LC-MS/MS-Based Quantitative Proteomics Analysis of Different Stages of Non-Small-Cell Lung Cancer

Advances in mass spectrometry imaging for spatial cancer metabolomics

Mass spectrometry (MS) has become a central technique in cancer research. The ability to analyze various types of biomolecules in complex biological matrices makes it well suited for understanding biochemical alterations associated with disease progression. Different biological samples, including serum, urine, saliva, and tissues have been successfully analyzed using mass spectrometry. In particular, spatial metabolomics using MS imaging (MSI) allows the direct visualization of metabolite distributions in tissues, thus enabling in-depth understanding of cancer-associated biochemical changes within specific structures. In recent years, MSI studies have been increasingly used to uncover metabolic reprogramming associated with cancer development, enabling the discovery of key biomarkers with potential for cancer diagnostics. In this review, we aim to cover the basic principles of MSI experiments for the nonspecialists, including fundamentals, the sample preparation process, the evolution of the mass spectrometry techniques used, and data analysis strategies. We also review MSI advances associated with cancer research in the last 5 years, including spatial lipidomics and glycomics, the adoption of three-dimensional and multimodal imaging MSI approaches, and the implementation of artificial intelligence/machine learning in MSI-based cancer studies. The adoption of MSI in clinical research and for single-cell metabolomics is also discussed. Spatially resolved studies on other small molecule metabolites such as amino acids, polyamines, and nucleotides/nucleosides will not be discussed in the context.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Prognostic Biomarkers Based on Proteomic Technology in COPD: A Recent Review

Chronic obstructive pulmonary disease (COPD) is a common heterogeneous respiratory disease which is characterized by persistent and incompletely reversible airflow limitation. Due to the heterogeneity and phenotypic complexity of COPD, traditional diagnostic methods provide limited information and pose a great challenge to clinical management. In recent years, with the development of omics technologies, proteomics, metabolomics, transcriptomics, etc., have been widely used in the study of COPD, providing great help to discover new biomarkers and elucidate the complex mechanisms of COPD. In this review, we summarize the prognostic biomarkers of COPD based on proteomic studies in recent years and evaluate their association with COPD prognosis. Finally, we present the prospects and challenges of COPD prognostic-related studies. This review is expected to provide cutting-edge evidence in prognostic evaluation of clinical patients with COPD and to inform future proteomic studies on prognostic biomarkers of COPD.

Label-free quantitative proteomics reveals aberrant expression levels of LRG, C9, FN, A1AT and AGP1 in the plasma of patients with colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the major causes of cancer-related death worldwide. Although commercial biomarkers of CRC are currently available, they are still lacking in terms of sensitivity and specificity; thus, searching for reliable blood-based biomarkers are important for the primary screening of CRC.

METHODS

Plasma samples of patients with non-metastatic (NM) and metastatic (M) CRC and healthy controls were fractionated using MARS-14 immunoaffinity chromatography. The flow-through and elute fractions representing low- and high-abundant proteins, respectively, were analyzed by label-free quantitative proteomics mass spectrometry. The functional analysis of the proteins with greater than 1.5-fold differential expression level between the CRC and the healthy control groups were analyzed for their biological processes and molecular functions. In addition, the levels of plasma proteins showing large alterations in CRC patients were confirmed by immunoblotting using two independent cohorts. Moreover, receiver operating characteristic (ROC) curve analysis was performed for individual and combinations of biomarker candidates so as to evaluate the diagnostic performance of biomarker candidates.

RESULTS

From 163 refined identifications, five proteins were up-regulated and two proteins were down-regulated in NM-CRC while eight proteins were up-regulated and three proteins were down-regulated in M-CRC, respectively. Altered plasma proteins in NM-CRC were mainly involved in complement activation, while those in M-CRC were clustered in acute-phase response, complement activation, and inflammatory response. Results from the study- and validation-cohorts indicate that the levels of leucine-rich alpha-2-glycoprotein-1(LRG), complement component C9 (C9), alpha-1-acid glycoprotein 1 (AGP1), and alpha-1-antitrypsin (A1AT) were statistically increased, while fibronectin (FN) level was statistically decreased in CRC patients compared to healthy controls, with most alterations found in a metastatic stage-dependent manner. ROC analysis revealed that FN exhibited the best diagnostic performance to discriminate CRC patients and healthy controls while AGP1 showed the best discrimination between the disease stages in both cohorts. The combined biomarker candidates, FN + A1AT + AGP1, exhibited perfect discriminatory power to discriminate between the CRC population and healthy controls whereas LRG + A1AT + AGP1 was likely to be the best panel to discriminate the metastatic stages in both cohorts.

CONCLUSIONS

This study identified and quantified distinct plasma proteome profiles of CRC patients. Selected CRC biomarker candidates including FN, LRG, C9, A1AT, and AGP1 may be further applied for screening larger cohorts including disease groups from other types of cancer or other diseases.

Anti-Metastatic Effect of Pyruvate Dehydrogenase Kinase 4 Inhibition in Bladder Cancer via the ERK, SRC, and JNK Pathways

Bladder cancer is a common global cancer with a high percentage of metastases and high mortality rate. Thus, it is necessary to identify new biomarkers that can be helpful in diagnosis. Pyruvate dehydrogenase kinase 4 (PDK4) belongs to the PDK family and plays an important role in glucose utilization in living organisms. In the present study, we evaluated the role of PDK4 in bladder cancer and its related protein changes. First, we observed elevated PDK4 expression in high-grade bladder cancers. To screen for changes in PDK4-related proteins in bladder cancer, we performed a comparative proteomic analysis using PDK4 knockdown cells. In bladder cancer cell lines, PDK4 silencing resulted in a lower rate of cell migration and invasion. In addition, a PDK4 knockdown xenograft model showed reduced bladder cancer growth in nude mice. Based on our results, PDK4 plays a critical role in the metastasis and growth of bladder cancer cells through changes in ERK, SRC, and JNK.

Proteomic and Phosphoproteomic Analyses Reveal the Oncogenic Role of PTK7-NDRG1 Axis in Non-small-cell Lung Cancer Cell Resistance to AZD9291

Epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) are the most important chemotherapeutics for non-small-cell lung cancer (NSCLC) therapy. The resistance to EGFR-TKIs is one of the biggest obstacles to NSCLC outcome. In this study, taking advantage of phospho- and proximal proteomic techniques, we analyzed the network rearrangement in cell lines responding to AZD9291 treatment and found that cell-cell adhesion was dramatically enhanced in AZD9291-resistant cells. Further analysis revealed that protein tyrosine kinase 7 (PTK7) expression was significantly elevated. Knockdown or overexpression assays showed that PTK7 played a critical role in improving cell adhesion, which enhanced drug resistance. Because PTK7 is a membrane-localized pseudokinase, the proximal labeling probe BirA* was fused to reveal PTK7-interacting proteins. We found that PTK7 interacted with and stabilized NDRG1, which is located predominantly adjacent to adherens junctions. Downregulation of PTK7 or NDRG1 eliminated the resistance of H1975-resistant (H1975-R) and PC9-resistant (PC9-R) cells to AZD9291, suggesting that the PTK7-NDRG1 axis might be a potential target to eliminate the EGFR-TKI resistance during NSCLC therapy.

The Role of Genomics and Proteomics in Lung Cancer Early Detection and Treatment

Lung cancer is the leading cause of cancer-related death worldwide, with non-small-cell lung cancer (NSCLC) being the primary type. Unfortunately, it is often diagnosed at advanced stages, when therapy leaves patients with a dismal prognosis. Despite the advances in genomics and proteomics in the past decade, leading to progress in developing tools for early diagnosis, targeted therapies have shown promising results; however, the 5-year survival of NSCLC patients is only about 15%. Low-dose computed tomography or chest X-ray are the main types of screening tools. Lung cancer patients without specific, actionable mutations are currently treated with conventional therapies, such as platinum-based chemotherapy; however, resistances and relapses often occur in these patients. More noninvasive, inexpensive, and safer diagnostic methods based on novel biomarkers for NSCLC are of paramount importance. In the current review, we summarize genomic and proteomic biomarkers utilized for the early detection and treatment of NSCLC. We further discuss future opportunities to improve biomarkers for early detection and the effective treatment of NSCLC.

A Cell Differentiation Trajectory-Related Signature for Predicting the Prognosis of Lung Adenocarcinoma

Objective

To screen the cell differentiation trajectory-related genes and build a cell differentiation trajectory-related signature for predicting the prognosis of lung adenocarcinoma (LUAD).

Methods

LUAD single cell mRNA expression profile, TCGA-LUAD transcriptome data were obtained from GEO and TCGA databases. Single-cell RNA-seq data were used for cell clustering and pseudotime analysis after dimensionality reduction analysis, and the cell differentiation trajectory-related genes were acquired after differential expression analysis conducted between the main branches. Then, the consensus clustering analysis was carried out on TCGA-LUAD samples, and the GSEA analysis was performed, then the differences on the expression levels of immune checkpoint genes and immunotherapy response were compared among clusters. The prognostic model was constructed, and the GSE42127 dataset was used to validate. A nomogram evaluation model was used to predict prognosis.

Results

Two subsets with distinct differentiation states were found after cell differentiation trajectory analysis. TCGA-LUAD samples were divided into two cell differentiation trajectory-related gene-based clusters, GSEA found that cluster 1 was significantly related to 20 pathways, cluster 2 was significantly enriched in three pathways, and it was also shown that clusters could better predict immune checkpoint gene expression and immunotherapy response. A six cell differentiation-related genes-based prognostic signature was constructed, and the patients in the high-risk group had poorer prognosis than those in the low-risk group. Moreover, a nomogram was constructed based on the prognostic signature and clinicopathological features, and this nomogram had strong predictive performance and high accuracy.

Conclusion

The cell differentiation-related signature and the prognostic nomogram could accurately predict survival.

Applications of Tandem Mass Spectrometry (MS/MS) in Protein Analysis for Biomedical Research

Mass Spectrometry (MS) allows the analysis of proteins and peptides through a variety of methods, such as Electrospray Ionization-Mass Spectrometry (ESI-MS) or Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry (MALDI-MS). These methods allow identification of the mass of a protein or a peptide as intact molecules or the identification of a protein through peptide-mass fingerprinting generated upon enzymatic digestion. Tandem mass spectrometry (MS/MS) allows the fragmentation of proteins and peptides to determine the amino acid sequence of proteins (top-down and middle-down proteomics) and peptides (bottom-up proteomics). Furthermore, tandem mass spectrometry also allows the identification of post-translational modifications (PTMs) of proteins and peptides. Here, we discuss the application of MS/MS in biomedical research, indicating specific examples for the identification of proteins or peptides and their PTMs as relevant biomarkers for diagnostic and therapy.

Components of the Lectin Pathway of Complement in Solid Tumour Cancers

The complement system is an important branch of the humoral innate immune response that can be activated via three distinct pathways (classical, alternative, lectin), contributing to keeping/restoring homeostasis. It can also interact with cellular innate immunity and with components of acquired immunity. Cross-talk between the complement system and other enzyme-dependent cascades makes it a more influential defence system, but on the other hand, over- or chronic activation can be harmful. This short review is focused on the dual role of the lectin pathway of complement activation in human solid tumour cancers, including those of the female reproductive system, lung, and alimentary tract, with emphasis on the aforementioned cross-talk.

Neutrophils in cancer carcinogenesis and metastasis

In recent years, neutrophils have attracted increasing attention because of their cancer-promoting effects. An elevated neutrophil-to-lymphocyte ratio is considered a prognostic indicator for patients with cancer. Neutrophils are no longer regarded as innate immune cells with a single function, let alone bystanders in the pathological process of cancer. Their diversity and plasticity are being increasingly recognized. This review summarizes previous studies assessing the roles and mechanisms of neutrophils in cancer initiation, progression, metastasis and relapse. Although the findings are controversial, the fact that neutrophils play a dual role in promoting and suppressing cancer is undeniable. The plasticity of neutrophils allows them to adapt to different cancer microenvironments and exert different effects on cancer. Given the findings from our own research, we propose a reasonable hypothesis that neutrophils may be reprogrammed into a cancer-promoting state in the cancer microenvironment. This new perspective indicates that neutrophil reprogramming in the course of cancer treatment is a problem worthy of attention. Preventing or reversing the reprogramming of neutrophils may be a potential strategy for adjuvant cancer therapy.

A Serum Metabolomic Study Reveals Changes in Metabolites During the Treatment of Lung Cancer-Bearing Mice with Anlotinib

Background

Anlotinib is a vascular endothelial growth factor receptor tyrosine kinase inhibitor recommended for the treatment of advanced lung cancer patients after at least two previous systemic chemotherapies. Currently, many patients with lung cancer do not respond well to anlotinib treatment. Therefore, the aim of this metabolomic study was to determine the internal mechanism of anlotinib action at the molecular level and to identify the potential biomarkers and pathways associated with the therapeutic effects of anlotinib.

Methods

A total of 20 male nude mice were randomly divided into 2 groups and treated with anlotinib or physiological saline. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was performed to analyze the serum samples and determine the differential metabolites and pathways between anlotinib and control groups.

Results

We observed significant differences between the anlotinib and control groups, and 13 endogenous differential metabolites and 5 potential metabolic pathways were identified. Glyoxylate and dicarboxylate metabolism, tryptophan metabolism, glycine, serine and threonine metabolism, phenylalanine metabolism and valine, leucine and isoleucine biosynthesis were the most important pathways regulated by anlotinib in vivo. Notably, these 5 differential pathways were highly associated with the TCA cycle, which is important in the proliferation and apoptosis of cancer cells.

Conclusion

This serum metabolomic study revealed distinct metabolic profiles in lung cancer-bearing mice treated with anlotinib and identified differential metabolites and pathways between the anlotinib and control groups, which may provide new ideas for the clinical application of anlotinib.