Quantification of the Lamin A/C Transcript Variants in Cancer Cell Lines by Targeted Absolute Quantitative Proteomics and Correlation with mRNA Expression

Al-Qahtani, Wedad Saeed; Abduljabbar, Mai; AlSuhaibani, Entissar S.; Rahman, Anas M. Abdel; Aljada, Ahmad

doi:10.3390/ijms20081902

Cited by 10 publications

(9 citation statements)

References 35 publications

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“…The signature peptides for the key proteins were selected based on their involvement in the network and pathway analyses as described earlier ( 17 ). Four significantly differentially regulated proteins between the proteomics profiles of the study groups were selected for the overall expression validation.…”

Section: Resultsmentioning

confidence: 99%

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Proteomics Profiling to Distinguish DOCK8 Deficiency From Atopic Dermatitis

et al. 2021

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Dedicator of cytokinesis 8 deficiency is an autosomal recessive primary immune deficiency disease belonging to the group of hyperimmunoglobulinemia E syndrome (HIES). The clinical phenotype of dedicator of cytokinesis 8 (DOCK8) deficiency, characterized by allergic manifestations, increased infections, and increased IgE levels, overlaps with the clinical presentation of atopic dermatitis (AD). Despite the identification of metabolomics and cytokine biomarkers, distinguishing between the two conditions remains clinically challenging. The present study used a label-free untargeted proteomics approach using liquid-chromatography mass spectrometry with network pathway analysis to identify the differentially regulated serum proteins and the associated metabolic pathways altered between the groups. Serum samples from DOCK8 (n = 10), AD (n = 9) patients and healthy control (Ctrl) groups (n = 5) were analyzed. Based on the proteomics profile, the PLS-DA score plot between the three groups showed a clear group separation and sample clustering (R2 = 0.957, Q2 = 0.732). Significantly differentially abundant proteins (p < 0.05, FC cut off 2) were identified between DOCK8-deficient and AD groups relative to Ctrl (n = 105, and n = 109) and between DOCK8-deficient and AD groups (n = 85). Venn diagram analysis revealed a differential regulation of 24 distinct proteins from among the 85 between DOCK8-deficient and AD groups, including claspin, haptoglobin-related protein, immunoglobulins, complement proteins, fibulin, and others. Receiver-operating characteristic curve (ROC) analysis identified claspin and haptoglobin-related protein, as potential biomarkers with the highest sensitivity and specificity (AUC = 1), capable of distinguishing between patients with DOCK8 deficiency and AD. Network pathway analysis between DOCK8-deficiency and AD groups revealed that the identified proteins centered around the dysregulation of ERK1/2 signaling pathway. Herein, proteomic profiling of DOCK8-deficiency and AD groups was carried out to determine alterations in the proteomic profiles and identify a panel of the potential proteomics biomarker with possible diagnostic applications. Distinguishing between DOCK8-deficiency and AD will help in the early initiation of treatment and preventing complications.

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Section: Resultsmentioning

confidence: 99%

“…A signature peptide per protein from the proteomics profile was selected as described previously and confirmed using SkyLine Software V3 ( 17 , 18 ). The tryptic digests of patient samples were purified using solid-phase extraction (SPE) ( 19 ).…”

Section: Methodsmentioning

confidence: 99%

Proteomics Profiling to Distinguish DOCK8 Deficiency From Atopic Dermatitis

et al. 2021

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“…Six different significantly dysregulated proteins from the CF 2D DIGE proteomics profile were selected for validation. Signature peptides for these selected proteins were identified using the criteria that we described elsewhere [ 21 ]. The proteins were selected based on their involvement in the protein-protein interaction network pathway.…”

Section: Resultsmentioning

confidence: 99%

“…Six different proteins were selected from the proteomics profile of CF, and a signature peptide per protein was identified using the criteria that we described elsewhere [ 21 ]. These signature peptides were confirmed using SkeyLine Software V3 and synthesized for standard material (GeneMed Synthesis, San Francisco, CA, USA).…”

Section: Methodsmentioning

confidence: 99%

Serum-Based Proteomics Profiling in Adult Patients with Cystic Fibrosis

Benabdelkamel

Alamri

Okla

et al. 2020

IJMS

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Cystic fibrosis (CF), the most common lethal autosomal recessive disorder among Caucasians, is caused by mutations in the CF transmembrane conductance regulator (CFTR) chloride channel gene. Despite significant advances in the management of CF patients, novel disease-related biomarkers and therapies must be identified. We performed serum proteomics profiling in CF patients (n = 28) and healthy subjects (n = 10) using the 2D-DIGE MALDI-TOF proteomic approach. Out of a total of 198 proteins identified, 134 showed a statistically significant difference in abundance and a 1.5-fold change (ANOVA, p < 0.05), including 80 proteins with increased abundance and 54 proteins with decreased abundance in CF patients. A multiple reaction monitoring-mass spectrometry analysis of six differentially expressed proteins identified by a proteomic approach (DIGE-MALD-MS) showed a significant increase in C3 and CP proteins and a decrease in APOA1, Complement C1, Hp, and RBP4proteins compared with healthy controls. Fifteen proteins were identified as potential biomarkers for CF diagnosis. An ingenuity pathway analysis of the differentially regulated proteins indicates that the central nodes dysregulated in CF subjects involve pro-inflammatory cytokines, ERK1/2, and P38 MAPK, which are primarily involved in catalytic activities and metabolic processes. The involved canonical pathways include those related to FXR/RXR, LXR/RXR, acute phase response, IL12, nitric oxide, and reactive oxygen species in macrophages. Our data support the current efforts toward augmenting protease inhibitors in patients with CF. Perturbations in lipid and vitamin metabolism frequently observed in CF patients may be partly due to abnormalities in their transport mechanism.

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“…Six significantly dysregulated proteins from the 2D-DIGE proteomic profile were selected for validation. Signature peptides for the selected proteins were identified using criteria described previously [26]. Proteins were selected based on their involvement in the protein-protein interaction network pathway.…”

Section: Multiple Reaction Monitoring (Mrm) Mass Spectrometrymentioning

confidence: 99%

Tissue-Based Proteomic Profiling in Patients with Hyperplasia and Endometrial Cancer

Akkour

Alanazi

Alfadda

et al. 2022

Cells

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Uterine cancers are among the most prevalent gynecological malignancies, and endometrial cancer (EC) is the most common in this group. This study used tissue-based proteomic profiling analysis in patients with endometrial cancer and hyperplasia, and control patients. Conventional 2D gel electrophoresis, followed by a mass spectrometry approach with bioinformatics, including a network pathway analysis pipeline, was used to identify differentially expressed proteins and associated metabolic pathways between the study groups. Thirty-six patients (twelve with endometrial cancer, twelve with hyperplasia, and twelve controls) were enrolled in this study. The mean age of the participants was 46–75 years. Eighty-seven proteins were significantly differentially expressed between the study groups, of which fifty-three were significantly differentially regulated (twenty-eight upregulated and twenty-five downregulated) in the tissue samples of EC patients compared to the control (Ctrl). Furthermore, 26 proteins were significantly dysregulated (8 upregulated and 18 downregulated) in tissue samples of hyperplasia (HY) patients compared to Ctrl. Thirty-two proteins (nineteen upregulated and thirteen downregulated) including desmin, peptidyl prolyl cis-trans isomerase A, and zinc finger protein 844 were downregulated in the EC group compared to the HY group. Additionally, fructose bisphosphate aldolase A, alpha enolase, and keratin type 1 cytoskeletal 10 were upregulated in the EC group compared to those in the HY group. The proteins identified in this study were known to regulate cellular processes (36%), followed by biological regulation (16%). Ingenuity pathway analysis found that proteins that are differentially expressed between EC and HY are linked to AKT, ACTA2, and other signaling pathways. The panels of protein markers identified in this study could be used as potential biomarkers for distinguishing between EC and HY and early diagnosis and progression of EC from hyperplasia and normal patients.

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Quantification of the Lamin A/C Transcript Variants in Cancer Cell Lines by Targeted Absolute Quantitative Proteomics and Correlation with mRNA Expression

Cited by 10 publications

References 35 publications

Proteomics Profiling to Distinguish DOCK8 Deficiency From Atopic Dermatitis

Proteomics Profiling to Distinguish DOCK8 Deficiency From Atopic Dermatitis

Serum-Based Proteomics Profiling in Adult Patients with Cystic Fibrosis

Tissue-Based Proteomic Profiling in Patients with Hyperplasia and Endometrial Cancer

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