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Leukemia May 2024The hypomethylating agent 5-azacytidine (AZA) is the first-line treatment for AML patients unfit for intensive chemotherapy. The effect of AZA results in part from...
The hypomethylating agent 5-azacytidine (AZA) is the first-line treatment for AML patients unfit for intensive chemotherapy. The effect of AZA results in part from T-cell cytotoxic responses against MHC-I-associated peptides (MAPs) deriving from hypermethylated genomic regions such as cancer-testis antigens (CTAs), or endogenous retroelements (EREs). However, evidence supporting higher ERE MAPs presentation after AZA treatment is lacking. Therefore, using proteogenomics, we examined the impact of AZA on the repertoire of MAPs and their source transcripts. AZA-treated AML upregulated both CTA and ERE transcripts, but only CTA MAPs were presented at greater levels. Upregulated ERE transcripts triggered innate immune responses against double-stranded RNAs but were degraded by autophagy, and not processed into MAPs. Autophagy resulted from the formation of protein aggregates caused by AZA-dependent inhibition of DNMT2. Autophagy inhibition had an additive effect with AZA on AML cell proliferation and survival, increased ERE levels, increased pro-inflammatory responses, and generated immunogenic tumor-specific ERE-derived MAPs. Finally, autophagy was associated with a lower abundance of CD8 T-cell markers in AML patients expressing high levels of EREs. This work demonstrates that AZA-induced EREs are degraded by autophagy and shows that inhibiting autophagy can improve the immune recognition of AML blasts in treated patients.
Topics: Humans; Leukemia, Myeloid, Acute; Azacitidine; Autophagy; Antimetabolites, Antineoplastic; DNA Methylation; Cell Proliferation; Antigens, Neoplasm
PubMed: 38627586
DOI: 10.1038/s41375-024-02250-6 -
BioRxiv : the Preprint Server For... Apr 2024Alternative splicing is a major contributor of transcriptomic complexity, but the extent to which transcript isoforms are translated into stable, functional protein...
Alternative splicing is a major contributor of transcriptomic complexity, but the extent to which transcript isoforms are translated into stable, functional protein isoforms is unclear. Furthermore, detection of relatively scarce isoform-specific peptides is challenging, with many protein isoforms remaining uncharted due to technical limitations. Recently, a family of advanced targeted MS strategies, termed internal standard parallel reaction monitoring (IS-PRM), have demonstrated multiplexed, sensitive detection of pre-defined peptides of interest. Such approaches have not yet been used to confirm existence of novel peptides. Here, we present a targeted proteogenomic approach that leverages sample-matched long-read RNA sequencing (LR RNAseq) data to predict potential protein isoforms with prior transcript evidence. Predicted tryptic isoform-specific peptides, which are specific to individual gene product isoforms, serve as "triggers" and "targets" in the IS-PRM method, Tomahto. Using the model human stem cell line WTC11, LR RNAseq data were generated and used to inform the generation of synthetic standards for 192 isoform-specific peptides (114 isoforms from 55 genes). These synthetic "trigger" peptides were labeled with super heavy tandem mass tags (TMT) and spiked into TMT-labeled WTC11 tryptic digest, predicted to contain corresponding endogenous "target" peptides. Compared to DDA mode, Tomahto increased detectability of isoforms by 3.6-fold, resulting in the identification of five previously unannotated isoforms. Our method detected protein isoform expression for 43 out of 55 genes corresponding to 54 resolved isoforms. This LR RNA seq-informed Tomahto targeted approach, called LRP-IS-PRM, is a new modality for generating protein-level evidence of alternative isoforms - a critical first step in designing functional studies and eventually clinical assays.
PubMed: 38617311
DOI: 10.1101/2024.04.01.587549 -
Nature Communications Apr 2024Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to...
Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to different recurrence risks (RRs) remain poorly defined. Here, we perform an integrative proteogenomic and metabolomic characterization of 102 Chinese PTC patients with different RRs. Genomic profiling reveals that mutations in MUC16 and TERT promoter as well as multiple gene fusions like NCOA4-RET are enriched by the high RR. Integrative multi-omics analyses further describe the multi-dimensional characteristics of PTC, especially in metabolism pathways, and delineate dominated molecular patterns of different RRs. Moreover, the PTC patients are clustered into four subtypes (CS1: low RR and BRAF-like; CS2: high RR and metabolism type, worst prognosis; CS3: high RR and immune type, better prognosis; CS4: high RR and BRAF-like) based on the omics data. Notably, the subtypes display significant differences considering BRAF and TERT promoter mutations, metabolism and immune pathway profiles, epithelial cell compositions, and various clinical factors (especially RRs and prognosis) as well as druggable targets. This study can provide insights into the complex molecular characteristics of PTC recurrences and help promote early diagnosis and precision treatment of recurrent PTC.
Topics: Humans; Thyroid Cancer, Papillary; Proteogenomics; Proto-Oncogene Proteins B-raf; Metabolomics; Thyroid Neoplasms
PubMed: 38609408
DOI: 10.1038/s41467-024-47581-1 -
Cancer Research May 2024Never-smoker lung adenocarcinoma (NSLA) is prevalent in Asian populations, particularly in women. EGFR mutations and anaplastic lymphoma kinase (ALK) fusions are major...
UNLABELLED
Never-smoker lung adenocarcinoma (NSLA) is prevalent in Asian populations, particularly in women. EGFR mutations and anaplastic lymphoma kinase (ALK) fusions are major genetic alterations observed in NSLA, and NSLA with these alterations have been well studied and can be treated with targeted therapies. To provide insights into the molecular profile of NSLA without EGFR and ALK alterations (NENA), we selected 141 NSLA tissues and performed proteogenomic characterization, including whole genome sequencing (WGS), transcriptomic, methylation EPIC array, total proteomic, and phosphoproteomic analyses. Forty patients with NSLA harboring EGFR and ALK alterations and seven patients with NENA with microsatellite instability were excluded. Genome analysis revealed that TP53 (25%), KRAS (22%), and SETD2 (11%) mutations and ROS1 fusions (14%) were the most frequent genetic alterations in NENA patients. Proteogenomic impact analysis revealed that STK11 and ERBB2 somatic mutations had broad effects on cancer-associated genes in NENA. DNA copy number alteration analysis identified 22 prognostic proteins that influenced transcriptomic and proteomic changes. Gene set enrichment analysis revealed estrogen signaling as the key pathway activated in NENA. Increased estrogen signaling was associated with proteogenomic alterations, such as copy number deletions in chromosomes 14 and 21, STK11 mutation, and DNA hypomethylation of LLGL2 and ST14. Finally, saracatinib, an Src inhibitor, was identified as a potential drug for targeting activated estrogen signaling in NENA and was experimentally validated in vitro. Collectively, this study enhanced our understanding of NENA NSLA by elucidating the proteogenomic landscape and proposed saracatinib as a potential treatment for this patient population that lacks effective targeted therapies.
SIGNIFICANCE
The proteogenomic landscape in never-smoker lung cancer without known driver mutations reveals prognostic proteins and enhanced estrogen signaling that can be targeted as a potential therapeutic strategy to improve patient outcomes.
Topics: Female; Humans; Male; Middle Aged; Adenocarcinoma of Lung; Anaplastic Lymphoma Kinase; DNA Copy Number Variations; ErbB Receptors; Estrogens; Lung Neoplasms; Mutation; Non-Smokers; Prognosis; Proteogenomics; Signal Transduction
PubMed: 38607364
DOI: 10.1158/0008-5472.CAN-23-1551 -
Molecular & Cellular Proteomics : MCP Jun 2024Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and...
Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.
Topics: Humans; Esophageal Neoplasms; Adenocarcinoma; Proteomics; Gene Expression Regulation, Neoplastic; Biomarkers, Tumor; Male; Female; RNA Processing, Post-Transcriptional; Proteome; Multiomics
PubMed: 38604503
DOI: 10.1016/j.mcpro.2024.100764 -
BioRxiv : the Preprint Server For... Mar 2024Gene expression is a multi-step transformation of biological information from its storage form (DNA) into functional forms (protein and some RNAs). Regulatory activities...
Gene expression is a multi-step transformation of biological information from its storage form (DNA) into functional forms (protein and some RNAs). Regulatory activities at each step of this transformation multiply a single gene into a myriad of proteoforms. Proteogenomics is the study of how genomic and transcriptomic variation creates this proteoform diversity, and is limited by the challenges of modeling the complexities of gene-expression. We therefore created moPepGen, a graph-based algorithm that comprehensively enumerates proteoforms in linear time. moPepGen works with multiple technologies, in multiple species and on all types of genetic and transcriptomic data. In human cancer proteomes, it detects and quantifies previously unobserved noncanonical peptides arising from germline and somatic genomic variants, noncoding open reading frames, RNA fusions and RNA circularization. By enabling efficient identification and quantitation of previously hidden proteins in both existing and new proteomic data, moPepGen facilitates all proteogenomics applications. It is available at: https://github.com/uclahs-cds/package-moPepGen.
PubMed: 38585946
DOI: 10.1101/2024.03.28.587261 -
Frontiers in Oncology 2024
PubMed: 38577326
DOI: 10.3389/fonc.2024.1383838 -
Nature Genetics Apr 2024Endometrial carcinoma remains a public health concern with a growing incidence, particularly in younger women. Preserving fertility is a crucial consideration in the...
Endometrial carcinoma remains a public health concern with a growing incidence, particularly in younger women. Preserving fertility is a crucial consideration in the management of early-onset endometrioid endometrial carcinoma (EEEC), particularly in patients under 40 who maintain both reproductive desire and capacity. To illuminate the molecular characteristics of EEEC, we undertook a large-scale multi-omics study of 215 patients with endometrial carcinoma, including 81 with EEEC. We reveal an unexpected association between exposome-related mutational signature and EEEC, characterized by specific CTNNB1 and SIGLEC10 hotspot mutations and disruption of downstream pathways. Interestingly, SIGLEC10 mutation in EEECs resulted in aberrant SIGLEC-10 protein expression and promoted progestin resistance by interacting with estrogen receptor alpha. We also identified potential protein biomarkers for progestin response in fertility-sparing treatment for EEEC. Collectively, our study establishes a proteogenomic resource of EEECs, uncovering the interactions between exposome and genomic susceptibilities that contribute to the development of primary prevention and early detection strategies for EEECs.
Topics: Humans; Female; Progestins; Proteogenomics; Antineoplastic Agents, Hormonal; Endometrial Hyperplasia; Fertility Preservation; Retrospective Studies; Carcinoma, Endometrioid; Endometrial Neoplasms
PubMed: 38565644
DOI: 10.1038/s41588-024-01703-z -
BioRxiv : the Preprint Server For... Feb 2024The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant melanoma (MM). However, resistance to targeted and immune-checkpoint-based...
UNLABELLED
The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant melanoma (MM). However, resistance to targeted and immune-checkpoint-based therapies still poses a significant problem. Here we mine large scale MM proteogenomic data integrating it with MM cell line dependency screen, and drug sensitivity data to identify druggable targets and forecast treatment efficacy and resistance. Leveraging protein profiles from established MM subtypes and molecular structures of 82 cancer treatment drugs, we identified nine candidate hub proteins, mTOR, FYN, PIK3CB, EGFR, MAPK3, MAP4K1, MAP2K1, SRC and AKT1, across five distinct MM subtypes. These proteins serve as potential drug targets applicable to one or multiple MM subtypes. By analyzing transcriptomic data from 48 publicly accessible melanoma cell lines sourced from Achilles and CRISPR dependency screens, we forecasted 162 potentially targetable genes. We also identified genetic resistance in 260 genes across at least one melanoma subtype. In addition, we employed publicly available compound sensitivity data (Cancer Therapeutics Response Portal, CTRPv2) on the cell lines to assess the correlation of compound effectiveness within each subtype. We have identified 20 compounds exhibiting potential drug impact in at least one melanoma subtype. Remarkably, employing this unbiased approach, we have uncovered compounds targeting ferroptosis, that demonstrate a striking 30x fold difference in sensitivity among different subtypes. This implies that the proteogenomic classification of melanoma has the potential to predict sensitivity to ferroptosis compounds. Our results suggest innovative and novel therapeutic strategies by stratifying melanoma samples through proteomic profiling, offering a spectrum of novel therapeutic interventions and prospects for combination therapy.
HIGHLIGHTS
(1) Proteogenomic subtype classification can define the landscape of genetic dependencies in melanoma (2) Nine proteins from molecular subtypes were identified as potential drug targets for specified MM patients (3) 20 compounds identified that show potential effectiveness in at least one melanoma subtype (4) Proteogenomics can predict specific ferroptosis inducers, HDAC, and RTK Inhibitor sensitivity in melanoma subtypes.
PubMed: 38545623
DOI: 10.1101/2024.02.08.579424 -
Frontiers in Cell and Developmental... 2024is an invertebrate animal model system that is well characterized and has many advantages for the study of cardiovascular biology. The regulatory mechanisms of cardiac...
is an invertebrate animal model system that is well characterized and has many advantages for the study of cardiovascular biology. The regulatory mechanisms of cardiac myocyte proliferation in are intriguing since regeneration of functional tissue has been demonstrated in other organs of in response to injury To identify genes that are differentially expressed in response to cardiac injury, microarray analysis was conducted on RNA from adult hearts with normal or damaged myocardium. After a 24- or 48-h recovery period, total RNA was isolated from damaged and control hearts. Initial results indicate significant changes in gene expression in hearts damaged by ligation in comparison to control hearts. Ligation injury shows differential expression of 223 genes as compared to control with limited false discovery (5.8%). Among these 223 genes, 117 have known human orthologs of which 68 were upregulated and 49 were downregulated. Notably, , insulin-like growth factor binding protein and Ras-related protein were significantly upregulated in injured hearts, whereas expression of a junctophilin ortholog was decreased. Histological analyses of injured myocardium were conducted in parallel to the microarray study which revealed thickened myocardium in injured hearts. Taken together, these studies will connect differences in gene expression to cellular changes in the myocardium of , which will help to promote further investigations into the regulatory mechanisms of cardiac myocyte proliferation across chordates.
PubMed: 38544819
DOI: 10.3389/fcell.2024.1304755