A large-scale targeted proteomics of plasma extracellular vesicles shows utility for prognosis prediction subtyping in colorectal cancer

Personalized prognostic model for colorectal cancer in the era of precision medicine: a dynamic approach based on real-world data

BACKGROUND

Predicting individual prognosis is required for patients with colorectal cancer in the era of precision medicine. However, this may be challenging for the conventional survival analysis such as the Cox proportional hazards model. This study aims to develop a personalized prognostic prediction that incorporates longitudinal data to improve predictions for colorectal cancer patients.

METHODS

Patients with advanced or recurrent colorectal cancer, who received treatment at Kyoto University Hospital between April 2015 and December 2021, were retrospectively analyzed. The Joint model is one of the dynamic prediction models. Using longitudinal clinical data, a carcinoembryonic antigen (CEA) prediction equation was developed for each patient. Additionally, a personalized prognostic prediction model was created using the Joint model. The prediction accuracy of the Joint model was compared with one of the Cox proportional hazards model.

RESULTS

Among the 1010 patients, 614 patients were enrolled. The median frequency of tumor marker measurement (per patient) was 20 times (range: 3-117 times). CEA values could be predicted accurately and the Pearson's correlation coefficient between measured CEA and predicted CEA was 0.931. In the Joint model, the significant prognostic factors were baseline age (HR, 1.039; 95% CI, 1.025-1.054), poor-differentiated tumor (HR, 2.600; 95% CI 1.446-4.675) and log2 (predicted CEA) (HR, 1.551; 95% CI 1.488-1.617). The areas under the curve at 2, 3, 4, and 5 were significantly higher for the Joint model than for the Cox proportional hazards model, respectively.

CONCLUSION

The Joint model may accurately predict personalized prognosis that reflects changes in longitudinal tumor marker values.

Prognostic value of extracellular vesicles in colorectal cancer: a systematic review and meta-analysis

OBJECTIVE

Extracellular vesicles (EVs) are prognostic factors in colorectal cancer (CRC). This study aims to evaluate the prognostic value of EVs CRC.

METHODS

Clinical studies that directly investigated the association between EVs in different kinds of body fluids of CRC patients and patient prognosis were included by searching the PubMed, Web of Science, ClinicalTrials, and CENTRAL databases. The associations between single biomarkers, molecular panels, and EVs count with overall survival (OS), disease-free survival (DFS), and recurrence-free survival (RFS) were analyzed. Heterogeneity was assessed using the I2 statistic, with a random-effects model applied when I2 > 30% and a fixed-effects model when I2 ≤ 30%.

RESULTS

A total of 56 studies involving 5,985 patients were included. All included studies detected EVs in blood. Univariate analysis revealed an association between EVs single-biomarkers and OS (pHR = 2.07, 95% CI: 1.73-2.73) and DFS (pHR = 2.20, 95% CI: 1.46-2.79). Additionally, univariate analysis revealed an association between molecular-panels in EVs and OS (pHR = 3.67, 95% CI: 2.51-5.36) and RFS (pHR = 3.97, 95% CI: 1.57-10.08). Moreover, an association was observed between a EVs count and OS (pHR = 1.87, 95% CI: 1.40-2.49). On the basis of the results of the meta-regression and subgroup analyses, the subgroups of EVs and the disease stage of CRC patients are key factors contributing to the heterogeneity in the associations between EVs single-biomarkers and OS.

CONCLUSION

This study provides compelling evidence that EVs from blood hold prognostic value in CRC.

Quantitative Proteomics and Molecular Mechanisms of Non-Hodgkin Lymphoma Mice Treated with Incomptine A, Part II

Background/Objectives: Incomptine A (IA) has cytotoxic activity in non-Hodgkin lymphoma (NHL) cancer cell lines. Its effects on U-937 cells include induction of apoptosis, production of reactive oxygen species, and inhibition of glycolytic enzymes. We examined the altered protein levels present in the lymph nodes of an in vivo mouse model. Methods: We induced an in vivo model with Balb/c mice with U-937 cells and treated it with IA or methotrexate, as well as healthy mice. We determined expressed proteins by TMT based on the LC-MS/MS method (Data are available via ProteomeXchange with identifier PXD060392) and a molecular docking study targeting 15 deregulated proteins. We developed analyses through the KEGG, Reactome, and Gene Ontology databases. Results: A total of 2717 proteins from the axillary and inguinal lymph nodes were analyzed and compared with healthy mice. Of 412 differentially expressed proteins, 132 were overexpressed (FC ≥ 1.5) and 117 were underexpressed (FC ≤ 0.67). This altered expression was associated with 20 significantly enriched processes, including chromatin remodeling, transcription, translation, metabolic and energetic processes, oxidative phosphorylation, glycolysis/gluconeogenesis, cell proliferation, cytoskeletal organization, and with cell death with necroptosis. Conclusions: We confirmed the previously observed dose-dependent effect of IA as a secondary metabolite with important potential as an anticancer agent for the treatment of NHL, showing that the type of drug or the anatomical location influences the response to treatment. The IA promises to be a likely safer and more effective treatment to improve outcomes, reduce toxicities, and improve survival in patients with NHL, initially targeting histones and transcription factors that will affect cell death proteins.

A Proteomic Examination of Plasma Extracellular Vesicles Across Colorectal Cancer Stages Uncovers Biological Insights That Potentially Improve Prognosis

BACKGROUND

Recent advancements in understanding plasma extracellular vesicles (EVs) and their role in disease biology have provided additional unique insights into the study of Colorectal Cancer (CRC).

METHODS

This study aimed to gain biological insights into disease progression from plasma-derived extracellular vesicle proteomic profiles of 80 patients (20 from each CRC stage I-IV) against 20 healthy age- and sex-matched controls using a high-resolution SWATH-MS proteomics with a reproducible centrifugation method to isolate plasma EVs.

RESULTS

We applied the High-Stringency Human Proteome Project (HPP) guidelines for SWATH-MS analysis, which refined our initial EV protein identification from 1362 proteins (10,993 peptides) to a more reliable and confident subset of 853 proteins (6231 peptides). In early-stage CRC, we identified 11 plasma EV proteins with differential expression between patients and healthy controls (three up-regulated and eight down-regulated), many of which are involved in key cancer hallmarks. Additionally, within the same cohort, we analysed EV proteins associated with tumour recurrence to identify potential prognostic indicators for CRC. A subset of up-regulated proteins associated with extracellular vesicle formation (GDI1, NSF, and TMED9) and the down-regulation of TSG101 suggest that micro-metastasis may have occurred earlier than previously anticipated.

DISCUSSION

By employing stringent proteomic analysis and a robust SWATH-MS approach, we identified dysregulated EV proteins that potentially indicate early-stage CRC and predict recurrence risk, including proteins involved in metabolism, cytoskeletal remodelling, and immune response. While our findings underline discrepancies with other studies due to differing isolation and stringency parameters, they provide valuable insights into the complexity of the EV proteome, emphasising the need for standardised protocols and larger, well-controlled studies to validate potential biomarkers.

Immune capture and protein profiling of small extracellular vesicles from human plasma

Extracellular vesicles (EVs), the key players in inter-cellular communication, are produced by all cell types and are present in all body fluids. Analysis of the proteome content is an important approach in structural and functional studies of these vesicles. EVs circulating in human plasma are heterogeneous in size, cellular origin, and functions. This heterogeneity and the potential presence of contamination with plasma components such as lipoprotein particles and soluble plasma proteins represent a challenge in profiling the proteome of EV subsets by mass spectrometry. An immunocapture strategy prior to mass spectrometry may be used to isolate a homogeneous subpopulation of small EVs (sEV) with a specific endocytic origin from plasma or other biofluids. Immunocapture selectively separates EV subpopulations in biofluids based on the presence of a unique protein carried on the vesicle surface. The advantages and disadvantages of EV immune capture as a preparative step for mass spectrometry are discussed.

A proteomic classifier panel for early screening of colorectal cancer: a case control study

BACKGROUND

Diagnosis of colorectal cancer (CRC) during early stages can greatly improve patient outcome. Although technical advances in the field of genomics and proteomics have identified a number of candidate biomarkers for non-invasive screening and diagnosis, developing more sensitive and specific methods with improved cost-effectiveness and patient compliance has tremendous potential to help combat the disease.

METHODS

We enrolled three cohorts of 479 subjects, including 226 CRC cases, 197 healthy controls, and 56 advanced precancerous lesions (APC). In the discovery cohort, we used quantitative mass spectrometry to measure the expression profile of plasma proteins and applied machine-learning to select candidate proteins. We then developed a targeted mass spectrometry assay to measure plasma concentrations of seven proteins and a logistic regression classifier to distinguish CRC from healthy subjects. The classifier was further validated using two independent cohorts.

RESULTS

The seven-protein panel consisted of leucine rich alpha-2-glycoprotein 1 (LRG1), complement C9 (C9), insulin-like growth factor binding protein 2 (IGFBP2), carnosine dipeptidase 1 (CNDP1), inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3), serpin family A member 1 (SERPINA1), and alpha-1-acid glycoprotein 1 (ORM1). The panel classified CRC and healthy subjects with high accuracy, since the area under curve (AUC) of the training and testing cohort reached 0.954 and 0.958. The AUC of the two independent validation cohorts was 0.905 and 0.909. In one validation cohort, the panel had an overall sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 89.9%, 81.8%, 89.2%, and 82.9%, respectively. In another blinded validation cohort, the panel classified CRC from healthy subjects with a sensitivity of 81.5%, specificity of 97.9%, and overall accuracy of 92.0%. Finally, the panel was able to detect APC with a sensitivity of 49%.

CONCLUSIONS

This seven-protein classifier is a clear improvement compared to previously published blood-based protein biomarkers for detecting early-stage CRC, and is of translational potential to develop into a clinically useful assay.

Comprehensive Overview the Role of Glycosylation of Extracellular Vesicles in Cancers

Extracellular vesicles (EVs) are membranous structures secreted by various cells carrying diverse biomolecules. Recent advancements in EV glycosylation research have underscored their crucial role in cancer. This review provides a global overview of EV glycosylation research, covering aspects such as specialized techniques for isolating and characterizing EV glycosylation, advances on how glycosylation affects the biogenesis and uptake of EVs, and the involvement of EV glycosylation in intracellular protein expression, cellular metastasis, intercellular interactions, and potential applications in immunotherapy. Furthermore, through an extensive literature review, we explore recent advances in EV glycosylation research in the context of cancer, with a focus on lung, colorectal, liver, pancreatic, breast, ovarian, prostate, and melanoma cancers. The primary objective of this review is to provide a comprehensive update for researchers, whether they are seasoned experts in the field of EVs or newcomers, aiding them in exploring new avenues and gaining a deeper understanding of EV glycosylation mechanisms. This heightened comprehension not only enhances researchers' knowledge of the pathogenic mechanisms of EV glycosylation but also paves the way for innovative cancer diagnostic and therapeutic strategies.

ORM1 promotes tumor progression of kidney renal clear cell carcinoma (KIRC) through CALR-mediated apoptosis

Kidney renal clear cell carcinoma (KIRC) is the most prevalent type of kidney cancer and causes thousands of deaths each year. The prognosis for KIRC is poor. One critical factor is that the mechanism beneath KIRC is unclear. ORM1 is a reactant to acute inflammation. In this study, we demonstrated that methylation of ORM1 promoter was low and ORM1 was expressed significantly higher in KIRC. KIRC with higher ORM1 expression exhibited worse survival probability. Meanwhile, ORM1 was expressed higher in KIRC cell lines. When ORM1 was knocked down, cell proliferation ability was inhibited potently compared to the NC control. Cell migration as well as invasion ability were also suppressed dramatically. At molecular level, the expression of active caspase-3 and Bax was upregulated in ORM1-KD group while Bcl-2 downregulated. Moreover, CALR decreased following ORM1-KD and rescued expression of CALR increased Bcl-2 level but reduced the level of cleaved caspase-3 and Bax. Consistently, the apoptotic rate of 786-O and Caki-2 cells was upregulated in ORM1-KD but downregulated after CALR overexpression. The activity of caspase-3 was also regulated by ORM1-KD. In addition, the inhibition rate of sorafenib was enhanced in ORM1 KD group but reduced after overexpression of ORM1. Conclusively, ORM1 is clinically associated with progression of KIRC and regulates cell proliferation, migration, invasion, and apoptosis in KIRC. Moreover, ORM1 affects the efficiency of sorafenib in KIRC and regulates caspase-3 mediated cascades response through CALR molecule. This study provides us a new way to recognize the development and progression in KIRC.

Integrating Proteomics and Lipidomics for Evaluating the Risk of Breast Cancer Progression: A Pilot Study

Metastasis is a serious and often life-threatening condition, representing the leading cause of death among women with breast cancer (BC). Although the current clinical classification of BC is well-established, the addition of minimally invasive laboratory tests based on peripheral blood biomarkers that reflect pathological changes in the body is of utmost importance. In the current study, the serum proteome and lipidome profiles for 50 BC patients with (25) and without (25) metastasis were studied. Targeted proteomic analysis for concertation measurements of 125 proteins in the serum was performed via liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) using the BAK 125 kit (MRM Proteomics Inc., Victoria, BC, Canada). Untargeted label-free lipidomic analysis was performed using liquid chromatography coupled to tandem mass-spectrometry (LC-MS/MS), in both positive and negative ion modes. Finally, 87 serum proteins and 295 lipids were quantified and showed a moderate correlation with tumor grade, histological and biological subtypes, and the number of lymph node metastases. Two highly accurate classifiers that enabled distinguishing between metastatic and non-metastatic BC were developed based on proteomic (accuracy 90%) and lipidomic (accuracy 80%) features. The best classifier (91% sensitivity, 89% specificity, AUC = 0.92) for BC metastasis diagnostics was based on logistic regression and the serum levels of 11 proteins: alpha-2-macroglobulin, coagulation factor XII, adiponectin, leucine-rich alpha-2-glycoprotein, alpha-2-HS-glycoprotein, Ig mu chain C region, apolipoprotein C-IV, carbonic anhydrase 1, apolipoprotein A-II, apolipoprotein C-II and alpha-1-acid glycoprotein 1.

Proteomic Research of Extracellular Vesicles in Clinical Biofluid

Extracellular vesicles (EVs), the lipid bilayer membranous structures of particles, are produced and released from almost all cells, including eukaryotes and prokaryotes. The versatility of EVs has been investigated in various pathologies, including development, coagulation, inflammation, immune response modulation, and cell-cell communication. Proteomics technologies have revolutionized EV studies by enabling high-throughput analysis of their biomolecules to deliver comprehensive identification and quantification with rich structural information (PTMs, proteoforms). Extensive research has highlighted variations in EV cargo depending on vesicle size, origin, disease, and other features. This fact has sparked activities to use EVs for diagnosis and treatment to ultimately achieve clinical translation with recent endeavors summarized and critically reviewed in this publication. Notably, successful application and translation require a constant improvement of methods for sample preparation and analysis and their standardization, both of which are areas of active research. This review summarizes the characteristics, isolation, and identification approaches for EVs and the recent advances in EVs for clinical biofluid analysis to gain novel knowledge by employing proteomics. In addition, the current and predicted future challenges and technical barriers are also reviewed and discussed.