survival for selected patients with colorectal liver metastases (CRLM). However, the treatment of CRLM remains challenging because recurrence is common, and prognosis varies widely between patients despite curative-intent treatment. Clinicopathological features and tissue-based molecular biomarkers, either alone or in combination, are insufficient for accurate prognostication. As most of the functional information in cells resides in the proteome, circulating proteomic biomarkers may be useful for rationalising the molecular complexities of CRLM and identifying potentially prognostic molecular subtypes. High-throughput proteomics has accelerated a range of applications including protein profiling of liquid biopsies for biomarker discovery. Moreover, these proteomic biomarkers may provide non-invasive prognostic information even before CRLM resection. This review evaluates recently discovered circulating proteomic biomarkers in CRLM. We also highlight some of the challenges and opportunities with translating these discoveries into clinical applications.

Extracellular Vesicles in Colorectal Cancer: From Tumor Growth and Metastasis to Biomarkers and Nanomedications

Colorectal cancer (CRC) is a leading public health concern due to its incidence and high mortality rates, highlighting the requirement of an early diagnosis. Evaluation of circulating extracellular vesicles (EVs) might constitute a noninvasive and reliable approach for CRC detection and for patient follow-up because EVs display the molecular features of the cells they originate. EVs are released by almost all cell types and are mainly categorized as exosomes originating from exocytosis of intraluminal vesicles from multivesicular bodies, ectosomes resulting from outward budding of the plasma membrane and apoptotic bodies' ensuing cell shrinkage. These vesicles play a critical role in intercellular communications during physiological and pathological processes. They facilitate CRC progression and premetastatic niche formation, and they enable transfer of chemotherapy resistance to sensitive cells through the local or remote delivery of their lipid, nucleic acid and protein content. On another note, their stability in the bloodstream, their permeation in tissues and their sheltering of packaged material make engineered EVs suitable vectors for efficient delivery of tracers and therapeutic agents for tumor imaging or treatment. Here, we focus on the physiopathological role of EVs in CRCs, their value in the diagnosis and prognosis and ongoing investigations into therapeutic approaches.