The plasma peptides of ovarian cancer

Identification of MORN3 and LLGL2 as novel diagnostic biomarkers for latent tuberculosis infection using machine learning strategies and experimental verification

BACKGROUND

Current diagnostic methods cannot effectively distinguish between latent tuberculosis infection (LTBI) and active tuberculosis (ATB). This study aims to explore novel non-invasive diagnostic biomarkers for LTBI and to elucidate possible molecular mechanisms of LTBI pathogenesis.

METHODS

Three GEO datasets (GSE19439, GSE19444, and GSE62525) were utilized to analyze the differentially expressed genes (DEGs). Functional enrichment studies were then performed on these DEGs. To ascertain potential diagnostic biomarkers, we utilized two different machine learning techniques: LASSO and RF. ROC curves were constructed in both the training and validation datasets to assess the diagnostic efficacy. The expression of identified biomarkers was verified by RT-qPCR in our own Chinese cohort. Using CIBERSORT, we estimated the abundances of 22 immune cell types in LTBI group, and subsequently analyzed the relationship between biomarker expression and immune cell infiltration.

RESULTS

166 DEGs were identified between ATB and LTBI groups, which are primarily associated with immune responses, inflammatory signaling pathways, and infection factors. Following that, 22 candidate diagnostic biomarkers for LTBI were selected in the machine learning process. Three up-regulated genes, MORN3, LLGL2, and IFT140, whose expression levels were not previously reported in TB, were validated using the training and validation cohort datasets. In our own Chinese cohort, we also found that MORN3 and LLGL2 showed good diagnostic effect using RT-qPCR method. Finally, we revealed the specific infiltration features of immune cells in LTBI and observed a notable correlation between potential marker expression and immune cells.

CONCLUSIONS

MORN3 and LLGL2 emerged as candidate diagnostic biomarkers for LTBI, following the elucidation of the key immune cell types involved. Our findings will contribute to providing a potential target for early noninvasive diagnosis of LTBI patients.

Plasma-based proteomic profiling identifies the distinct regulation of proteins in hyperplasia and endometrial cancer

BACKGROUND

Among gynaecological malignancies, endometrial cancer (EC) is the most prevalent type of uterine cancer affecting women. This study explored the proteomic profiles of plasma samples obtained from EC patients, those with hyperplasia (Hy), and a control group (CO). A combination of techniques, such as 2D-DIGE, mass spectrometry, and bioinformatics, including pathway analysis, was used to identify proteins with modified expression levels, biomarkers and their associated metabolic pathways in these groups.

METHODS

Thirty-four patients, categorized into three groups-10 with EC, 12 with Hy, and 12 CO-between the ages of 46 and 75 years old were included in the study. Untargeted proteomic analysis was carried out using two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS).

RESULTS

In all three groups, 114 proteins that were significantly (p ≤ 0.05 and fold change ≥ 1.5) altered were successfully identified using peptide mass fingerprints (PMFs). Compared with those in the control group (CO), the EC samples had 85 differentially expressed proteins (39 upregulated and 46 downregulated), and in the Hy group, 81 proteins were dysregulated (40 upregulated and 41 downregulated) compared to those in the CO group, while 33 proteins exhibited differential regulation (12 upregulated and 21 downregulated) in the EC plasma samples compared to those in the Hy group. Vitamin D binding protein and complement C3 distinguished Hy and EC from CO with the greatest changes in expression. Among the differentially expressed proteins identified, enzymes with catalytic activity represented the largest group (42.9%). In terms of biological processes, most of the proteins were involved in cellular processes (28.8%), followed by metabolic processes (16.7%). STRING analysis for protein interactions revealed that the significantly differentially abundant proteins in the three groups are involved in three main biological processes: signalling of complement and coagulation cascades, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), and plasma lipoprotein assembly, remodelling, and clearance.

CONCLUSION

The identified plasma protein markers have the potential to serve as biomarkers for differentiating between EC and Hy, as well as for early diagnosis and monitoring of cancer progression.

New insights into the genetic loci related to egg weight and age at first egg traits in broiler breeder

Egg weight (EW) and age at first egg (AFE) are economically important traits in breeder chicken production. The genetic basis of these traits, however, is far from understood, especially for broiler breeders. In this study, genetic parameter estimation, genome-wide association analysis, meta-analysis, and selective sweep analysis were carried out to identify genetic loci associated with EW and AFE in 6,842 broiler breeders. The study found that the heritability of EW ranged from 0.42 to 0.44, while the heritability of AFE was estimated at 0.33 in the maternal line. Meta-analysis and selective sweep analysis identified two colocalized regions on GGA4 that significantly influenced EW at 32 wk (EW32W) and at 43 wk (EW43W) with both paternal and maternal lines. The genes AR, YIPF6, and STARD8 were located within the significant region (GGA4: 366.86-575.50 kb), potentially affecting EW through the regulation of follicle development, cell proliferation, and lipid transfer etc. The promising genes LCORL and NCAPG were positioned within the significant region (GGA4:75.35-75.42 Mb), potentially influencing EW through pleiotropic effects on growth and development. Additionally, 3 significant regions were associated with AFE on chromosomes GGA7, GGA19, and GGA27. All of these factors affected the AFE by influencing ovarian development. In our study, the genomic information from both paternal and maternal lines was used to identify genetic regions associated with EW and AFE. Two genomic regions and eight genes were identified as the most likely candidates affecting EW and AFE. These findings contribute to a better understanding of the genetic basis of egg production traits in broiler breeders and provide new insights into future technology development.

The Immune Suppressor IGSF1 as a Potential Target for Cancer Immunotherapy

The development of first-generation immune-checkpoint inhibitors targeting PD-1/PD-L1 and CTLA-4 ushered in a new era in anticancer therapy. Although immune-checkpoint blockade therapies have shown clinical success, a substantial number of patients yet fail to benefit. Many studies are under way to discover next-generation immunotherapeutic targets. Immunoglobulin superfamily member 1 (IGSF1) is a membrane glycoprotein proposed to regulate thyroid function. Despite containing 12 immunoglobin domains, a possible role for IGSF1, in immune response, remains unknown. Here, our studies revealed that IGSF1 is predominantly expressed in tumors but not normal tissues, and increased expression is observed in PD-L1low non-small cell lung cancer (NSCLC) cells as compared with PD-L1high cells. Subsequently, we developed and characterized an IGSF1-specific human monoclonal antibody, WM-A1, that effectively promoted antitumor immunity and overcame the limitations of first-generation immune-checkpoint inhibitors, likely via a distinct mechanism of action. We further demonstrated high WM-A1 efficacy in humanized peripheral blood mononuclear cells (PBMC), and syngeneic mouse models, finding additive efficacy in combination with an anti-PD-1 (a well-characterized checkpoint inhibitor). These findings support IGSF1 as an immune target that might complement existing cancer immunotherapeutics.

CA9, CYFIP2 and LGALS3BP-A Novel Biomarker Panel to Aid Prognostication in Glioma

Brain cancer is a devastating and life-changing disease. Biomarkers are becoming increasingly important in addressing clinical issues, including in monitoring tumour progression and assessing survival and treatment response. The goal of this study was to identify prognostic biomarkers associated with glioma progression. Discovery proteomic analysis was performed on a small cohort of astrocytomas that were diagnosed as low-grade and recurred at a higher grade. Six proteins were chosen to be validated further in a larger cohort. Three proteins, CA9, CYFIP2, and LGALS3BP, were found to be associated with glioma progression and, in univariate analysis, could be used as prognostic markers. However, according to the results of multivariate analysis, these did not remain significant. These three proteins were then combined into a three-protein panel. This panel had a specificity and sensitivity of 0.7459 for distinguishing between long and short survival. In silico data confirmed the prognostic significance of this panel.

DHCR24 in Tumor Diagnosis and Treatment: A Comprehensive Review

As an important nutrient in the human body, cholesterol can not only provide structural components for the body's cells, but also can be transformed into a variety of active substances to regulate cell signaling pathways. As an important cholesterol synthase, DHCR24 participates in important regulatory processes in the body. The application of DHCR24 in tumor clinical diagnosis and treatment also attracts much attention. This article reviews the structure and regulatory characteristics of DHCR24, and the research of DHCR24 on tumor progression. We summarize the possible mechanisms of DHCR24 promoting tumor progression through reactive oxygen species (ROS), p53, Ras and PI3K-AKT pathways. Through our review, we hope to provide more research ideas and reference value for the application of DHCR24 in tumor prevention and treatment.

The heterogeneity and clonal evolution analysis of the advanced prostate cancer with castration resistance

BACKGROUND

Nowadays, the incidence rate of advanced and metastatic prostate cancer at the first time of diagnosis grows higher in China yearly. At present, androgen deprivation therapy (ADT) is the primary treatment of advanced prostate cancer. However, after several years of ADT, most patients will ultimately progress to castration-resistant prostate cancer (CRPC). Previous studies mainly focus on Caucasian and very few on East Asian patients.

METHODS

In this study, the pre- and post-ADT tumor samples were collected from five Chinese patients with advanced prostate cancer. The whole-exome sequencing, tumor heterogeneity, and clonal evolution pattern were analyzed.

RESULTS

The results showed that the gene mutation pattern and heterogeneity changed significantly after androgen deprivation therapy. Tumor Mutational Burden (TMB) and Copy Number Alteration (CNA) were substantially reduced in the post-treatment group, but the Mutant-allele tumor heterogeneity (MATH), Socio-Demographic Index (SDI), Intratumor heterogeneity (ITH), and weighted Genome Instability Index (wGII) had no significant difference. According to the clone types and characteristics, the presence of main clones in five pre-and post-treatment samples, the clonal evolution pattern can be further classified into two sub-groups (the Homogeneous origin clonal model or the Heterogeneous origin clonal model). The Progression-free survival (PFS) of the patients with the "Homogeneous origin clonal model" was shorter than the "Heterogeneous origin clonal model". The longer PFS might relate to MUC7 and MUC5B mutations repaired. ZNF91 mutation might be responsible for resistance to ADT resistance.

CONCLUSION

Our findings revealed potential genetic regulators to predict the castration resistance and provide insights into the castration resistance processes in advanced prostate cancer. The crosstalk between clonal evolution patterns and tumor microenvironment may also play a role in castration resistance. A multicenter-research including larger populations with different background are needed to confirm our conclusion in the future.

Mitochondria and cytochrome components released into the plasma of severe COVID-19 and ICU acute respiratory distress syndrome patients

INTRODUCTION

Proteomic analysis of human plasma by LC-ESI-MS/MS has discovered a limited number of new cellular protein biomarkers that may be confirmed by independent biochemical methods. Analysis of COVID-19 plasma has indicated the re-purposing of known biomarkers that might be used as prognostic markers of COVID-19 infection. However, multiple molecular approaches have previously indicated that the SARS-COV2 infection cycle is linked to the biology of mitochondria and that the response to infections may involve the action of heme containing oxidative enzymes.

METHODS

Human plasma from COVID-19 and ICU-ARDS was analyzed by classical analytical biochemistry techniques and classical frequency-based statistical approaches to look for prognostic markers of severe COVID-19 lung damage. Plasma proteins from COVID-19 and ICU-ARDS were identified and enumerated versus the controls of normal human plasma (NHP) by LC-ESI-MS/MS. The observation frequency of proteins detected in COVID-19 and ICU-ARDS patients were compared to normal human plasma, alongside random and noise MS/MS spectra controls, using the Chi Square (χ²) distribution.

RESULTS

PCR showed the presence of MT-ND1 DNA in the plasma of COVID-19, ICU-ARDS, as well as normal human plasma. Mitochondrial proteins such as MRPL, L2HGDH, ATP, CYB, CYTB, CYP, NDUF and others, were increased in COVID-19 and ICU-ARDS plasma. The apparent activity of the cytochrome components were tested alongside NHP by dot blotting on PVDF against a purified cytochrome c standard preparation for H₂O₂ dependent reaction with luminol as measured by enhanced chemiluminescence (ECL) that showed increased activity in COVID-19 and ICU-ARDS patients.

DISCUSSION

The results from PCR, LC-ESI-MS/MS of tryptic peptides, and cytochrome ECL assays confirmed that mitochondrial components were present in the plasma, in agreement with the established central role of the mitochondria in SARS-COV-2 biology. The cytochrome activity assay showed that there was the equivalent of at least nanogram amounts of cytochrome(s) in the plasma sample that should be clearly detectable by LC-ESI-MS/MS. The release of the luminol oxidase activity from cells into plasma forms the basis of a simple and rapid test for the severity of cell damage and lung injury in COVID-19 infection and ICU-ARDS.

Comprehensive analysis of ZNF family genes in prognosis, immunity, and treatment of esophageal cancer

BACKGROUND

As a common malignant tumor, esophageal carcinoma (ESCA) has a low early diagnosis rate and poor prognosis. This study aimed to construct the prognostic features composed of ZNF family genes to effectively predict the prognosis of ESCA patients.

METHODS

The mRNA expression matrix and clinical data were downloaded from TCGA and GEO database. Using univariate Cox analysis, lasso regression and multivariate Cox analysis, we screened six prognosis-related ZNF family genes to construct the prognostic model. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, and nomogram to evaluate the prognostic value within and across sets, separately and combined. We also validated the prognostic value of the six-gene signature using GSE53624 dataset. The different immune status was observed in the single sample Gene Set Enrichment Analysis (ssGSEA). Finally, real-time quantitative PCR was used to detect the expression of six prognostic ZNF genes in twelve pairs of ESCA and adjacent normal tissues.

RESULTS

A six prognosis-related ZNF family genes model consisted of ZNF91, ZNF586, ZNF502, ZNF865, ZNF106 and ZNF225 was identified. Multivariable Cox regression analysis revealed that six prognosis-related ZNF family genes were independent prognostic factors for overall survival of ESCA patients in TCGA and GSE53624. Further, a prognostic nomogram including the riskScore, age, gender, T, stage was constructed, and TCGA/GSE53624-based calibration plots indicated its excellent predictive performance. Drug Sensitivity and ssGSEA analysis showed that the six genes model was closely related to immune cells infiltration and could be used as a potential predictor of chemotherapy sensitivity.

CONCLUSION

We identified six prognosis-related ZNF family genes model of ESCA, which provide evidence for individualized prevention and treatment.

A peptide-centric approach to analyse quantitative proteomics data- an application to prostate cancer biomarker discovery

Bottom-up proteomics is a popular approach in molecular biomarker research. However, protein analysts have realized the limitations of protein-based approaches for identifying and quantifying proteins in complex samples, such as the identification of peptides sequences shared by multiple proteins and the difficulty in identifying modified peptides. Thus, there are many exciting opportunities to improve analysis methods. Here, an alternative method focused on peptide analysis is proposed as a complement to the conventional proteomics data analysis. To investigate this hypothesis, a peptide-centric approach was applied to reanalyse a urine proteome dataset of samples from prostate cancer patients and controls. The results were compared with the conventional protein-centric approach. The relevant proteins/peptides to discriminate the groups were detected based on two approaches, p-value and VIP values obtained by a PLS-DA model. A comparison of the two strategies revealed high inconsistency between protein and peptide information and greater involvement of peptides in key PCa processes. This peptide analysis unveiled discriminative features that are lost when proteins are analyzed as homogeneous entities. This type of analysis is innovative in PCa and integrated with the widely used protein-centric approach might provide a more comprehensive view of this disease and revolutionize biomarker discovery. SIGNIFICANCE: In this study, the application of a protein and peptide-centric approaches to reanalyse a urine proteome dataset from prostate cancer (PCa) patients and controls showed that many relevant proteins/peptides are missed by the conservative nature of p-value in statistical tests, therefore, the inclusion of variable selection methods in the analysis of the dataset reported in this work is fruitful. Comparison of protein- and peptide-based approaches revealed a high inconsistency between protein and peptide information and a greater involvement of peptides in key PCa processes. These results provide a new perspective to analyse proteomics data and detect relevant targets based on the integration of peptide and protein information. This data integration allows to unravel discriminative features that normally go unnoticed, to have a more comprehensive view of the disease pathophysiology and to open new avenues for the discovery of biomarkers.

CHD6 promotes broad nucleosome eviction for transcriptional activation in prostate cancer cells

Despite being a member of the chromodomain helicase DNA-binding protein family, little is known about the exact role of CHD6 in chromatin remodeling or cancer disease. Here we show that CHD6 binds to chromatin to promote broad nucleosome eviction for transcriptional activation of many cancer pathways. By integrating multiple patient cohorts for bioinformatics analysis of over a thousand prostate cancer datasets, we found CHD6 expression elevated in prostate cancer and associated with poor prognosis. Further comprehensive experiments demonstrated that CHD6 regulates oncogenicity of prostate cancer cells and tumor development in a murine xenograft model. ChIP-Seq for CHD6, along with MNase-Seq and RNA-Seq, revealed that CHD6 binds on chromatin to evict nucleosomes from promoters and gene bodies for transcriptional activation of oncogenic pathways. These results demonstrated a key function of CHD6 in evicting nucleosomes from chromatin for transcriptional activation of prostate cancer pathways.

Anti-SEZ6L2 antibodies in paraneoplastic cerebellar syndrome: case report and review of the literature

Seizure Related 6 Homolog Like 2 (SEZ6L2) protein has been shown to have implications in neuronal and especially motor function development. In oncology, overexpression of SEZ6L2 serves as a negative prognostic marker in several tumor entities. Recently, few cases of anti-SEZ6L2 antibody mediated cerebellar syndromes were reported. In this article, we present a case of a 70-year-old woman with subacute onset of gait disturbance, dysarthria and limb ataxia. Serum anti-SEZ6L2 antibodies were markedly increased, and further diagnostic workup revealed left sided breast cancer. Neurological symptoms and SEZ6L2 titer significantly improved after curative tumor therapy. This is a very rare and educationally important report of anti-SEZ6L2 autoimmune cerebellar syndrome with a paraneoplastic etiology. Additionally, we performed a review of the current literature for SEZ6L2, focusing on comparing the published cases on autoimmune cerebellar syndrome.

Genome-wide association study of aromatase inhibitor discontinuation due to musculoskeletal symptoms

OBJECTIVE

Aromatase inhibitors (AIs) are commonly used to treat hormone receptor positive (HR +) breast cancer. AI-induced musculoskeletal syndrome (AIMSS) is a common toxicity that causes AI treatment discontinuation. The objective of this genome-wide association study (GWAS) was to identify genetic variants associated with discontinuation of AI therapy due to AIMSS and attempt to replicate previously reported associations.

METHODS

In the Exemestane and Letrozole Pharmacogenetics (ELPh) study, postmenopausal patients with HR + non-metastatic breast cancer were randomized to letrozole or exemestane. Genome-wide genotyping of germline DNA was conducted followed by imputation. Each imputed variant was tested for association with time-to-treatment discontinuation due to AIMSS using a Cox proportional hazards model assuming additive genetic effects and adjusting for age, baseline pain score, prior taxane treatment, and AI arm. Secondary analyses were conducted within each AI arm and analyses of candidate variants previously reported to be associated with AIMSS risk.

RESULTS

Four hundred ELPh participants were included in the combined analysis. Two variants surpassed the genome-wide significance level in the primary analysis (p value < 5 × 10-8), an intronic variant (rs79048288) within CCDC148 (HR = 4.42, 95% CI: 2.67-7.33) and an intergenic variant (rs912571) upstream of PPP1R14C (HR = 0.30, 95% CI: 0.20-0.47). In the secondary analysis, rs74418677, which is known to be associated with expression of SUPT20H, was significantly associated with discontinuation of letrozole therapy due to AIMSS (HR = 5.91, 95% CI: 3.16-11.06). We were able to replicate associations for candidate variants previously reported to be associated with AIMSS in this cohort, but were not able to replicate associations for any other variants previously reported in other patient cohorts.

CONCLUSIONS

Our GWAS findings identify several candidate variants that may be associated with AIMSS risk from AI generally or letrozole specifically. Validation of these associations in independent cohorts is needed before translating these findings into clinical practice to improve treatment outcomes in patients with HR + breast cancer.

LEDGF is a new growth factor in fetal serum

Fetal serum supports the immortal growth of mammalian cell lines in culture while adult serum leads to the terminal differentiation and death of cells in culture. Many of the proteins in fetal serum that support the indefinite division and growth of cancerous cell lines remain obscure. The peptides and proteins of fetal versus adult serum were analyzed by liquid chromatography, nano electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS). Three batches of fetal serum contained the Alpha Fetoprotein marker while adult serum batches did not. Insulin (INS), and insulin-like growth factor (ILGF), fibroblast growth factor (FGF), epidermal growth factor (EGF) and platelet derived growth factor (PDGF) were increased in fetal serum. New fetal growth factors including MEGF, HDGFRP and PSIP1 and soluble growth receptors such as TNFR, EGFR, NTRK2 and THRA were discovered. Addition of insulin or the homeotic transcription factor PSIP1, also referred to as Lens Epithelium Derived Growth Factor (LEDGF), partially restored the rounded phenotype of rapidly dividing cells but was not as effective as fetal serum. Thus, a new growth factor in fetal serum, LEDGF/PSIP1, was directly observed by tandem mass spectrometry and confirmed by add back experiments to cell culture media alongside insulin.

Loxl3 Promotes Melanoma Progression and Dissemination Influencing Cell Plasticity and Survival

Simple Summary

Malignant melanoma is the most lethal skin cancer due to its aggressive clinical behavior and therapeutic resistance. A comprehensive knowledge of the molecular mechanisms underlying melanoma progression is urgently needed to improve the survival of melanoma patients. Phenotypic plasticity of melanoma cells has emerged as a key process in melanomagenesis and therapy resistance. This phenotypic plasticity is sustained by an epithelial-to-mesenchymal (EMT)-like program that favors multiple intermediate states and allows adaptation to changing microenvironments along melanoma progression. Given the essential role of lysyl oxidase-like 3 (LOXL3) in human melanoma cell survival and its contribution to EMT, we generated mice with conditional melanocyte-specific targeting of Loxl3, concomitant to Braf activation and Pten deletion. Our results supported a key role of Loxl3 for melanoma progression, metastatic dissemination, and genomic stability, and supported its contribution to melanoma phenotypic plasticity by modulating the expression of several EMT transcription factors (EMT-TFs).

Abstract

Malignant melanoma is a highly aggressive tumor causing most skin cancer-related deaths. Understanding the fundamental mechanisms responsible for melanoma progression and therapeutic evasion is still an unmet need for melanoma patients. Progression of skin melanoma and its dissemination to local or distant organs relies on phenotypic plasticity of melanoma cells, orchestrated by EMT-TFs and microphthalmia-associated TF (MITF). Recently, melanoma phenotypic switching has been proposed to uphold context-dependent intermediate cell states benefitting malignancy. LOXL3 (lysyl oxidase-like 3) promotes EMT and has a key role in human melanoma cell survival and maintenance of genomic integrity. To further understand the role of Loxl3 in melanoma, we generated a conditional Loxl3-knockout (KO) melanoma mouse model in the context of BrafV600E-activating mutation and Pten loss. Melanocyte-Loxl3 deletion increased melanoma latency, decreased tumor growth, and reduced lymph node metastatic dissemination. Complementary in vitro and in vivo studies in mouse melanoma cells confirmed Loxl3’s contribution to melanoma progression and metastasis, in part by modulating phenotypic switching through Snail1 and Prrx1 EMT-TFs. Importantly, a novel LOXL3-SNAIL1-PRRX1 axis was identified in human melanoma, plausibly relevant to melanoma cellular plasticity. These data reinforced the value of LOXL3 as a therapeutic target in melanoma.

Insights into the Association Between QSER1 and M2 Macrophages and Remarkable Malignancy Characteristics in Hepatocellular Carcinoma

Purpose

Glutamine and serine rich 1 (QSER1), as a DNA methylation modulator, play a crucial role in transforming tumor cells. Previous studies have shown that QSER1 plays a role in regulating the progression of various malignancies and that QSER1 dysfunction is connected with precancerous lesions of hepatocellular carcinoma (HCC) as well as HCC prognosis. However, little is known about the detailed contribution of QSER1 in HCC.

Patients and Methods

Various statistical methods such as Kaplan–Meier method, AUC analysis, GSEA, and immune-infiltration analysis were used to evaluate the relationship between QSER1 expression and clinical features, prognostic factors, and potential functional mechanisms of QSER1.

Results

QSER1 expression was negatively correlated with clinicopathological features (clinical stage, pathological grade, TP53 mutation, lymph node metastasis) and clinical outcome (overall survival versus recurrence). Functional enrichment analysis further suggested that QSER1 is involved in multiple pathways related to DNA replication and tumor immunity. TIMER analysis indicated that high QSER1 expression was significantly associated with higher macrophage infiltration and poorer macrophage-related outcomes. In particular, QSER1 was significantly more associated with M2 macrophages than M1 macrophages.

Conclusion

Overall, elevated QSER1 is a potential prognostic marker for HCC and is associated with immune infiltration in HCC.

Hemopexin and Cancer

Hemopexin is the plasma protein with the highest affinity for heme. Seminal studies have highlighted its role in different kinds of heme-associated disorders, but its implication in cancer has been neglected for a long time. Considering the emerging importance of heme in tumors, the present review proposes an update of the works investigating hemopexin involvement in cancer, with the attempt to stimulate further future studies on this topic.

Toward improvement of screening through mass spectrometry-based proteomics: ovarian cancer as a case study

Ovarian cancer is one of the leading causes of cancer related deaths affecting United States women. Early-stage detection of ovarian cancer has been linked to increased survival, however, current screening methods, such as biomarker testing, have proven to be ineffective in doing so. Therefore, further developments are necessary to be able to achieve positive patient prognosis. Ongoing efforts are being made in biomarker discovery towards clinical applications in screening for early-stage ovarian cancer. In this perspective, we discuss and provide examples for several workflows employing mass spectrometry-based proteomics towards protein biomarker discovery and characterization in the context of ovarian cancer; workflows include protein identification and characterization as well as intact protein profiling. We also discuss the opportunities to merge these workflows for a multiplexed approach for biomarkers. Lastly, we provide our insight as to future developments that may serve to enhance biomarker discovery workflows while also considering translational potential.

Clinical Significance and Integrative Analysis of the SMC Family in Hepatocellular Carcinoma

Worldwide, hepatocellular carcinoma (HCC) is one of the most malignant cancers with poor prognosis. The structural maintenance of chromosomes (SMC) gene family has been shown to play important roles in human cancers. Nevertheless, the role of SMC members in HCC is not well-understood. In this study, we comprehensively explored the role of the SMC family in HCC using a series of bioinformatic analysis tools. Studies have demonstrated that the mRNA expression levels of SMC1A, SMC1B, SMC2, SMC4, and SMC6 are significantly overexpressed in HCC, and the protein levels of SMC1A, SMC2, SMC3, SMC4, SMC5, and SMC6 are similarly elevated. Moreover, HCC patients with high SMC2 and SMC4 expression levels exhibit poor survival. Using KEGG and GO analyses, we analyzed the enrichment of gene expression in the biological functions and pathways of the SMC family in HCC. Immune infiltration analysis revealed that the expression of the SMC family is closely associated with B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils, and DCs. In conclusion, our findings will enhance a more thorough understanding of the SMC family in HCC progression and provide new directions for the diagnosis and treatment of HCC in the future.

LOXL3 Silencing Affected Cell Adhesion and Invasion in U87MG Glioma Cells

Lysyl oxidase-like 3 (LOXL3), belonging to the lysyl oxidase family, is responsible for the crosslinking in collagen or elastin. The cellular localization of LOXL3 is in the extracellular space by reason of its canonical function. In tumors, the presence of LOXL3 has been associated with genomic stability, cell proliferation, and metastasis. In silico analysis has shown that glioblastoma was among tumors with the highest LOXL3 expression levels. LOXL3 silencing of U87MG cells by siRNA led to the spreading of the tumor cell surface, and the transcriptome analysis of these cells revealed an upregulation of genes coding for extracellular matrix, cell adhesion, and cytoskeleton components, convergent to an increase in cell adhesion and a decrease in cell invasion observed in functional assays. Significant correlations of LOXL3 expression with genes coding for tubulins were observed in the mesenchymal subtype in the TCGA RNA-seq dataset of glioblastoma (GBM). Conversely, genes involved in endocytosis and lysosome formation, along with MAPK-binding proteins related to focal adhesion turnover, were downregulated, which may corroborate the observed decrease in cell viability and increase in the rate of cell death. Invasiveness is a major determinant of the recurrence and poor outcome of GBM patients, and downregulation of LOXL3 may contribute to halting the tumor cell invasion.

LINC01224/ZNF91 Promote Stem Cell-Like Properties and Drive Radioresistance in Non-Small Cell Lung Cancer

Background

Radioresistance is the main reason for the failure of radiotherapy in non-small-cell lung cancer (NSCLC); however, the molecular mechanism of radioresistance is still unclear.

Methods

An RNA-Seq assay was used to screen differentially expressed long non-coding RNAs (lncRNAs) and genes in irradiation-resistant NSCLC cells. RT-PCR and Western blotting assays were performed to analyze the expressions of lncRNAs and genes. The chromosome conformation capture (3C) assay was performed to measure chromatin interactions. Cell cytotoxicity, cell apoptosis, sphere formation and Transwell assays were performed to assess cellular function.

Results

In this study, it was found that LINC01224 increased during the induction of radioresistance in NSCLC cells. LINC01224 was located within the enhancer of ZNF91, and LINC01224 could affect the transcription of ZNF91 by regulating the long-range interactions between the ZNF91 enhancer and promoter. Moreover, upregulation of LINC01224 and ZNF91 could promote irradiation resistance by regulating the stem cell-like properties of NSCLC cells. In addition, high expression levels of LINC01224 and ZNF91 in tissue samples were associated with radioresistance in NSCLC patients.

Conclusion

Our findings demonstrated that LINC01224/ZNF91 drove radioresistance regulation by promoting the stem cell-like properties in NSCLC.

The plasma peptides of Alzheimer's disease

Background

A practical strategy to discover proteins specific to Alzheimer’s dementia (AD) may be to compare the plasma peptides and proteins from patients with dementia to normal controls and patients with neurological conditions like multiple sclerosis or other diseases. The aim was a proof of principle for a method to discover proteins and/or peptides of plasma that show greater observation frequency and/or precursor intensity in AD. The endogenous tryptic peptides of Alzheimer’s were compared to normals, multiple sclerosis, ovarian cancer, breast cancer, female normal, sepsis, ICU Control, heart attack, along with their institution-matched controls, and normal samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from blinded, individual AD and control EDTA plasma samples in a step gradient of acetonitrile for random and independent sampling by LC–ESI–MS/MS with a set of robust and sensitive linear quadrupole ion traps. The MS/MS spectra were fit to fully tryptic peptides within proteins identified using the X!TANDEM algorithm. Observation frequency of the identified proteins was counted using SEQUEST algorithm. The proteins with apparently increased observation frequency in AD versus AD Control were revealed graphically and subsequently tested by Chi Square analysis. The proteins specific to AD plasma by Chi Square with FDR correction were analyzed by the STRING algorithm. The average protein or peptide log₁₀ precursor intensity was compared across disease and control treatments by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as complement C2, C7, and C1QBP among others showed increased observation frequency by Chi Square and/or precursor intensity in AD. Cellular gene symbols with large Chi Square values (χ2 ≥ 25, p ≤ 0.001) from tryptic peptides included KIF12, DISC1, OR8B12, ZC3H12A, TNF, TBC1D8B, GALNT3, EME2, CD1B, BAG1, CPSF2, MMP15, DNAJC2, PHACTR4, OR8B3, GCK, EXOSC7, HMGA1 and NT5C3A among others. Similarly, increased frequency of tryptic phosphopeptides were observed from MOK, SMIM19, NXNL1, SLC24A2, Nbla10317, AHRR, C10orf90, MAEA, SRSF8, TBATA, TNIK, UBE2G1, PDE4C, PCGF2, KIR3DP1, TJP2, CPNE8, and NGF amongst others. STRING analysis showed an increase in cytoplasmic proteins and proteins associated with alternate splicing, exocytosis of luminal proteins, and proteins involved in the regulation of the cell cycle, mitochondrial functions or metabolism and apoptosis. Increases in mean precursor intensity of peptides from common plasma proteins such as DISC1, EXOSC5, UBE2G1, SMIM19, NXNL1, PANO, EIF4G1, KIR3DP1, MED25, MGRN1, OR8B3, MGC24039, POLR1A, SYTL4, RNF111, IREB2, ANKMY2, SGKL, SLC25A5, CHMP3 among others were associated with AD. Tryptic peptides from the highly conserved C-terminus of DISC1 within the sequence MPGGGPQGAPAAAGGGGVSHRAGSRDCLPPAACFR and ARQCGLDSR showed a higher frequency and highest intensity in AD compared to all other disease and controls.

Conclusion

Proteins apparently expressed in the brain that were directly related to Alzheimer’s including Nerve Growth Factor (NFG), Sphingomyelin Phosphodiesterase, Disrupted in Schizophrenia 1 (DISC1), the cell death regulator retinitis pigmentosa (NXNl1) that governs the loss of nerve cells in the retina and the cell death regulator ZC3H12A showed much higher observation frequency in AD plasma vs the matched control. There was a striking agreement between the proteins known to be mutated or dis-regulated in the brains of AD patients with the proteins observed in the plasma of AD patients from endogenous peptides including NBN, BAG1, NOX1, PDCD5, SGK3, UBE2G1, SMPD3 neuronal proteins associated with synapse function such as KSYTL4, VTI1B and brain specific proteins such as TBATA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-021-09320-2.

Mining TCGA database for gene expression in ovarian serous cystadenocarcinoma microenvironment

Background

Ovarian cancer is one of the leading causes of female deaths worldwide. Ovarian serous cystadenocarcinoma occupies about 90% of it. Effective and accurate biomarkers for diagnosis, outcome prediction and personalized treatment are needed urgently

Methods

Gene expression profile for OSC patients was obtained from the TCGA database. The ESTIMATE algorithm was used to calculate immune scores and stromal scores of expression data of ovarian serous cystadenocarcinoma samples. Survival results between high and low groups of immune and stromal score were compared and differentially expressed genes (DEGs) were screened out by limma package. The Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and the protein-protein interaction (PPI) network analysis were performed with the g:Profiler database, the Cytoscape and Search Tool for the Retrieval of Interacting Genes (STRING-DB). Survival results between high and low immune and stromal score groups were compared. Kaplan-Meier plots based on TCGA follow up information were generated to evaluate patients’ overall survival.

Results

Eighty-six upregulated DEGs and one downregulated DEG were identified. Three modules, which included 49 nodes were chosen as important networks. Seven DEGs (VSIG4, TGFBI, DCN, F13A1, ALOX5AP, GPX3, SFRP4) were considered to be correlated with poor overall survival.

Conclusion

Seven DEGs (VSIG4, TGFBI, DCN, F13A1, ALOX5AP, GPX3, SFRP4) were correlated with poor overall survival in our study. This new set of genes can become strong predictor of survival, individually or combined. Further investigation of these genes is needed to validate the conclusion to provide novel understanding of tumor microenvironment with ovarian serous cystadenocarcinoma prognosis and treatment.

SIRT1 and gynecological malignancies (Review)

Sirtuin 1 (SIRT1), a member of the sirtuin protein family, is a nicotinamide adenine dinucleotide (NAD⁺)-dependent type III histone deacetylase and mono-ADP-ribosyltransferase. SIRT1 can deacetylate histones (H1, H3, and H4) and non-histone proteins, and it is widely involved in various physiological and pathological processes in the body, including metabolism, aging, transcription, DNA damage and repair, apoptosis, cell cycle regulation, inflammation and cancer. Research has shown that SIRT1 is involved in tumorigenesis, tumor metastasis and chemotherapy resistance, but it exerts opposing effects and plays different roles in different pathogenic processes. Recent studies have demonstrated that SIRT1 may be implicated in the pathogenesis, development, treatment and prognosis of tumors; however, its role in gynecological tumors remains elusive. The aim of the present review was to summarize the pathogenic roles of SIRT1 in cancer, and to provide what is, to the best of our knowledge, the first review of recent advances involving SIRT1 in cervical cancer, endometrial cancer (EC) and ovarian cancer (OC). In addition, the critical research gaps regarding SIRT1, particularly its potential involvement in the concurrence of EC and cervical cancer and its antagonistic effect against poly(ADP-ribose) polymerase inhibitors in OC, were highlighted.

A Meta-Analysis of Proteomic Blood Markers of Colorectal Cancer

BACKGROUND

Early diagnosis will significantly improve the survival rate of colorectal cancer (CRC); however, the existing methods for CRC screening were either invasive or inefficient. There is an emergency need for novel markers in CRC's early diagnosis. Serum proteomics has gained great potential in discovering novel markers, providing markers that reflect the early stage of cancer and prognosis prediction of CRC. In this paper, the results of proteomics of CRC studies were summarized through a meta-analysis in order to obtain the diagnostic efficiency of novel markers.

METHODS

A systematic search on bibliographic databases was performed to collect the studies that explore blood-based markers for CRC applying proteomics. The detection and validation methods, as well as the specificity and sensitivity of the biomarkers in these studies, were evaluated. Newcastle- Ottawa Scale (NOS) case-control studies version was used for quality assessment of included studies.

RESULTS

Thirty-four studies were selected from 751 studies, in which markers detected by proteomics were summarized. In total, fifty-nine proteins were classified according to their biological function. The sensitivity, specificity, or AUC varied among these markers. Among them, Mammalian STE20-like protein kinase 1/ Serine threonine kinase 4 (MST1/STK4), S100 calcium-binding protein A9 (S100A9), and Tissue inhibitor of metalloproteinases 1 (TIMP1) were suitable for effect sizes merging, and their diagnostic efficiencies were recalculated after merging. MST1/STK4 obtained a sensitivity of 68% and a specificity of 78%. S100A9 achieved a sensitivity of 72%, a specificity of 83%, and an AUC of 0.88. TIMP1 obtained a sensitivity of 42%, a specificity of 88%, and an AUC of 0.71.

CONCLUSION

MST1/STK4, S100A9, and TIMP1 showed excellent performance for CRC detection. Several other markers also presented optimized diagnostic efficacy for CRC early detection, but further verification is still needed before they are suitable for clinical use. The discovering of more efficient markers will benefit CRC treatment.

Convergence of Plasma Metabolomics and Proteomics Analysis to Discover Signatures of High-Grade Serous Ovarian Cancer

Simple Summary

In-time diagnosing ovarian cancer, intractable cancer that has no symptoms can increase the survival of women. The aim of this study was to discover biomarkers from liquid biopsy samples using multi-omics approach, metabolomics and proteomics for the diagnosis of ovarian cancer. To verify our biomarker candidates, we conducted comparative analysis with other previous published studies. Despite the limitations of non-invasive samples, our findings are able to discover emerging properties through the interplay between metabolites and proteins and mechanism-based biomarkers through integrated protein and metabolite analysis.

Abstract

The 5-year survival rate in the early and late stages of ovarian cancer differs by 63%. In addition, a liquid biopsy is necessary because there are no symptoms in the early stage and tissue collection is difficult without using invasive methods. Therefore, there is a need for biomarkers to achieve this goal. In this study, we found blood-based metabolite or protein biomarker candidates for the diagnosis of ovarian cancer in the 20 clinical samples (10 ovarian cancer patients and 10 healthy control subjects). Plasma metabolites and proteins were measured and quantified using mass spectrometry in ovarian cancer patients and control groups. We identified the differential abundant biomolecules (34 metabolites and 197 proteins) and statistically integrated molecules of different dimensions to better understand ovarian cancer signal transduction and to identify novel biological mechanisms. In addition, the biomarker reliability was verified through comparison with existing research results. Integrated analysis of metabolome and proteome identified emerging properties difficult to grasp with the single omics approach, more reliably interpreted the cancer signaling pathway, and explored new drug targets. Especially, through this analysis, proteins (PPCS, PMP2, and TUBB) and metabolites (L-carnitine and PC-O (30:0)) related to the carnitine system involved in cancer plasticity were identified.

SEZ6L2 Is an Important Regulator of Drug-Resistant Cells and Tumor Spheroid Cells in Lung Adenocarcinoma

Many lung cancer deaths result from relapses in distant organs, such as the brain or bones, after standard chemotherapy. For cancer cells to spread to other organs, they must survive as circulating tumor cells (CTCs) in blood vessels. Thus, reducing distant recurrence after chemotherapy requires simultaneously inhibiting drug resistance and CTC survival. Here, we investigated the molecular pathways and genes that are commonly altered in drug-resistant lung cancer cells and lung tumor spheroid (TS) cells. First, RNA sequencing was performed in drug-resistant cells and TS cells originating from H460 and A549 lung cancer cells. Bioinformatic pathway analysis showed that cell cycle-related pathways were downregulated in drug-resistant cells, and cholesterol biosynthesis-related pathways were upregulated in TS cells. Seizure-related 6 homolog-like 2 (SEZ6L2) was selected as a gene that was commonly upregulated in both drug-resistant cells and TS cells, and that showed elevated expression in samples from lung adenocarcinoma patients. Second, the protein expression of SEZ6L2 was analyzed by flow cytometry. The proportions of SEZ6L2 positive cells among both drug-resistant cells and TS cells was increased. Finally, as SEZ6L2 is a transmembrane protein with an extracellular region, the function of SEZ6L2 was disrupted by treatment with an anti-SEZ6L2 antibody. Treatment with the anti-SEZ6L2 antibody reduced drug resistance and TS formation. Overall, our data showed that SEZ6L2 plays an important role in drug resistance and TS formation and may be a therapeutic target for reducing distant recurrence of lung adenocarcinoma.

The plasma peptides of sepsis

Background

A practical strategy to discover sepsis specific proteins may be to compare the plasma peptides and proteins from patients in the intensive care unit with and without sepsis. The aim was to discover proteins and/or peptides that show greater observation frequency and/or precursor intensity in sepsis. The endogenous tryptic peptides of ICU-Sepsis were compared to ICU Control, ovarian cancer, breast cancer, female normal, sepsis, heart attack, Alzheimer’s and multiple sclerosis along with their institution-matched controls, female normals and normal samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from individual sepsis and control EDTA plasma samples in a step gradient of acetonitrile for random and independent sampling by LC–ESI–MS/MS with a set of robust and sensitive linear quadrupole ion traps. The MS/MS spectra were fit to fully tryptic peptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The protein observation frequency of ICU-sepsis versus ICU Control was subsequently tested by Chi square analysis. The average protein or peptide log₁₀ precursor intensity was compared across disease and control treatments by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as ITIH3, SAA2, SAA1, and FN1 showed increased observation frequency by Chi square (χ² > 9, p < 0.003) and/or precursor intensity in sepsis. Cellular gene symbols with large Chi square values from tryptic peptides included POTEB, CTNNA1, U2SURP, KIF24, NLGN2, KSR1, GTF2H1, KIT, RPS6KL1, VAV2, HSPA7, SMC2, TCEB3B, ZNF300, SUPV3L1, ADAMTS20, LAMB4, MCCC1, SUPT6H, SCN9A, SBNO1, EPHA1, ABLIM2, cB5E3.2, EPHA10, GRIN2B, HIVEP2, CCL16, TKT, LRP2 and TMF1 amongst others showed increased observation frequency. Similarly, increased frequency of tryptic phosphopeptides were observed from POM121C, SCN8A, TMED8, NSUN7, SLX4, MADD, DNLZ, PDE3B, UTY, DEPDC7, MTX1, MYO1E, RXRB, SYDE1, FN1, PUS7L, FYCO1, USP26, ACAP2, AHI1, KSR2, LMAN1, ZNF280D and SLC8A2 amongst others. Increases in mean precursor intensity in peptides from common plasma proteins such as ITIH3, SAA2, SAA1, and FN1 as well as cellular proteins such as COL24A1, POTEB, KANK1, SDCBP2, DNAH11, ADAMTS7, MLLT1, TTC21A, TSHR, SLX4, MTCH1, and PUS7L among others were associated with sepsis. The processing of SAA1 included the cleavage of the terminal peptide D/PNHFRPAGLPEKY from the most hydrophilic point of SAA1 on the COOH side of the cystatin C binding that was most apparent in ICU-Sepsis patients compared to all other diseases and controls. Additional cleavage of SAA1 on the NH2 terminus side of the cystatin binding site were observed in ICU-Sepsis. Thus there was disease associated variation in the processing of SAA1 in ICU-Sepsis versus ICU controls or other diseases and controls.

Conclusion

Specific proteins and peptides that vary between diseases might be discovered by the random and independent sampling of multiple disease and control plasma from different hospital and clinics by LC–ESI–MS/MS for storage in a relational SQL Server database and analysis with the R statistical system that will be a powerful tool for clinical research. The processing of SAA1 may play an unappreciated role in the inflammatory response to Sepsis.

Roles of eIF3m in the tumorigenesis of triple negative breast cancer

Background

Without targets, triple negative breast cancer (TNBC) has the worst prognosis in all subtypes of breast cancer (BC). Recently, eukaryotic translation initiation factor 3 m (eIF3m) has been declared to be involved in the malignant progression of various neoplasms. The aim of this study is to explore biological functions of eIF3m in TNBC.

Methods

Multiple databases, including Oncomine, KM-plotter and so on, were performed to analyze prognosis and function of eIF3m in TNBC. After transfection of eIF3m-shRNA lentivirus, CCK-8, colony formation assay, cell cycle analysis, wound healing assay, transwell assays, mitochondrial membrane potential assay and cell apoptosis analysis were performed to explore the roles of eIF3m in TNBC cell bio-behaviors. In addition, western blotting was conducted to analyze the potential molecular mechanisms of eIF3m.

Results

In multiple databases, up-regulated eIF3m had lower overall survival, relapse-free survival and post progression survival in BC. EIF3m expression in TNBC was obviously higher than in non-TNBC or normal breast tissues. Its expression in TNBC was positively related to differentiation, lymph node invasion and distant metastasis. After knockdown of eIF3m, cell proliferation, migration, invasion and levels of mitochondrial membrane potential of MDA-MB-231 and MDA-MB-436 were all significantly suppressed, while apoptosis rates of them were obviously increased. In addition, eIF3m could regulate cell-cycle, epithelial–mesenchymal transition and apoptosis-related proteins. Combined with public databases and RT-qPCR, 14 genes were identified to be modulated by eIF3m in the development of TNBC.

Conclusions

eIF3m is an unfavorable indicator of TNBC, and plays a vital role in the process of TNBC tumorigenesis.

Re-evaluation of the 18 non-human protein standards used to create the empirical statistical model for decoy library searching

The Empirical Statistical Model (ESM) for decoy library searching fused the expected amino acid sequence of 18 non-human protein standards to a human decoy library. The ESM assumed a priori the standards were pure such that only the 18 nominal proteins were true positive, all other proteins were false positive, there was no overlap in the peptides of non-human proteins versus human proteins, and that the score distribution of individual peptides would resolve true positive from false positive results or noise. The results of random and independent sampling by LC-ESI-MS/MS indicated that the fundamental assumptions of the ESM were not in good agreement with the actual purity of the commercial test standards and so the method showed a 99.7% false negative rate. The ESM for decoy library searching apparently showed poor agreement with SDS-PAGE using silver staining, goodness of fit of MS/MS spectra by X!TANDEM, FDR correction by Benjamini and Hochberg, or comparison to the observation frequency of null random MS/MS spectra, that all confirmed the standards contain hundreds of proteins with a low FDR of primary structural identification. The protein observation frequency increased with abundance and the log₁₀ precursor intensity distributions were Gaussian and nearly ideal for relative quantification.

The proteome and its dynamics: A missing piece for integrative multi-omics in schizophrenia

The complex and heterogeneous pathophysiology of schizophrenia can be deconstructed by integration of large-scale datasets encompassing genes through behavioral phenotypes. Genome-wide datasets are now available for genetic, epigenetic and transcriptomic variations in schizophrenia, which are then analyzed by newly devised systems biology algorithms. A missing piece, however, is the inclusion of information on the proteome and its dynamics in schizophrenia. Proteomics has lagged behind omics of the genome, transcriptome and epigenome since analytic platforms were relatively less robust for proteins. There has been remarkable progress, however, in the instrumentation of liquid chromatography (LC) and mass spectrometry (MS) (LCMS), experimental paradigms and bioinformatics of the proteome. Here, we present a summary of methodological innovations of recent years in MS based proteomics and the power of new generation proteomics, review proteomics studies that have been conducted in schizophrenia to date, and propose how such data can be analyzed and integrated with other omics results. The function of a protein is determined by multiple molecular properties, i.e., subcellular localization, posttranslational modification (PTMs) and protein-protein interactions (PPIs). Incorporation of these properties poses additional challenges in proteomics and their integration with other omics; yet is a critical next step to close the loop of multi-omics integration. In sum, the recent advent of high-throughput proteome characterization technologies and novel mathematical approaches enable us to incorporate functional properties of the proteome to offer a comprehensive multi-omics based understanding of schizophrenia pathophysiology.

The plasma peptides of breast versus ovarian cancer

Background

There is a need to demonstrate a proof of principle that proteomics has the capacity to analyze plasma from breast cancer versus other diseases and controls in a multisite clinical trial design. The peptides or proteins that show a high observation frequency, and/or precursor intensity, specific to breast cancer plasma might be discovered by comparison to other diseases and matched controls. The endogenous tryptic peptides of breast cancer plasma were compared to ovarian cancer, female normal, sepsis, heart attack, Alzheimer's and multiple sclerosis along with the institution-matched normal and control samples collected directly onto ice.

Methods

Endogenous tryptic peptides were extracted from individual breast cancer and control EDTA plasma samples in a step gradient of acetonitrile, and collected over preparative C18 for LC-ESI-MS/MS with a set of LTQ XL linear quadrupole ion traps working together in parallel to randomly and independently sample clinical populations. The MS/MS spectra were fit to fully tryptic peptides or phosphopeptides within proteins using the X!TANDEM algorithm. The protein observation frequency was counted using the SEQUEST algorithm after selecting the single best charge state and peptide sequence for each MS/MS spectra. The observation frequency was subsequently tested by Chi Square analysis. The log₁₀ precursor intensity was compared by ANOVA in the R statistical system.

Results

Peptides and/or phosphopeptides of common plasma proteins such as APOE, C4A, C4B, C3, APOA1, APOC2, APOC4, ITIH3 and ITIH4 showed increased observation frequency and/or precursor intensity in breast cancer. Many cellular proteins also showed large changes in frequency by Chi Square (χ² > 100, p < 0.0001) in the breast cancer samples such as CPEB1, LTBP4, HIF-1A, IGHE, RAB44, NEFM, C19orf82, SLC35B1, 1D12A, C8orf34, HIF1A, OCLN, EYA1, HLA-DRB1, LARS, PTPDC1, WWC1, ZNF562, PTMA, MGAT1, NDUFA1, NOGOC, OR1E1, OR1E2, CFI, HSA12, GCSH, ELTD1, TBX15, NR2C2, FLJ00045, PDLIM1, GALNT9, ASH2L, PPFIBP1, LRRC4B, SLCO3A1, BHMT2, CS, FAM188B2, LGALS7, SAT2, SFRS8, SLC22A12, WNT9B, SLC2A4, ZNF101, WT1, CCDC47, ERLIN1, SPFH1, EID2, THOC1, DDX47, MREG, PTPRE, EMILIN1, DKFZp779G1236 and MAP3K8 among others. The protein gene symbols with large Chi Square values were significantly enriched in proteins that showed a complex set of previously established functional and structural relationships by STRING analysis. An increase in mean precursor intensity of peptides was observed for QSER1 as well as SLC35B1, IQCJ-SCHIP1, MREG, BHMT2, LGALS7, THOC1, ANXA4, DHDDS, SAT2, PTMA and FYCO1 among others. In contrast, the QSER1 peptide QPKVKAEPPPK was apparently specific to ovarian cancer.

Conclusion

There was striking agreement between the breast cancer plasma peptides and proteins discovered by LC-ESI-MS/MS with previous biomarkers from tumors, cells lines or body fluids by genetic or biochemical methods. The results indicate that variation in plasma peptides from breast cancer versus ovarian cancer may be directly discovered by LC-ESI-MS/MS that will be a powerful tool for clinical research. It may be possible to use a battery of sensitive and robust linear quadrupole ion traps for random and independent sampling of plasma from a multisite clinical trial.

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.

LOXL3 Function Beyond Amino Oxidase and Role in Pathologies, Including Cancer

Lysyl oxidase like 3 (LOXL3) is a copper-dependent amine oxidase responsible for the crosslinking of collagen and elastin in the extracellular matrix. LOXL3 belongs to a family including other members: LOX, LOXL1, LOXL2, and LOXL4. Autosomal recessive mutations are rare and described in patients with Stickler syndrome, early-onset myopia and non-syndromic cleft palate. Along with an essential function in embryonic development, multiple biological functions have been attributed to LOXL3 in various pathologies related to amino oxidase activity. Additionally, various novel roles have been described for LOXL3, such as the oxidation of fibronectin in myotendinous junction formation, and of deacetylation and deacetylimination activities of STAT3 to control of inflammatory response. In tumors, three distinct roles were described: (1) LOXL3 interacts with SNAIL and contributes to proliferation and metastasis by inducing epithelial-mesenchymal transition in pancreatic ductal adenocarcinoma cells; (2) LOXL3 is localized predominantly in the nucleus associated with invasion and poor gastric cancer prognosis; (3) LOXL3 interacts with proteins involved in DNA stability and mitosis completion, contributing to melanoma progression and sustained proliferation. Here we review the structure, function and activity of LOXL3 in normal and pathological conditions and discuss the potential of LOXL3 as a therapeutic target in various diseases.