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During the last three decades, technological advancements in high-throughput next-generation sequencing have resulted in an increased understanding of proteomic and genomic data, aptly termed proteogenomics. Efforts in developing such approaches have not only been limited but also focused on protein identification and subcellular localization. These approaches, however, have also been explored for their broad understanding of how genomics/transcriptomics data have yielded measures, for example, gene expression regulation/signal cascading and diseasome studies. In this review, we discuss methods and tools developed through sequence-centric integrative modeling of proteogenomic approaches., (© 2025. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Cancer neoantigens are tumor-specific non-synonymous mutant peptides that activate the immune system to produce an anti-tumor response. Personalized cancer vaccines based on neoantigens are currently one of the most promising therapeutic approaches for cancer treatment. By utilizing the unique mutations within each patient's tumor, these vaccines aim to elicit a strong and specific immune response against cancer cells. However, the identification of neoantigens remains challenging due to the low accuracy of current prediction tools and the high false-positive rate of candidate neoantigens. Since the concept of "proteogenomics" emerged in 2004, it has evolved rapidly with the increased sequencing depth of next-generation sequencing technologies and the maturation of mass spectrometry-based proteomics technologies to become a more comprehensive approach to neoantigen identification, allowing the discovery of high-confidence candidate neoantigens. In this review, we summarize the reason why cancer neoantigens have become attractive targets for immunotherapy, the mechanism of cancer vaccines and the advances in cancer immunotherapy. Considerations relevant to the application emerging of proteogenomics technologies for neoantigen identification and challenges in this field are described., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare, aggressive, and heterogeneous subtype of kidney cancer, which is not well characterized. Since genetic alterations are always associated with carcinogenesis, and proteins are the major executors of biological features, multi-omics studies can reveal the systematic tRCC biological process comprehensively. Here, we describe the proteogenomic workflow for characterization of tRCC in detail to provide the knowledge foundation for integrated proteogenomic analysis of tRCC and other malignant tumors in the future., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities., Competing Interests: Declaration of interests M.J.B. has participated in advisory boards for the following companies: Clovis, Astra Zeneca, and GSK-Tesaro. A.N.H. is the Associate Editor of Clinical Chemistry and has a financial interest in the company Seattle Genetics. A.G.P. is the founder of Precision Assays, LLC. A.B.B. is employed by Synapse. S.Y. is an employee and shareholder of Sema4. B.J.W. has stock interests in Verastem and Exact Sciences., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

How cells control gene expression is a fundamental question. The relative contribution of protein-level and RNA-level regulation to this process remains unclear. Here, we perform a proteogenomic analysis of tumors and untransformed cells containing somatic copy number alterations (SCNAs). By revealing how cells regulate RNA and protein abundances of genes with SCNAs, we provide insights into the rules of gene regulation. Protein complex genes have a strong protein-level regulation while non-complex genes have a strong RNA-level regulation. Notable exceptions are plasma membrane protein complex genes, which show a weak protein-level regulation and a stronger RNA-level regulation. Strikingly, we find a strong negative association between the degree of RNA-level and protein-level regulation across genes and cellular pathways. Moreover, genes participating in the same pathway show a similar degree of RNA- and protein-level regulation. Pathways including translation, splicing, RNA processing, and mitochondrial function show a stronger protein-level regulation while cell adhesion and migration pathways show a stronger RNA-level regulation. These results suggest that the evolution of gene regulation is shaped by functional constraints and that many cellular pathways tend to evolve one predominant mechanism of gene regulation at the protein level or at the RNA level., Competing Interests: PC, XZ, LK, EC, AM, JM, SL, RR, RM, JS, DG, DF, TD No competing interests declared, (© 2022, Cheng, Zhao, Katsnelson et al.)

A proteogenomics-based neoantigen prediction pipeline, namely ProGeo-neo, was previously developed by our team to predict neoantigens, allowing the identification of class-I major histocompatibility complex (MHC) binding peptides based on single-nucleotide variation (SNV) mutations. To improve it, we here present an updated pipeline, i.e., ProGeo-neo v2.0, in which a one-stop software solution was proposed to identify neoantigens based on the paired tumor-normal whole genome sequencing (WGS)/whole exome sequencing (WES) data in FASTQ format. Preferably, in ProGeo-neo v2.0, several new features are provided. In addition to the identification of MHC-I neoantigens, the new version supports the prediction of MHC class II-restricted neoantigens, i.e., peptides up to 30-mer in length. Moreover, the source of neoantigens has been expanded, allowing more candidate neoantigens to be identified, such as in-frame insertion-deletion (indels) mutations, frameshift mutations, and gene fusion analysis. In addition, we propose two more efficient screening approaches, including an in-group authentic neoantigen peptides database and two more stringent thresholds. The range of candidate peptides was effectively narrowed down to those that are more likely to elicit an immune response, providing a more meaningful reference for subsequent experimental validation. Compared to ProGeo-neo, the ProGeo-neo v2.0 performed well based on the same dataset, including updated functionality and improved accuracy.

The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

The strain Burkholderia sp. ISTR5 (R5) was studied for polyhydroxyalkanoate (PHA) production on Kraft lignin (KL) and lignosulfonate (LS) as substrates. During the initial screening, the maximum PHA mass fraction in biomass produced on KL and LS was 23% and 18%, respectively, at 96 h. PHA production on KL was further optimized using the Box-Behnken Design (BBD) model of Response Surface Methodology (RSM). After optimization, a 42.5% increase in PHA production and a 32.2% increase in the total cell biomass was observed. PHA was characterized by GC-MS, TEM, FTIR, NMR, and fluorescence microscopy. It was found to be a small chain length PHA with a copolymer of poly (hydroxybutyrate-co-hydroxyvalerate) (PHBV). The degradation of PHBV was also studied using this strain; it was observed that R5 completely degraded PHBV in 120 h. Genomic and proteomic analysis of R5 revealed numerous enzymes for the metabolism of lignin degradation and PHA production., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: Despite toxic side effects and limited durable response, the current standard-of-care treatment for high grade serous ovarian cancer (HGSOC) remains platinum/taxane-based chemotherapy. Given that the overall prognosis has not improved drastically over the past several decades, there is a critical need to understand the underlying mechanisms that lead to tumour development and progression., Methods: We utilized an integrative proteogenomic analysis of HGSOC tumours applying a poor prognosis gene expression signature (PPS) as a conceptual framework to analyse orthogonal genomic and proteomic data from the TCGA (n = 488) and CPTAC (n = 169) studies. Genes identified through in silico analyses were assessed in vitro studies to demonstrate their impact on proliferation and cell cycle progression., Findings: These analyses identified DNA amplification and overexpression of the transcription factor ADNP (Activity Dependent Neuroprotector Homeobox) in poorly prognostic tumours. Validation studies confirmed the prognostic capacity of ADNP and suggested an oncogenic role for this protein given the association between ADNP expression and pro-proliferative signalling. In vitro studies confirmed ADNP as a novel and essential mediator of cell proliferation through dysregulation of cell cycle checkpoints., Interpretation: We identified ADNP as being amplified and overexpressed in poor prognosis HGSOC in silico analyses and demonstrated that ADNP is a novel and essential oncogene in HGSOC which mediates proliferation through dysregulation of cell cycle checkpoints in vitro., Funding: The National Cancer Institute of the National Institutes of Health, the V Foundation for Cancer Research and the New Jersey Commission for Cancer Research., (Copyright © 2019 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Brucella spp. are Gram-negative, facultative intracellular pathogens that cause brucellosis in both humans and animals. The B. abortus vaccine strain 104 M is the only vaccine available in China for the prevention of brucellosis in humans. Although the B. abortus 104 M genome has been fully sequenced, the current genome annotations are not yet complete. In addition, the main mechanisms underpinning its residual toxicity and vaccine-induced immune protection have yet to be elucidated. Mapping the proteome of B. abortus 104 M will help to improve genome annotation quality, thereby facilitating a greater understanding of its biology., Results: In this study, we utilized a proteogenomic approach that combined subcellular fractionation and peptide fractionation to perform a whole-proteome analysis and genome reannotation of B. abortus 104 M using high-resolution mass spectrometry. In total, 1,729 proteins (56.3% of 3,072) including 218 hypothetical proteins were identified using the culture conditions that were employed this study. The annotations of the B. abortus 104 M genome were also refined following identification and validation by reverse transcription-PCR. In addition, 14 pivotal virulence factors and 17 known protective antigens known to be involved in residual toxicity and immune protection were confirmed at the protein level following induction by the 104 M vaccine. Moreover, a further insight into the cell biology of multichromosomal bacteria was obtained following the elucidation of differences in protein expression levels between the small and large chromosomes., Conclusions: The work presented in this report used a proteogenomic approach to perform whole-proteome analysis and genome reannotation in B. abortus 104 M; this work helped to improve genome annotation quality. Our analysis of virulence factors, protective antigens and other protein effectors provided the basis for further research to elucidate the mechanisms of residual toxicity and immune protection induced by the 104 M vaccine. Finally, the potential link between replication dynamics, gene function, and protein expression levels in this multichromosomal bacterium was detailed.