SMURF2 predisposes cancer cell toward ferroptosis in GPX4-independent manners by promoting GSTP1 degradation.

Ferroptosis is a non-apoptotic form of regulated cell death. Glutathione (GSH) peroxidase 4 (GPX4) and GSH-independent ferroptosis suppressor protein 1 (FSP1) have been identified as major defenses. Here, we uncover a protective mechanism mediated by GSH S-transferase P1 (GSTP1) by monitoring proteinomic dynamics during ferroptosis. Dramatic downregulation of GSTP1 is caused by SMURF2-mediated GSTP1 ubiquitination and degradation at early stages of ferroptosis. Intriguingly, GSTP1 acts in GPX4- and FSP1-independent manners by catalyzing GSH conjugation of 4-hydroxynonenal and detoxifying lipid hydroperoxides via selenium-independent GSH peroxidase activity. Genetic modulation of the SMURF2/GSTP1 axis or the pharmacological inhibition of GSTP1's catalytic activity sensitized tumor responses to Food and Drug Administration (FDA)-approved ferroptosis-inducing drugs both in vitro and in vivo. GSTP1 expression also confers resistance to immune checkpoint inhibitors by blunting ferroptosis. Collectively, these findings demonstrate a GPX4/FSP1-independent cellular defense mechanism against ferroptosis and suggest that targeting SMURF2/GSTP1 to sensitize cancer cells to ferroptosis has potential as an anticancer therapy.

iASPP suppresses Gp78-mediated TMCO1 degradation to maintain Ca2+ homeostasis and control tumor growth and drug resistance.

Ca2+ release from the endoplasmic reticulum (ER) is an essential event in the modulation of Ca2+ homeostasis, which is coordinated by multiple biological processes, ranging from cell proliferation to apoptosis. Deregulated Ca2+ homeostasis is linked with various cancer hallmarks; thus, uncovering the mechanisms underlying Ca2+ homeostasis dynamics may lead to new anticancer treatment strategies. Here, we demonstrate that a reported Ca2+-channel protein TMCO1 (transmembrane and coiled-coil domains 1) is overexpressed in colon cancer tissues at protein levels but not at messenger RNA levels in colon cancer. Further study revealed that TMCO1 is a substrate of ER-associated degradation E3 ligase Gp78. Intriguingly, Gp78-mediated TMCO1 degradation at K186 is under the control of the iASPP (inhibitor of apoptosis-stimulating protein of p53) oncogene. Mechanistically, iASPP robustly reduces ER Ca2+ stores, mainly by competitively binding with Gp78 and interfering with Gp78-mediated TMCO1 degradation. A positive correlation between iASPP and TMCO1 proteins is further validated in human colon tissues. Inhibition of iASPP-TMCO1 axis promotes cytosolic Ca2+ overload-induced apoptotic cell death, reducing tumor growth both in vitro and in vivo. Thus, iASPP-TMCO1 represents a promising anticancer treatment target by modulating Ca2+ homeostasis.

Identification of pyruvic and maleic acid as potential markers for disease activity and prognosis in chronic urticaria.

BACKGROUND: Population-based studies have highlighted the link between chronic urticaria (CU) and metabolic syndrome, and metabolic alterations have been revealed in CU. However, to our knowledge, a comprehensive metabolomics study on a large cohort of patients with CU has not been reported. OBJECTIVE: We sought to explore the underlying metabolic subtypes and novel metabolite biomarkers for CU diagnosis and therapy. METHODS: Plasma samples from 80 patients with CU and 82 healthy controls were collected for metabolomics quantification and bioinformatics analysis. Another independent cohort consisting of 144 patients with CU was studied to validate the findings. Bone marrow-derived mast cells and mice with IgE-induced passive cutaneous anaphylaxis were used for in vitro and in vivo experiments, respectively. RESULTS: We observed clear metabolome differences between CU patients and healthy controls. Meanwhile, differential metabolites N6-acetyl-l-lysine, l-aspartate, maleic acid, and pyruvic acid were used to construct random forest classifiers and achieved area under receiver operating characteristic curve values greater than 0.85, suggesting their potential as diagnostic biomarkers of CU. More importantly, by exploring the underlying metabolic subtypes of CU, we found that the low abundance of pyruvic acid and maleic acid was significantly related to the activity of CU, poor efficacy of second-generation H1 antihistamines, and short relapse-free time. The results were validated in the independent cohort. Moreover, supplementation with pyruvate or maleate could significantly attenuate IgE-mediated mast cell activation in vitro and in vivo. CONCLUSIONS: Plasma pyruvic acid and maleic acid may be effective biomarkers for predicting disease activity, therapeutic efficacy, and prognosis for patients with CU.

Lipidomic studies revealing serological markers associated with the occurrence of retinopathy in type 2 diabetes.

PURPOSE: The duration of type 2 diabetes mellitus (T2DM) and blood glucose levels have a significant impact on the development of T2DM complications. However, currently known risk factors are not good predictors of the onset or progression of diabetic retinopathy (DR). Therefore, we aimed to investigate the differences in the serum lipid composition in patients with T2DM, without and with DR, and search for potential serological indicators associated with the development of DR. METHODS: A total of 622 patients with T2DM hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Xi'an JiaoTong University were selected as the discovery set. One-to-one case-control matching was performed according to the traditional risk factors for DR (i.e., age, duration of diabetes, HbA1c level, and hypertension). All cases with comorbid chronic kidney disease were excluded to eliminate confounding factors. A total of 42 pairs were successfully matched. T2DM patients with DR (DR group) were the case group, and T2DM patients without DR (NDR group) served as control subjects. Ultra-performance liquid chromatography-mass spectrometry (LC-MS/MS) was used for untargeted lipidomics analysis on serum, and a partial least squares discriminant analysis (PLS-DA) model was established to screen differential lipid molecules based on variable importance in the projection (VIP) > 1. An additional 531 T2DM patients were selected as the validation set. Next, 1:1 propensity score matching (PSM) was performed for the traditional risk factors for DR, and a combined 95 pairings in the NDR and DR groups were successfully matched. The screened differential lipid molecules were validated by multiple reaction monitoring (MRM) quantification based on mass spectrometry. RESULTS: The discovery set showed no differences in traditional risk factors associated with the development of DR (i.e., age, disease duration, HbA1c, blood pressure, and glomerular filtration rate). In the DR group compared with the NDR group, the levels of three ceramides (Cer) and seven sphingomyelins (SM) were significantly lower, and one phosphatidylcholine (PC), two lysophosphatidylcholines (LPC), and two SMs were significantly higher. Furthermore, evaluation of these 15 differential lipid molecules in the validation sample set showed that three Cer and SM(d18:1/24:1) molecules were substantially lower in the DR group. After excluding other confounding factors (e.g., sex, BMI, lipid-lowering drug therapy, and lipid levels), multifactorial logistic regression analysis revealed that a lower abundance of two ceramides, i.e., Cer(d18:0/22:0) and Cer(d18:0/24:0), was an independent risk factor for the occurrence of DR in T2DM patients. CONCLUSION: Disturbances in lipid metabolism are closely associated with the occurrence of DR in patients with T2DM, especially in ceramides. Our study revealed for the first time that Cer(d18:0/22:0) and Cer(d18:0/24:0) might be potential serological markers for the diagnosis of DR occurrence in T2DM patients, providing new ideas for the early diagnosis of DR.

A biomarker panel of secondary hypertension is simultaneously quantified by coupling of magnetic solid-phase extraction and liquid chromatography-tandem mass spectrometry.

RATIONALE: Secondary hypertension is often caused by activation of complex multi-organ endocrine systems, while renin activity indicated by angiotensins (Angs), aldosterone (ALD) and cortisol (COR) in such systems are generally accepted as its diagnostic markers. As antibody-based methods cannot offer comparable quantification for these biomarkers, a liquid chromatography (LC)-tandem mass spectrometry (MS/MS)-based approach was developed to quantify them simultaneously and accurately. METHODS: Five different beads for magnetic solid-phase extraction (MSPE) were evaluated towards their enrichment efficiency for these biomarkers. An LC system with optimized elution gradient and a triple-quadrupole MS with tuned parameters were coupled to quantitatively monitor the extracted analytes. The method performance was further examined such as linearity, precision, stability, recovery rate and matrix effect. Based on the developed method, the abundance of Ang II, ALD and COR in plasma was measured and the quantification was compared with that derived from commercial ELISA kits. RESULTS: As compared with other MSPEs, Angs, ALD and COR were highly enriched by the HLB magnetic beads with satisfactory recoveries. These analytes were simultaneously quantified by LC/MS/MS and all the method parameters for quantification were well matched with the requirements of clinical testing. Comparison of the quantitative results derived from ELISA and LC/MS/MS exhibited that the two methods offered basically comparable values with Pearson r values at 0.896, 0.895 and 0.835, respectively. The stability test for plasma Angs at room temperature indicated that the abundance of Ang II was relatively stable within 3 h, whereas that of Ang I and Ang 1-7 was time-dependently changed. CONCLUSIONS: Coupling of HLB beads and LC/MS/MS thus enables simultaneous quantification of a set of biomarkers related to secondary hypertension.

Lipidomic profiling reveals metabolic signatures in psoriatic skin lesions.

Psoriasis is a chronic immune-mediated inflammatory disease. Lipids play an important role in regulating the inflammatory response. However, the alteration of lipids involved in psoriasis particular in skin lesions remain unclear. Here, we performed the lipidomics to investigate lipid profiling in the skin lesions of the imiquimod-induced psoriasis-like dermatitis and psoriasis patients. The findings showed that ceramides phosphate (CerP) and ceramides were enriched in psoriatic lesions compared with controls from both psoriasis patients and psoriasis-like mouse model. Psoriasis patients were classified into two subtypes, the CC1 and CC2, by consensus clustering of these lipid signatures. The CC1 was characterized by the higher levels of CerP, uric acid, and more severe psoriasis, compared with CC2 subtype. Interestingly, ceramide-1-phosphate (C1P), dramatically enriched in CC1 subtype, facilitated imiquimod-induced psoriasis-like inflammatory responses. Mechanistically, C1P induced the expression of inflammatory factors and activated DNA replication and cell cycle signaling pathways in the primary keratinocytes. Inhibiting the production of C1P with ceramide kinase inhibitor effectively alleviated the imiquimod-induced psoriasis-like inflammation. Taken together, we described the landscape of lipids alteration and established lipids classification based on pattern of abundance of lipids in psoriatic skin lesions. Suppression of C1P pathway is a novel potential strategy for psoriasis treatment.

LC-MS/MS-Based Absolute Quantitation of Hemoglobin Subunits from Dried Blood Spots Reveals Novel Biomarkers for α-Thalassemia Silent Carriers.

Identification of α-thalassemia silent carriers is challenging with conventional phenotype-based screening methods. A liquid chromatography tandem mass spectrometry (LC-MS/MS)-based approach may offer novel biomarkers to address this conundrum. In this study, we collected dried blood spot samples from individuals with three α-thalassemia subtypes for biomarker discovery and validation. We observed differential expression patterns of hemoglobin subunits among various α-thalassemia subtypes and normal controls through proteomic profiling of 51 samples in the discovery phase. Then, we developed and optimized a multiple reaction monitoring (MRM) assay to measure all detectable hemoglobin subunits. The validation phase was conducted in a cohort of 462 samples. Among the measured hemoglobin subunits, subunit µ was significantly upregulated in all the α-thalassemia groups with distinct fold changes. The hemoglobin subunit µ exhibits great potential as a novel biomarker for α-thalassemia, especially for silent α-thalassemia. We constructed predictive models based on the concentrations of hemoglobin subunits and their ratios to classify the various subtypes of α-thalassemia. In the binary classification problems of silent α-thalassemia vs normal, non-deletional α-thalassemia vs normal, and deletional α-thalassemia vs normal, the best performance of the models achieved average ROCAUCs of 0.9505, 0.9430, and 0.9976 in the cross-validation, respectively. In the multiclass model, the best performance achieved an average ROCAUC of 0.9290 in cross-validation. The performance of our MRM assay and models demonstrated that the hemoglobin subunit µ would play a vital role in screening silent α-thalassemia in clinical practice.

Maternal plasma diacylglycerols and triacylglycerols in the prediction of gestational diabetes mellitus.

OBJECTIVE: To define the lipidomic profile in plasma across pregnancy, and identify lipid biomarkers for gestational diabetes mellitus (GDM) prediction in early pregnancy. DESIGN: Case-control study. SETTING: Tertiary referral maternity unit. POPULATION OR SAMPLE: Plasma samples from 100 GDM and 100 normal glucose tolerance (NGT) women, divided into a training set (GDM first trimester = 50, GDM second trimester = 40, NGT first trimester = 50, NGT second trimester = 50) and a validation set (GDM first trimester = 45, GDM second trimester = 34, NGT first trimester = 44, NGT second trimester = 40). METHODS: Plasma samples were collected in the first (11+0 to 13+6 weeks), second (19+0 to 24+6 weeks), and third trimesters (30+0 to 34+6 weeks), and tested by ultra-high-performance liquid chromatography coupled with electrospray ionisation-quadrupole-time of flight-mass spectrometry; The GDM prediction model was established by the machine-learning method of random forest. MAIN OUTCOME MEASURES: Gestational diabetes mellitus. RESULTS: In both the GDM and NGT group, lyso-glycerophospholipids were down-regulated, whereas ceramides, sphingomyelins, cholesteryl ester, diacylglycerols (DGs) and triacylglycerols (TGs) and glucosylceramide were up-regulated across the three trimesters of pregnancy. In the training dataset, seven TGs and five DGs demonstrated good performance in the prediction of GDM in the first and second trimesters (area under the curve [AUC] = 0.96 with 95% confidence interval [CI] of 0.93-1 and AUC = 0.97 with 95% CI of 0.95-1, respectively), independent of maternal body mass index (BMI) and ethnicity. In the validation dataset, the predictive model achieved an AUC of 0.88 and 0.94 at the first and second trimesters, respectively. CONCLUSIONS: Our results have proposed new lipid biomarkers for the first trimester prediction of GDM, independent of ethnicity and BMI.

Proteomic Profiling of Gastric Signet Ring Cell Carcinoma Tissues Reveals Characteristic Changes of the Complement Cascade Pathway.

Signet ring cell carcinoma (SRCC) is a histological subtype of gastric cancer with distinct features in multiple aspects compared with adenocarcinomas (ACs). The lack of a systematic molecular overview of this disease has led to slow progress in its clinical practice. In the present proteomics study, gastric tissues were collected from tumors and adjacent tissues, including 14 SRCCs and 34 ACs, and laser capture microdissection (LCM) was employed to eradicate the cellular heterogeneity of the tissues. The proteomes of tissues were profiled by data-independent acquisition (DIA) mass spectrometry (MS). Based on the over 6000 proteins quantified, univariate analysis and pathway enrichment revealed that some proteins and pathways demonstrated differences between SRCC and ACs. Importantly, the upregulation of a majority of complement-related proteins was notable for SRCC but not for ACs. A hypothesis, based on the proteomics evidence, was proposed that the complement cascade was evoked in the SRCC microenvironment upon infiltration, and the SRCC cells survived the complement cytotoxicity by secreting endogenous negative regulators. Moreover, an attempt was made to establish appropriate cell models for gastric SRCC through proteomic comparison of the 15 gastric cell lines and gastric tumors. The predictions of a supervised classifier suggested that none of these gastric cell lines qualified to mimic SRCC. This study discovered that the complement cascade is activated at a higher level in gastric SRCC than in ACs.

Pathway attenuation of fatty acid beta-oxidation in the skeletal muscle of a type 2 diabetic mouse model.

RATIONALE: Whether catabolic abnormalities of fatty acids exist in the skeletal muscle of type 2 diabetes mellitus (T2DM) has not been determined. In this study, we postulated that a systematic evaluation of the protein abundance and metabolic activity related to fatty acids in the skeletal muscle tissues of a T2DM mouse model was feasible to address this question. METHODS: Mitochondria were extracted from wild-type (WT) and db/db mice followed by quantitative analysis of the proteins involved in mitochondrial fatty acid oxidation (mFAO). The pathway activity of mFAO in skeletal muscle tissues was monitored in vitro using mass spectrometry, and tissue lipidomic analysis was conducted in profiling and target mode to distinguish the levels of long-chain acylcarnitines between WT and db/db mice. RESULTS: Two proteins related to the mFAO pathway were significantly downregulated in the skeletal muscle mitochondria of db/db mice. The measurement of mFAO pathway activity in vitro revealed that the abundance of long-chain acylcarnitines (C14 to C18) in db/db mice was lower than that in WT mice, and the determination of acylcarnitines in skeletal muscle tissues in vivo revealed that most long-chain acylcarnitines were decreased in db/db mice. CONCLUSIONS: The findings of lower abundance of ACAD9 and CPT1B, reduced activity of the mFAO pathway in vitro and decreased acylcarnitines in vivo firmly support that the mFAO pathway in the skeletal muscle of diabetic mice is attenuated, possibly resulting in cell/tissue dysfunction in diabetes.

Peptide Biosynthesis with Stable Isotope Labeling from a Cell-free Expression System for Targeted Proteomics with Absolute Quantification.

Because of its specificity and sensitivity, targeted proteomics using mass spectrometry for multiple reaction monitoring is a powerful tool to detect and quantify pre-selected peptides from a complex background and facilitates the absolute quantification of peptides using isotope-labeled forms as internal standards. How to generate isotope-labeled peptides remains an urgent challenge for accurately quantitative targeted proteomics on a large scale. Herein, we propose that isotope-labeled peptides fused with a quantitative tag could be synthesized through an expression system in vitro, and the homemade peptides could be enriched by magnetic beads with tag-affinity and globally quantified based on the corresponding multiple reaction monitoring signals provided by the fused tag. An Escherichia coli cell-free protein expression system, protein synthesis using recombinant elements, was adopted for the synthesis of isotope-labeled peptides fused with Strep-tag. Through a series of optimizations, we enabled efficient expression of the labeled peptides such that, after Strep-Tactin affinity enrichment, the peptide yield was acceptable in scale for quantification, and the peptides could be completely digested by trypsin to release the Strep-tag for quantification. Moreover, these recombinant peptides could be employed in the same way as synthetic peptides for multiple reaction monitoring applications and are likely more economical and useful in a laboratory for the scale of targeted proteomics. As an application, we synthesized four isotope-labeled glutathione S-transferase (GST) peptides and added them to mouse sera pre-treated with GST affinity resin as internal standards. A quantitative assay of the synthesized GST peptides confirmed the absolute GST quantification in mouse sera to be measurable and reproducible.

The serum protein responses to treatment with Xiaoke Pill and Glibenclamide in type 2 diabetes patients.

AIM: The Xiaoke Pill containing Chinese herb extracts and Glibenclamide, is used in therapy for type 2 diabetes mellitus (T2DM), and is effective in reducing the risk of hypoglycemia and improving diabetes symptoms compared with Glibenclamide. We describe a quantitative proteomics project to measure the T2DM serum proteome response to the Xiaoke Pill and Glibenclamide. METHODS: Based on a recently conducted 48-week clinical trial comparing the safety and efficacy of Glibenclamide (n = 400) and Xiaoke Pill (n = 400), after matching for age, sex, BMI, drug dose and whether hypoglycemia occurred, 32 patients were selected for the serum based proteomic analysis and divided into four groups (with/without hypoglycemia treated with Xiaoke Pill or Glibenclamide, n = 8 for each group). We screened the differential serum proteins related to treatments and the onset of hypoglycemia using the iTRAQ labeling quantitative proteomics technique. Baseline and follow-up samples were used. RESULTS: The quantitative proteomics experiments demonstrated that 25 and 21 proteins differed upon treatment with the Xiaoke Pill in patients without and with hypoglycemia, respectively, while 24 and 25 proteins differed upon treatment with Glibenclamide in patients without and with hypoglycemia, respectively. The overlap of different proteins between the patients with and without hypoglycemia given the same drug treatment was much greater than between the patients given different drug treatments. CONCLUSIONS: We conclude that the serum proteins response to the two different anti-diabetic drug treatments may serve as a sensitive biomarker for evaluation of the therapeutic effects and continue investigations into the mechanism.

A Comprehensive Investigation toward the Indicative Proteins of Bladder Cancer in Urine: From Surveying Cell Secretomes to Verifying Urine Proteins.

Urine is an ideal material to study the cancer-related protein biomarkers in bladder, whereas exploration to these candidates is confronting technique challenges. Herein, we propose a comprehensive strategy of searching the urine proteins related with bladder cancer. The strategy consists of three core combinations, screening the biomarker candidates in the secreted proteins derived from the bladder cancer cell lines and verifying them in patient urines, defining the differential proteins through two-dimensional electrophoresis (2DE) and isobaric tags for relative and absolute quantitation (iTRAQ) coupled with LC-MS/MS, and implementing quantitative proteomics of profiling and targeting analysis. With proteomic survey, a total of 700 proteins were found with their abundance of secreted proteins in cancer cell lines different from normal, while 87 proteins were identified in the urine samples. The multiple reaction monitoring (MRM)-based quantification was adapted in verifying the bladder cancer related proteins in individual urine samples, resulting in 10 differential urine proteins linked with the cancer. Of these candidates, receiver operating characteristic analysis revealed that the combination of CO3 and LDHB was more sensitive as the cancer indicator than other groups. The discovery of the bladder cancer indicators through our strategy has paved an avenue to further biomarker validation.

Biomarker Discovery and Verification of Esophageal Squamous Cell Carcinoma Using Integration of SWATH/MRM.

We propose an efficient integration of SWATH with MRM for biomarker discovery and verification when the corresponding ion library is well established. We strictly controlled the false positive rate associated with SWATH MS signals and carefully selected the target peptides coupled with SWATH and MRM. We collected 10 samples of esophageal squamous cell carcinoma (ESCC) tissues paired with tumors and adjacent regions and quantified 1758 unique proteins with FDR 1% at protein level using SWATH, in which 467 proteins were abundance-dependent with ESCC. After carefully evaluating the SWATH MS signals of the up-regulated proteins, we selected 120 proteins for MRM verification. MRM analysis of the pooled and individual esophageal tissues resulted in 116 proteins that exhibited similar abundance response modes to ESCC that were acquired with SWATH. Because the ESCC-related proteins consisted of a high percentile of secreted proteins, we conducted the MRM assay on patient sera that were collected from pre- and postoperation. Of the 116 target proteins, 42 were identified in the ESCC sera, including 11 with lowered abundances postoperation. Coupling SWATH and MRM is thus feasible and efficient for the discovery and verification of cancer-related protein biomarkers.

Appraisal of the Missing Proteins Based on the mRNAs Bound to Ribosomes.

Considering the technical limitations of mass spectrometry in protein identification, the mRNAs bound to ribosomes (RNC-mRNA) are assumed to reflect the mRNAs participating in the translational process. The RNC-mRNA data are reasoned to be useful for appraising the missing proteins. A set of the multiomics data including free-mRNAs, RNC-mRNAs, and proteomes was acquired from three liver cancer cell lines. On the basis of the missing proteins in neXtProt (release 2014-09-19), the bioinformatics analysis was carried out in three phases: (1) finding how many neXtProt missing proteins have or do not have RNA-seq and/or MS/MS evidence, (2) analyzing specific physicochemical and biological properties of the missing proteins that lack both RNA-seq and MS/MS evidence, and (3) analyzing the combined properties of these missing proteins. Total of 1501 missing proteins were found by neither RNC-mRNA nor MS/MS in the three liver cancer cell lines. For these missing proteins, some are expected higher hydrophobicity, unsuitable detection, or sensory functions as properties at the protein level, while some are predicted to have nonexpressing chromatin structures on the corresponding gene level. With further integrated analysis, we could attribute 93% of them (1391/1501) to these causal factors, which result in the expression products scarcely detected by RNA-seq or MS/MS.

Omics evidence: single nucleotide variants transmissions on chromosome 20 in liver cancer cell lines.

Cancer genomics unveils many cancer-related mutations, including some chromosome 20 (Chr.20) genes. The mutated messages have been found in the corresponding mRNAs; however, whether they could be translated to proteins still requires more evidence. Herein, we proposed a transomics strategy to profile the expression status of human Chr.20 genes (555 in Ensembl v72). The data of transcriptome and translatome (the mRNAs bound with ribosome, translating mRNAs) revealed that ∼80% of the coding genes on Chr.20 were detected with mRNA signals in three liver cancer cell lines, whereas of the proteome identified, only ∼45% of the Chr.20 coding genes were detected. The high amount of overlapping of identified genes in mRNA and RNC-mRNA (ribosome nascent-chain complex-bound mRNAs, translating mRNAs) and the consistent distribution of the abundance averages of mRNA and RNC-mRNA along the Chr.20 subregions in three liver cancer cell lines indicate that the mRNA information is efficiently transmitted from transcriptional to translational stage, qualitatively and quantitatively. Of the 457 genes identified in mRNAs and RNC-mRNA, 136 were found to contain SNVs with 213 sites, and >40% of these SNVs existed only in metastatic cell lines, suggesting them as the metastasis-related SNVs. Proteomics analysis showed that 16 genes with 20 SNV sites were detected with reliable MS/MS signals, and some SNVs were further validated by the MRM approach. With the integration of the omics data at the three expression phases, therefore, we are able to achieve the overall view of the gene expression of Chr.20, which is constructive in understanding the potential trend of encoding genes in a cell line and exploration of a new type of markers related to cancers.

Systematic analyses of the transcriptome, translatome, and proteome provide a global view and potential strategy for the C-HPP.

To estimate the potential of the state-of-the-art proteomics technologies on full coverage of the encoding gene products, the Chinese Human Chromosome Proteome Consortium (CCPC) applied a multiomics strategy to systematically analyze the transciptome, translatome, and proteome of the same cultured hepatoma cells with varied metastatic potential qualitatively and quantitatively. The results provide a global view of gene expression profiles. The 9064 identified high confident proteins covered 50.2% of all gene products in the translatome. Those proteins with function of adhesion, development, reproduction, and so on are low abundant in transcriptome and translatome but absent in proteome. Taking the translatome as the background of protein expression, we found that the protein abundance plays a decisive role and hydrophobicity has a greater influence than molecular weight and isoelectric point on protein detectability. Thus, the enrichment strategy used for low-abundant transcription factors helped to identify missing proteins. In addition, those peptides with single amino acid polymorphisms played a significant role for the disease research, although they might negligibly contribute to new protein identification. The proteome raw and metadata of proteome were collected using the iProX submission system and submitted to ProteomeXchange (PXD000529, PXD000533, and PXD000535). All detailed information in this study can be accessed from the Chinese Chromosome-Centric Human Proteome Database.

Expansion of the ion library for mining SWATH-MS data through fractionation proteomics.

The strategy of sequential window acquisition of all theoretical fragment ion spectra (SWATH) is emerging in the field of label-free proteomics. A critical consideration for the processing of SWATH data is the quality of the ion library (or mass spectrometric reference map). As the availability of open spectral libraries that can be used to process SWATH data is limited, most users currently create their libraries in-house. Herein, we propose an approach to construct an expanded ion library using the data-dependent acquisition (DDA) data generated by fractionation proteomics. We identified three critical elements for achieving a satisfactory ion library during the iterative process of our ion library expansion, including a correction of the retention times (RTs) gained from fractionation proteomics, appropriate integrations of the fractionated proteomics into an ion library, and assessments of the impact of the expanded ion libraries to data mining in SWATH. Using a bacterial lysate as an evaluation material, we employed sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to fractionate the lysate proteins and constructed the expanded ion library using the fractionation proteomics data. Compared with the ion library built from the unfractionated proteomics, approximately 20% more peptides were extracted from the expanded ion library. The extracted peptides, moreover, were acceptable for further quantitative analysis.

Long noncoding RNA HITT coordinates with RGS2 to inhibit PD-L1 translation in T cell immunity.

Programmed cell death ligand 1 (PD-L1) is an immune checkpoint protein frequently expressed in human cancers that contributes to immune evasion through its binding to PD-1 on activated T cells. Unveiling the mechanisms underlying PD-L1 expression is essential for understanding the impact of the immunosuppressive microenvironment and is also crucial for the purpose of reboosting antitumor immunity. However, how PD-L1 is regulated, particularly at translational levels, remains largely unknown. Here, we discovered that a long noncoding RNA (lncRNA), HIF-1α inhibitor at translation level (HITT), was transactivated by E2F transcription factor 1 (E2F1) under IFN-γ stimulation. It coordinated with regulator of G protein signaling 2 (RGS2) in binding to the 5' UTR of PD-L1, resulting in reduced PD-L1 translation. HITT expression enhanced T cell-mediated cytotoxicity both in vitro and in vivo in a PD-L1-dependent manner. The clinical correlation between HITT/PD-L1 and RGS2/PD-L1 expression was also detected in breast cancer tissues. Together, these findings demonstrate the role of HITT in antitumor T cell immunity, highlighting activation of HITT as a potential therapeutic strategy for enhancing cancer immunotherapy.

IntroSpect: Motif-Guided Immunopeptidome Database Building Tool to Improve the Sensitivity of HLA I Binding Peptide Identification by Mass Spectrometry.

Although database search tools originally developed for shotgun proteome have been widely used in immunopeptidomic mass spectrometry identifications, they have been reported to achieve undesirably low sensitivities or high false positive rates as a result of the hugely inflated search space caused by the lack of specific enzymic digestions in immunopeptidome. To overcome such a problem, we developed a motif-guided immunopeptidome database building tool named IntroSpect, which is designed to first learn the peptide motifs from high confidence hits in the initial search, and then build a targeted database for refined search. Evaluated on 18 representative HLA class I datasets, IntroSpect can improve the sensitivity by an average of 76%, compared to conventional searches with unspecific digestions, while maintaining a very high level of accuracy (~96%), as confirmed by synthetic validation experiments. A distinct advantage of IntroSpect is that it does not depend on any external HLA data, so that it performs equally well on both well-studied and poorly-studied HLA types, unlike the previously developed method SpectMHC. We have also designed IntroSpect to keep a global FDR that can be conveniently controlled, similar to a conventional database search. Finally, we demonstrate the practical value of IntroSpect by discovering neoepitopes from MS data directly, an important application in cancer immunotherapies. IntroSpect is freely available to download and use.