SubCellBarCode: Proteome-wide Mapping of Protein Localization and Relocalization.

Subcellular localization is a main determinant of protein function; however, a global view of cellular proteome organization remains relatively unexplored. We have developed a robust mass spectrometry-based analysis pipeline to generate a proteome-wide view of subcellular localization for proteins mapping to 12,418 individual genes across five cell lines. Based on more than 83,000 unique classifications and correlation profiling, we investigate the effect of alternative splicing and protein domains on localization, complex member co-localization, cell-type-specific localization, as well as protein relocalization after growth factor inhibition. Our analysis provides information about the cellular architecture and complexity of the spatial organization of the proteome; we show that the majority of proteins have a single main subcellular location, that alternative splicing rarely affects subcellular location, and that cell types are best distinguished by expression of proteins exposed to the surrounding environment. The resource is freely accessible via www.subcellbarcode.org.

Generation of ENSEMBL-based proteogenomics databases boosts the identification of non-canonical peptides.

SUMMARY: We have implemented the pypgatk package and the pgdb workflow to create proteogenomics databases based on ENSEMBL resources. The tools allow the generation of protein sequences from novel protein-coding transcripts by performing a three-frame translation of pseudogenes, lncRNAs and other non-canonical transcripts, such as those produced by alternative splicing events. It also includes exonic out-of-frame translation from otherwise canonical protein-coding mRNAs. Moreover, the tool enables the generation of variant protein sequences from multiple sources of genomic variants including COSMIC, cBioportal, gnomAD and mutations detected from sequencing of patient samples. pypgatk and pgdb provide multiple functionalities for database handling including optimized target/decoy generation by the algorithm DecoyPyrat. Finally, we have reanalyzed six public datasets in PRIDE by generating cell-type specific databases for 65 cell lines using the pypgatk and pgdb workflow, revealing a wealth of non-canonical or cryptic peptides amounting to >5% of the total number of peptides identified. AVAILABILITY AND IMPLEMENTATION: The software is freely available. pypgatk: https://github.com/bigbio/py-pgatk/ and pgdb: https://nf-co.re/pgdb. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

[Efficacy and safety of low-dose rituximab in treatment of pediatric nephrotic syndrome: a prospective randomized controlled trial]. / ä½Žå‰‚é‡åˆ©å¦¥æ˜”å•æŠ—æ²»ç–—å„¿ç«¥è‚¾ç— ç»¼åˆå¾ç–—æ•ˆåŠå®‰å ¨æ€§çš„å‰çž»æ€§éšæœºå¯¹ç §ç ”ç©¶.

OBJECTIVES: To study the efficacy and safety of repeated application of rituximab (RTX) at a low dose (200 mg/m2) versus the recommended dose (375 mg/m2) for remission maintenance in frequently relapsing nephrotic syndrome (FRNS) or steroid-dependent nephrotic syndrome (SDNS). METHODS: A randomized controlled trial was conducted for 29 children with FRNS/SDNS who received systemic treatment in the Department of Nephrology, Anhui Provincial Children's Hospital, from September 2020 to December 2021. These children were divided into a recommended dose group (n=14) and a low dose group (n=15) using a random number table. The two groups were compared in terms of general characteristics, changes in CD19 expression after RTX treatment, number of relapses, glucocorticoid dose, adverse reactions of RTX, and hospital costs. RESULTS: After RTX treatment, both the low dose group and the recommended dose group achieved B-lymphocyte depletion and had significant reductions in the number of relapses and glucocorticoid dose (P<0.05). The low dose group had a comparable clinical effect to the recommended dose group after RTX treatment (P>0.05), and the low dose group had a significant reduction in hospital costs for the second, third, and fourth times of hospitalization (P<0.05). There were no serious adverse reactions in either group during RTX treatment and late follow-up, and there was no significant difference in adverse reactions between the two groups (P>0.05). CONCLUSIONS: Repeated RTX treatment at a low dose has comparable clinical efficacy and safety to that at the recommended dose and can significantly reduce the number of FRNS/SDNS relapses and the amount of glucocorticoids used, with little adverse effect throughout the treatment cycle. Therefore, it holds promise for clinical application.

Arsenic trioxide increases apoptosis of SK-N-BE (2) cells partially by inducing GPX4-mediated ferroptosis.

BACKGROUND: Neuroblastoma (NB) is the most common extracranial tumor in central nervous system threatening children's health with limited therapeutic options. Arsenic trioxide (ATO) has been identified the cytotoxicity in NB cells but the potential mechanism remains unclear. In this study, we attempted to obtain some insight into the mechanisms of cell death induced by ATO in NB cells. METHODS AND RESULTS: Proteomic analyses found that ATO can affect the signaling pathway associated with ferroptosis, including the upregulation of iron absorption (FTL, FTH1, HO-1), ferritinophagy (LC3, P62, ATG7, NCOA4) and modifier of glutathione synthesis (GCLM); downregulation of glutamine synthetase (GS) and GPX4, which was the critical inhibitor of ferroptosis. Western blot analysis revealing GPX4 expression in SK-N-BE (2) cells decreased after treatment with ATO (7.3 µM), resulting in a loss of GPX4 activity. Furthermore, Ferroptosis inhibitor ferrostatin-1 partially blocked ATO-induced cell death. CONCLUSIONS: Our study revealed that ATO may induce ferroptosis in neuroblastoma cell SK-N-BE (2) by facilitating the downregulation of GPX4, ultimately resulting in iron-dependent oxidative death.

DEqMS: A Method for Accurate Variance Estimation in Differential Protein Expression Analysis.

Quantitative proteomics by mass spectrometry is widely used in biomarker research and basic biology research for investigation of phenotype level cellular events. Despite the wide application, the methodology for statistical analysis of differentially expressed proteins has not been unified. Various methods such as t test, linear model and mixed effect models are used to define changes in proteomics experiments. However, none of these methods consider the specific structure of MS-data. Choices between methods, often originally developed for other types of data, are based on compromises between features such as statistical power, general applicability and user friendliness. Furthermore, whether to include proteins identified with one peptide in statistical analysis of differential protein expression varies between studies. Here we present DEqMS, a robust statistical method developed specifically for differential protein expression analysis in mass spectrometry data. In all data sets investigated there is a clear dependence of variance on the number of PSMs or peptides used for protein quantification. DEqMS takes this feature into account when assessing differential protein expression. This allows for a more accurate data-dependent estimation of protein variance and inclusion of single peptide identifications without increasing false discoveries. The method was tested in several data sets including E. coli proteome spike-in data, using both label-free and TMT-labeled quantification. Compared with previous statistical methods used in quantitative proteomics, DEqMS showed consistently better accuracy in detecting altered protein levels compared with other statistical methods in both label-free and labeled quantitative proteomics data. DEqMS is available as an R package in Bioconductor.

Proteogenomics produces comprehensive and highly accurate protein-coding gene annotation in a complete genome assembly of Malassezia sympodialis.

Complete and accurate genome assembly and annotation is a crucial foundation for comparative and functional genomics. Despite this, few complete eukaryotic genomes are available, and genome annotation remains a major challenge. Here, we present a complete genome assembly of the skin commensal yeast Malassezia sympodialis and demonstrate how proteogenomics can substantially improve gene annotation. Through long-read DNA sequencing, we obtained a gap-free genome assembly for M. sympodialis (ATCC 42132), comprising eight nuclear and one mitochondrial chromosome. We also sequenced and assembled four M. sympodialis clinical isolates, and showed their value for understanding Malassezia reproduction by confirming four alternative allele combinations at the two mating-type loci. Importantly, we demonstrated how proteomics data could be readily integrated with transcriptomics data in standard annotation tools. This increased the number of annotated protein-coding genes by 14% (from 3612 to 4113), compared to using transcriptomics evidence alone. Manual curation further increased the number of protein-coding genes by 9% (to 4493). All of these genes have RNA-seq evidence and 87% were confirmed by proteomics. The M. sympodialis genome assembly and annotation presented here is at a quality yet achieved only for a few eukaryotic organisms, and constitutes an important reference for future host-microbe interaction studies.

Rewired metabolism in drug-resistant leukemia cells: a metabolic switch hallmarked by reduced dependence on exogenous glutamine.

Cancer cells that escape induction therapy are a major cause of relapse. Understanding metabolic alterations associated with drug resistance opens up unexplored opportunities for the development of new therapeutic strategies. Here, we applied a broad spectrum of technologies including RNA sequencing, global untargeted metabolomics, and stable isotope labeling mass spectrometry to identify metabolic changes in P-glycoprotein overexpressing T-cell acute lymphoblastic leukemia (ALL) cells, which escaped a therapeutically relevant daunorubicin treatment. We show that compared with sensitive ALL cells, resistant leukemia cells possess a fundamentally rewired central metabolism characterized by reduced dependence on glutamine despite a lack of expression of glutamate-ammonia ligase (GLUL), a higher demand for glucose and an altered rate of fatty acid ß-oxidation, accompanied by a decreased pantothenic acid uptake capacity. We experimentally validate our findings by selectively targeting components of this metabolic switch, using approved drugs and starvation approaches followed by cell viability analyses in both the ALL cells and in an acute myeloid leukemia (AML) sensitive/resistant cell line pair. We demonstrate how comparative metabolomics and RNA expression profiling of drug-sensitive and -resistant cells expose targetable metabolic changes and potential resistance markers. Our results show that drug resistance is associated with significant metabolic costs in cancer cells, which could be exploited using new therapeutic strategies.

SpliceVista, a tool for splice variant identification and visualization in shotgun proteomics data.

Alternative splicing is a pervasive process in eukaryotic organisms. More than 90% of human genes have alternatively spliced products, and aberrant splicing has been shown to be associated with many diseases. Current methods employed in the detection of splice variants include prediction by clustering of expressed sequence tags, exon microarray, and mRNA sequencing, all methods focusing on RNA-level information. There is a lack of tools for analyzing splice variants at the protein level. Here, we present SpliceVista, a tool for splice variant identification and visualization based on mass spectrometry proteomics data. SpliceVista retrieves gene structure and translated sequences from alternative splicing databases and maps MS-identified peptides to splice variants. The visualization module plots the exon composition of each splice variant and aligns identified peptides with transcript positions. If quantitative mass spectrometry data are used, SpliceVista plots the quantitative patterns for each peptide and provides users with the option to cluster peptides based on their quantitative patterns. SpliceVista can identify splice-variant-specific peptides, providing the possibility for variant-specific analysis. The tool was tested on two experimental datasets (PXD000065 and PXD000134). In A431 cells treated with gefitinib, 2983 splice-variant-specific peptides corresponding to 939 splice variants were identified. Through comparison of splice-variant-centric, protein-centric, and gene-centric quantification, several genes (e.g. EIF4H) were found to have differentially regulated splice variants after gefitinib treatment. The same discrepancy between protein-centric and splice-centric quantification was detected in the other dataset, in which induced pluripotent stem cells were compared with parental fibroblast and human embryotic stem cells. In addition, SpliceVista can be used to visualize novel splice variants inferred from peptide-level evidence. In summary, SpliceVista enables visualization, detection, and differential quantification of protein splice variants that are often missed in current proteomics pipelines.

Characteristics of spatial protein expression in the mouse cochlear sensory epithelia: Implications for age-related hearing loss.

Hair cells in the cochlear sensory epithelia serve as mechanosensory receptors, converting sound into neuronal signals. The basal sensory epithelia are responsible for transducing high-frequency sounds, while the apex handles low-frequency sounds. Age-related hearing loss predominantly affects hearing at high frequencies and is indicative of damage to the basal sensory epithelia. However, the precise mechanism underlying this site-selective injury remains unclear. In this study, we employed a microscale proteomics approach to examine and compare protein expression in different regions of the cochlear sensory epithelia (upper half and lower half) in 1.5-month-old (normal hearing) and 6-month-old (severe high-frequency hearing loss without hair cell loss) C57BL/6J mice. A total of 2,386 proteins were detected, and no significant differences in protein expression were detected in the upper half of the cochlear sensory epithelia between the two age groups. The expression of 20 proteins in the lower half of the cochlear sensory epithelia significantly differed between the two age groups (e.g., MATN1, MATN4, and AQP1). Moreover, there were 311 and 226 differentially expressed proteins between the upper and lower halves of the cochlear sensory epithelia in 1.5-month-old and 6-month-old mice, respectively. The expression levels of selected proteins were validated by Western blotting. These findings suggest that the spatial differences in protein expression within the cochlear sensory epithelia may play a role in determining the susceptibility of cells at different sites of the cochlea to age-related damage.

Arsenic Trioxide inhibits Activation of Hedgehog Pathway in Human Neuroblastoma Cell Line SK-N-BE(2) Independent of Itraconazole.

BACKGROUND: Neuroblastoma (NB) remains associated with a low overall survival rate over the long term. Abnormal activation of the Hedgehog (HH) signaling pathway can activate the transcription of various downstream target genes that promote NB. Both arsenic trioxide (ATO) and itraconazole (ITRA) can inhibit tumor growth. OBJECTIVE: To determine whether ATO combined with ITRA can be used to treat NB with HH pathway activation, we examined the effects of ATO and ITRA monotherapy or combined inhibition of the HH pathway in NB. METHODS: Analysis of CCK8 and flow cytometry showed cell inhibition and cell cycle, respectively. Real-time PCR analysis was conducted to assess the mRNA expression of HH pathway. RESULTS: We revealed that as concentrations of ATO and ITRA increased, the killing effects of both agents on SK-N-BE(2) cells became more apparent. During G2/M, the cell cycle was largely arrested by ATO alone and combined with ITRA, and in the G0/G1 phase by ITRA alone. In the HH pathway, ATO inhibited the transcription of the SHH, PTCH1, SMO and GLI2 genes, however, ITRA did not. Instead of showing synergistic effects in a combined mode, ITRA decreased ATO inhibitory effects. CONCLUSION: We showed that ATO is an important inhibitor of HH pathway but ITRA can weaken the inhibitory effect of ATO. This study provides an experimental evidence for the clinical use of ATO and ITRA in the treatment of NB with HH pathway activation in cytology.

Correlation Study between Rural Human Settlement Health Factors: A Case Study of Xiangxi, China.

With the emergence of the Industry 4.0 era in China, more refined methods are being proposed for healthy living requirements for human settlements. Since the rural human settlements in China are relatively backward, this study aimed to investigate the influencing factors of human health. First, through field surveys and questionnaires conducted with villagers in Xiangxi's traditional villages in Hunan Province, we analyzed the factors affecting human health qualitatively and quantitatively using the SPSS software. We identified three main dimensions affecting human health in rural human settlements including human behavioral activities, physical environment, and natural environment. Then, we used correlation analysis and multiple linear regression analysis methods to analyze the correlation between environmental factors and human health. The results showed that human activities, building physical environment, and natural environment are significantly correlated with human health. Among them, human behavior has the strongest correlation with health. This research contributes to creating healthy human settlements and guiding the creation of a healthy environment in rural China.

Nitric oxide protects against cochlear hair cell damage and noise-induced hearing loss through glucose metabolic reprogramming.

Nitric oxide (NO) is critically involved in the regulation of a wide variety of physiological and pathophysiological processes. However, the role of NO in the pathogenesis of noise-induced hearing loss (NIHL) is complex and remains controversial. Here we reported that treatment of CBA/J mice with l-arginine, a physiological precursor of NO, significantly reduced noise-induced reactive oxygen species accumulation in outer hair cells (OHCs), attenuated noise-induced loss of OHCs and NIHL consequently. Conversely, pharmacological inhibition of endothelial nitric oxide synthase exacerbated noise-induced loss of OHCs and aggravated NIHL. In HEI-OC1 cells, NO also showed substantial protection against H2O2-induced oxidative stress and cytotoxicity. Mechanistically, NO increased S-nitrosylation of pyruvate kinase M2 (PKM2) and inhibited its activity, which thus diverted glucose metabolic flux from glycolysis into the pentose phosphate pathway to increase production of reducing equivalents (NADPH and GSH) and eventually prevented H2O2-induced oxidative damage. These findings open new avenues for protection of cochlear hair cells from oxidative stress and prevention of NIHL through NO modulation of PKM2 and glucose metabolism reprogramming.

Increased expression of peptides from non-coding genes in cancer proteomics datasets suggests potential tumor neoantigens.

Neoantigen-based immunotherapy has yielded promising results in clinical trials. However, it is limited to tumor-specific mutations, and is often tailored to individual patients. Identifying suitable tumor-specific antigens is still a major challenge. Previous proteogenomics studies have identified peptides encoded by predicted non-coding sequences in human genome. To investigate whether tumors express specific peptides encoded by non-coding genes, we analyzed published proteomics data from five cancer types including 933 tumor samples and 275 matched normal samples and compared these to data from 31 different healthy human tissues. Our results reveal that many predicted non-coding genes such as DGCR9 and RHOXF1P3 encode peptides that are overexpressed in tumors compared to normal controls. Furthermore, from the non-coding genes-encoded peptides specifically detected in cancers, we predict a large number of "dark antigens" (neoantigens from non-coding genomic regions), which may provide an alternative source of neoantigens beyond standard tumor specific mutations.

Construction and characterization of a fluorescent sendai virus carrying the gene for envelope fusion protein fused with enhanced green fluorescent protein.

Sendai virus (SeV) is an enveloped virus with a non-segmented negative-strand RNA genome. SeV envelope fusion (F) glycoproteins play crucial roles in the viral life cycle in processes such as viral binding, assembly, and budding. In this study, we developed a viable recombinant SeV designated F-EGFP SeV/ΔF, in which the F protein was replaced by an F protein fused to EGFP at the carboxyl terminus. Living infected cells of the recombinant virus were directly visualized by green fluorescence. The addition of EGFP to the F protein maintained the activities of the F protein in terms of intracellular transport to the plasma membrane via the ER and the Golgi apparatus and fusion activity in the infected cells. These results suggest that this fluorescent SeV is a useful tool for studying the viral binding, assembly, and budding mechanisms of F proteins and the SeV life cycle in living infected cells.

Hydrogen Bonds in Disulfonic-Functionalized Acid Ionic Liquids for Efficient Biodiesel Synthesis.

Regulating the states of hydrogen bonds in ionic liquids (ILs) is an effective way to improve their catalytic performance. In this paper, disulfonic-functionalized acidic ionic liquids (DSFAILs) were synthesized successfully, including novel SO3H-functionalized binuclear IL (bis[3-(CH2)3SO3H-1-(CH2)2-Im][HSO4]2). For the biodiesel synthesis, compared with the traditional ILs catalysts, DSFAILs bis[(3-(CH2)3SO3H-1-(CH2)2-Im][HSO4]2, [Im(N (CH2)3SO3H)2][HSO4]) had higher catalytic activity even under mild reaction conditions. Using the density functional theory (DFT) method, the role of hydrogen bonds in different SO3H-functionalized acidic ionic liquids (SFAILs) was explored. The forms of hydrogen bonds existing in different ILs directly determine their acidity. It suggested that the forming status of the active sites (hydrogen bonds) were diverse in different SFAILs. Also, deep ionization of the hydrogen atoms from the cation-anion strong interaction could increase the acidity and catalytic performance of SFAILs. From this, the structure-activity relationship between the SFAILs structures and the catalytic activity of methyl oleate synthesis was proposed. Besides, the experimental results also showed that bis[3-(CH2)3SO3H-1-(CH2)2-Im][HSO4]2 catalyst had a high catalytic activity to obtain methyl oleate and the catalyst could be separated easily owing to its larger molecular weight. However, [Im(N(CH2)3SO3H)2][HSO4] had a stronger acidity and a lower steric hindrance and thus a higher catalytic activity and was the optimal catalyst for the methyl oleate synthesis. In the presence of a small amount of catalyst (6 wt %) and at low reaction temperature (353 K), the methyl oleate yield could reach up to 93%. After six recycles of the catalyst, the methyl oleate yield remained at 90%.

Extracellular Vesicles for the Treatment of Radiation-Induced Normal Tissue Toxicity in the Lung.

Human stem cell-derived extracellular vesicles (EV) provide many advantages over cell-based therapies for the treatment of functionally compromised tissue beds and organ sites. Here we sought to determine whether human embryonic stem cell (hESC)-derived EV could resolve in part, the adverse late normal tissue complications associated with exposure of the lung to ionizing radiation. The hESC-derived EV were systemically administered to the mice via the retro-orbital sinus to explore the potential therapeutic benefits following exposure to high thoracic doses of radiation (14 Gy). Data demonstrated that hESC-derived EV treatment significantly improved overall survival of the irradiated cohorts (P < 0.001). Increased survival was also associated with significant reductions in lung fibrosis as quantified by CBCT imaging (P < 0.01, 2 weeks post-irradiation). Qualitative histological analyses revealed reduced indications of radiation induced pulmonary injury in animals treated with EV. EV were then subjected to a rigorous proteomic analysis to ascertain the potential bioactive cargo that may prove beneficial in ameliorating radiation-induced normal tissue toxicities in the lung. Proteomics validated several consensus exosome markers (e.g., CD68) and identified major classes of proteins involved in nuclear pore complexes, epigenetics, cell cycle, growth and proliferation, DNA repair, antioxidant function, and cellular metabolism (TCA cycle and oxidative phosphorylation, OXYPHOS). Interestingly, EV were also found to contain mitochondrial components (mtDNA, OXYPHOS protein subunits), which may contribute to the metabolic reprograming and recovery of radiation-injured pulmonary tissue. To evaluate the safety of EV treatments in the context of the radiotherapeutic management of tumors, mice harboring TC1 tumor xenografts were subjected to the same EV treatments shown to forestall lung fibrosis. Data indicated that over the course of one month, no change in the growth of flank tumors between treated and control cohorts was observed. In conclusion, present findings demonstrate that systemic delivery of hESC-derived EV could ameliorate radiation-induced normal tissue complications in the lung, through a variety of potential mechanisms based on EV cargo analysis.

In-depth human plasma proteome analysis captures tissue proteins and transfer of protein variants across the placenta.

Here, we present a method for in-depth human plasma proteome analysis based on high-resolution isoelectric focusing HiRIEF LC-MS/MS, demonstrating high proteome coverage, reproducibility and the potential for liquid biopsy protein profiling. By integrating genomic sequence information to the MS-based plasma proteome analysis, we enable detection of single amino acid variants and for the first time demonstrate transfer of multiple protein variants between mother and fetus across the placenta. We further show that our method has the ability to detect both low abundance tissue-annotated proteins and phosphorylated proteins in plasma, as well as quantitate differences in plasma proteomes between the mother and the newborn as well as changes related to pregnancy.

Breast cancer quantitative proteome and proteogenomic landscape.

In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.

Splicing of platelet resident pre-mRNAs upon activation by physiological stimuli results in functionally relevant proteome modifications.

Platelet activation triggers thrombus formation in physiological and pathological conditions, such as acute coronary syndromes. Current therapies still fail to prevent thrombotic events in numerous patients, indicating that the mechanisms modulating platelet response during activation need to be clarified. The evidence that platelets are capable of de novo protein synthesis in response to stimuli raised the issue of how megakaryocyte-derived mRNAs are regulated in these anucleate cell fragments. Proteogenomics was applied here to investigate this phenomeon in platelets activated in vitro with Collagen or Thrombin Receptor Activating Peptide. Combining proteomics and transcriptomics allowed in depth platelet proteome characterization, revealing a significant effect of either stimulus on proteome composition. In silico analysis revealed the presence of resident immature RNAs in resting platelets, characterized by retained introns, while unbiased proteogenomics correlated intron removal by RNA splicing with changes on proteome composition upon activation. This allowed identification of a set of transcripts undergoing maturation by intron removal during activation and resulting in accumulation of the corresponding peptides at exon-exon junctions. These results indicate that RNA splicing events occur in platelets during activation and that maturation of specific pre-mRNAs is part of the activation cascade, contributing to a dynamic fine-tuning of the transcriptome.

Discovery of coding regions in the human genome by integrated proteogenomics analysis workflow.

Proteogenomics enable the discovery of novel peptides (from unannotated genomic protein-coding loci) and single amino acid variant peptides (derived from single-nucleotide polymorphisms and mutations). Increasing the reliability of these identifications is crucial to ensure their usefulness for genome annotation and potential application as neoantigens in cancer immunotherapy. We here present integrated proteogenomics analysis workflow (IPAW), which combines peptide discovery, curation, and validation. IPAW includes the SpectrumAI tool for automated inspection of MS/MS spectra, eliminating false identifications of single-residue substitution peptides. We employ IPAW to analyze two proteomics data sets acquired from A431 cells and five normal human tissues using extended (pH range, 3-10) high-resolution isoelectric focusing (HiRIEF) pre-fractionation and TMT-based peptide quantitation. The IPAW results provide evidence for the translation of pseudogenes, lncRNAs, short ORFs, alternative ORFs, N-terminal extensions, and intronic sequences. Moreover, our quantitative analysis indicates that protein production from certain pseudogenes and lncRNAs is tissue specific.