Cancer Genomics & Proteomics[JOURNAL]
Sun
200 papers
Comprehensive review of MS-based studies on N-glycoproteome and N-glycome of extracellular vesicles.
Li Y, Wang J, Chen W … +2 more , Lu H, Zhang Y
Proteomics · 2024 Jun · PMID 37474487 · Publisher ↗
Extracellular vesicles (EVs) are lipid bilayer-enclosed particles that can be released by all type of cells. Whereas, as one of the most common post-translational modifications, glycosylation plays a vital role in variou...
Extracellular vesicles (EVs) are lipid bilayer-enclosed particles that can be released by all type of cells. Whereas, as one of the most common post-translational modifications, glycosylation plays a vital role in various biological functions of EVs, such as EV biogenesis, sorting, and cellular recognition. Nevertheless, compared with studies on RNAs or proteins, those investigating the glycoconjugates of EVs are limited. An in-depth investigation of N-glycosylation of EVs can improve the understanding of the biological functions of EVs and help to exploit EVs from different perspectives. The general focus of studies on glycosylation of EVs primarily includes isolation and characterization of EVs, preparation of glycoproteome/glycome samples and MS analysis. However, the low content of EVs and non-standard separation methods for downstream analysis are the main limitations of these studies. In this review, we highlight the importance of glycopeptide/glycan enrichment and derivatization owing to the low abundance of glycoproteins and the low ionization efficiency of glycans. Diverse fragmentation patterns and professional analytical software are indispensable for analysing glycosylation via MS. Altogether, this review summarises recent studies on glycosylation of EVs, revealing the role of EVs in disease progression and their remarkable potential as biomarkers.
Proteomic profiling reveals KRT6C as a probable hereterodimer partner for KRT9: New insights into re-classifying epidermolytic palmoplantar keratoderma (EPPK) and a milder form of pachyonychia congenita (PC-K6c) as a group of genetic cutaneous disorders.
Li P, Qi J, Zhong Y … +2 more , Ding A, Xiao H
J Proteomics · 2023 Sep · PMID 37467889 · Publisher ↗
Epidermolytic palmoplantar keratoderma (EPPK), a highly penetrant autosomal dominant genodermatosis, is characterized by diffuse keratoses on palmplantar epidermis. The keratin 9 gene (KRT9) is responsible for EPPK. To d...
Epidermolytic palmoplantar keratoderma (EPPK), a highly penetrant autosomal dominant genodermatosis, is characterized by diffuse keratoses on palmplantar epidermis. The keratin 9 gene (KRT9) is responsible for EPPK. To date, phenotypic therapy is the primary treatment for EPPK. Because KRT9 pairs with a type II keratin-binding partner to function in epidermis, identifying the interaction partner is an essential first step in revealing EPPK pathogenesis and its fundamental treatment. In this study, we proved that keratin 6C (KRT6C) is a probable hereterodimer partner for KRT9. In silico model for KRT6C/KRT9 shows a typical coiled-coil structure in their 2B domains. Proteomics analysis shows that KRT6C/KRT9 pair is in a densely connected protein-protein interaction network, where proteins participate jointly in regulating cytoskeleton organization and keratinization. This study shows that co-immunoprecipitation coupled with mass spectroscopy and proteomics analysis provide a sensitive approach, which compensates for inevitable inadequacies of anti-keratin 6C antibody and helps discover the probable hereterodimer partner KRT6C for KRT9. The acknowledgement of KRT6C/KRT9 pairwise relationship may help re-classify EPPK and PC-K6c (a milder form of pachyonychia congenita, caused by KRT6C) as a group of hereditary defects at a molecular-based level, and lay foundation for deciphering the keratin network contributing to EPPK and PC-K6c. SIGNIFICANCE OF THE STUDY: What is already known about this topic? KRT9 and KRT6C are disease-causing factors for epidermolytic palmoplantar keratoderma (EPPK) and a milder form of pachyonychia congenita (PC-K6c), respectively. EPPK and PC-K6c have some symptom similarities. Keratins are the major structural proteins in epithelial cells. Each of the type I keratin is matched by a particular type II keratin to assemble a coiled-coil heterodimer. The hereterodimer partner for KRT9 is unknown. What does this study add? We discovered and proved that KRT6C is a probable hereterodimer partner for KRT9 in palmplantar epidermis in a native endogenous environment by using co-immunoprecipitation coupled with mass spectroscopy and proteomics analysis, etc. The proteomics analysis shows that KRT6C/KRT9 keratin pair is in a densely connected protein-protein interaction network, where proteins participate jointly in regulating intermediate filament-based cytoskeleton organization and keratinization processes. What are the implications of this work? The new understanding of probable KRT6C/KRT9 pairwise correlation may help re-classify the genetic cutaneous disorders EPPK and PC-K6c as a group of hereditary defects at a molecular-based level, and lay foundation for pathogenic mechanism research in EPPK and PC-K6c. The densely related network components derived from the proteomic data using Metascape in the study and pairwise regulation fashion of specific keratin pairs should attract more attention in the further explorations when investigators concern the physiological functions of keratins and the pathogenesis of related skin diseases.
High-throughput proteomics of breast cancer subtypes: Biological characterization and multiple candidate biomarker panels to patients' stratification.
Azevedo ALK, Gomig THB, Batista M … +8 more , Marchini FK, Spautz CC, Rabinovich I, Sebastião APM, Oliveira JC, Gradia DF, Cavalli IJ, Ribeiro EMSF
J Proteomics · 2023 Aug · PMID 37390896 · Publisher ↗
BACKGROUND AND AIMS: The actual classification of breast tumors in subtypes represents an attempt to stratify patients into clinically cohesive groups, nevertheless, clinicians still lack reproducible and reliable protei...
BACKGROUND AND AIMS: The actual classification of breast tumors in subtypes represents an attempt to stratify patients into clinically cohesive groups, nevertheless, clinicians still lack reproducible and reliable protein biomarkers for breast cancer subtype discrimination. In this study, we aimed to access the differentially expressed proteins between these tumors and its biological implications, contributing to the subtype's biological and clinical characterization, and with protein panels for subtype discrimination. METHODS: In our study, we applied high-throughput mass spectrometry, bioinformatic, and machine learning approaches to investigate the proteome of different breast cancer subtypes. RESULTS: We identified that each subtype depends on different protein expression patterns to sustain its malignancy, and also alterations in pathways and processes that can be associated with each subtype and its biological and clinical behaviors. Regarding subtype biomarkers, our panels achieved performances with at least 75% of sensibility and 92% of specificity. In the validation cohort, the panels obtained acceptable to outstanding performances (AUC = 0.740 to 1.00). CONCLUSIONS: In general, our results expand the accuracy of breast cancer subtypes' proteomic landscape and improve the understanding of its biological heterogeneity. In addition, we identified potential protein biomarkers for the stratification of breast cancer patients, improving the repertoire of reliable protein biomarkers. SIGNIFICANCE: Breast cancer is the most diagnosed cancer type worldwide and the most lethal cancer in women. As a heterogeneous disease, breast cancer tumors can be classified into four major subtypes, each presenting particular molecular alterations, clinical behaviors, and treatment responses. Thus, a pivotal step in patient management and clinical decisions is accurately classifying breast tumor subtypes. Currently, this classification is made by the immunohistochemical detection of four classical markers (estrogen receptor, progesterone receptor, HER2 receptor, and the Ki-67 index); however, it is known that these markers alone do not fully discriminate the breast tumor subtypes. Also, the poor understanding of the molecular alterations of each subtype leads to a challenging decision-making process regarding treatment choice and prognostic determination. This study, through high-throughput label-free mass-spectrometry data acquisition and downstream bioinformatic analysis, advances in the proteomic discrimination of breast tumors and achieves an in-depth characterization of the subtype's proteomes. Here, we indicate how the variations in the subtype's proteome can influence the tumor's biological and clinical differences, highlighting the variation in the expression pattern of oncoproteins and tumor suppressor proteins between subtypes. Also, through our machine-learning approach, we propose multi-protein panels with the potential to discriminate the breast cancer subtypes. Our panels achieved high classification performance in our cohort and in the independent validation cohort, demonstrating their potential to improve the current tumor discrimination system as complements to the classical immunohistochemical classification.
Proteomic analysis of the small extracellular vesicles and soluble secretory proteins from cachexia inducing and non-inducing cancer cells.
Chitti SV, Kang T, Fonseka P … +8 more , Marzan AL, Stewart S, Shahi S, Bramich K, Ang CS, Pathan M, Gummadi S, Mathivanan S
Proteomics · 2023 Aug · PMID 37309723 · Publisher ↗
Cancer cachexia is a wasting syndrome characterised by the loss of fat and/or muscle mass in advanced cancer patients. It has been well-established that cancer cells themselves can induce cachexia via the release of seve...
Cancer cachexia is a wasting syndrome characterised by the loss of fat and/or muscle mass in advanced cancer patients. It has been well-established that cancer cells themselves can induce cachexia via the release of several pro-cachectic and pro-inflammatory factors. However, it is unclear how this process is regulated and the key cachexins that are involved. In this study, we validated C26 and EL4 as cachexic and non-cachexic cell models, respectively. Treatment of adipocytes and myotubes with C26 conditioned medium induced lipolysis and atrophy, respectively. We profiled soluble secreted proteins (secretome) as well as small extracellular vesicles (sEVs) released from cachexia-inducing (C26) and non-inducing (EL4) cancer cells by label-free quantitative proteomics. A total of 1268 and 1022 proteins were identified in the secretome of C26 and EL4, respectively. Furthermore, proteomic analysis of sEVs derived from C26 and EL4 cancer cells revealed a distinct difference in the protein cargo. Functional enrichment analysis using FunRich highlighted the enrichment of proteins that are implicated in biological processes such as muscle atrophy, lipolysis, and inflammation in both the secretome and sEVs derived from C26 cancer cells. Overall, our characterisation of the proteomic profiles of the secretory factors and sEVs from cachexia-inducing and non-inducing cancer cells provides insights into tumour factors that promote weight loss by mediating protein and lipid loss in various organs and tissues. Further investigation of these proteins may assist in highlighting potential therapeutic targets and biomarkers of cancer cachexia.
Evaluation of a 'plug and play' nanoflow liquid chromatography system for MS-based proteomic characterization of clinical FFPE specimens.
Mitsa G, Richard VR, Majedi Y … +4 more , Lafleur J, Aguilar-Mahecha A, Basik M, Borchers CH
Expert Rev Proteomics · 2023 · PMID 37309581 · Publisher ↗
INTRODUCTION: Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tumor tissue specimens has gained interest in the last 5 years due to technological advances and improved sample collection, as well as biobanki...
INTRODUCTION: Proteomic analysis of formalin-fixed paraffin-embedded (FFPE) tumor tissue specimens has gained interest in the last 5 years due to technological advances and improved sample collection, as well as biobanking for clinical trials. The real-world implementation of clinical proteomics to these specimens, however, is hampered by tedious sample preparation steps and long instrument acquisition times. AREAS COVERED: To advance the translation of quantitative proteomics into the clinic, we are comparing the performance of the leading commercial nanoflow liquid chromatography (nLC) system (based on literature reviews), the Easy-nLC 1200 (Thermo Fisher Scientific, Waltham, MA, U.S.A.), to the Evosep One HPLC (Evosep Biosystems, Odense, Denmark). We measured FFPE-tissue digests from 21 biological replicates with a similar gradient on both of the LC systems while keeping the on-column amount (1 µg total protein) and the single-shot data-dependent acquisition-based MS/MS method constant. EXPERT OPINION: Overall, the Evosep One facilitates robust and sensitive high-throughput sample acquisition, making it suitable for clinical MS. We found the Evosep One to be a useful platform for positioning mass spectrometry-based proteomics in the clinical setting. The clinical application of nLC/MS will inform clinical decision-making in oncology and other diseases.
Realm of proteomics in breast cancer management and drug repurposing to alleviate intricacies of treatment.
Behera RN, Bisht VS, Giri K … +1 more , Ambatipudi K
Proteomics Clin Appl · 2023 Nov · PMID 37259687 · Publisher ↗
Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breas...
Breast cancer, a multi-networking heterogeneous disease, has emerged as a serious impediment to progress in clinical oncology. Although technological advancements and emerging cancer research studies have mitigated breast cancer lethality, a precision cancer-oriented solution has not been achieved. Thus, this review will persuade the acquiescence of proteomics-based diagnostic and therapeutic options in breast cancer management. Recently, the evidence of breast cancer health surveillance through imaging proteomics, single-cell proteomics, interactomics, and post-translational modification (PTM) tracking, to construct proteome maps and proteotyping for stage-specific and sample-specific cancer subtyping have outperformed conventional ways of dealing with breast cancer by increasing diagnostic efficiency, prognostic value, and predictive response. Additionally, the paradigm shift in applied proteomics for designing a chemotherapy regimen to identify novel drug targets with minor adverse effects has been elaborated. Finally, the potential of proteomics in alleviating the occurrence of chemoresistance and enhancing reprofiled drugs' effectiveness to combat therapeutic obstacles has been discussed. Owing to the enormous potential of proteomics techniques, the clinical recognition of proteomics in breast cancer management can be achievable and therapeutic intricacies can be surmountable.
Integrating analysis of proteome profile and drug screening identifies therapeutic potential of MET pathway for the treatment of malignant peripheral nerve sheath tumor.
Tsuchiya R, Yoshimatsu Y, Noguchi R … +8 more , Sin Y, Ono T, Akiyama T, Kosako H, Yoshida A, Ohtori S, Kawai A, Kondo T
Expert Rev Proteomics · 2023 · PMID 37229542 · Publisher ↗
BACKGROUND: Malignant peripheral nerve sheath tumor (MPNST) is an aggressive sarcoma with a poor prognosis that requires novel therapeutic agents. Proteome information is useful for identifying new therapeutic candidates...
BACKGROUND: Malignant peripheral nerve sheath tumor (MPNST) is an aggressive sarcoma with a poor prognosis that requires novel therapeutic agents. Proteome information is useful for identifying new therapeutic candidates because it directly reflects the biological phenotype. Additionally, in vitro drug screening is an effective tool to identify candidate drugs for common cancers. Hence, we attempted to identify novel therapeutic candidates for MPNST by integrating proteomic analysis and drug screening. METHODS: We performed comprehensive proteomic analysis on 23 MPNST tumor samples using liquid chromatography - tandem mass spectrometry to identify therapeutic targets. We also conducted drug screening of six MPNST cell lines using 214 drugs. RESULTS: Proteomic analysis revealed that the MET and IGF pathways were significantly enriched in the local recurrence/distant metastasis group of MPNST, whereas drug screening revealed that 24 drugs showed remarkable antitumor effects on the MPNST cell lines. By integrating the results of these two approaches, MET inhibitors, crizotinib and foretinib, were identified as novel therapeutic candidates for the treatment of MPNST. CONCLUSIONS: We successfully identified novel therapeutic candidates for the treatment of MPNST, namely crizotinib and foretinib, which target the MET pathway. We hope that these candidate drugs will contribute to the treatment of MPNST.
Integrating intracellular and extracellular proteomic profiling for in-depth investigations of cellular communication in a model of prostate cancer.
Miles HN, Tomlin D, Ricke WA … +1 more , Li L
Proteomics · 2023 Nov · PMID 37226375 · Full text
Cellular communication is essential for cell-cell interactions, maintaining homeostasis and progression of certain disease states. While many studies examine extracellular proteins, the holistic extracellular proteome is...
Cellular communication is essential for cell-cell interactions, maintaining homeostasis and progression of certain disease states. While many studies examine extracellular proteins, the holistic extracellular proteome is often left uncaptured, leaving gaps in our understanding of how all extracellular proteins may impact communication and interaction. We used a cellular-based proteomics approach to more holistically profile both the intracellular and extracellular proteome of prostate cancer. Our workflow was generated in such a manner that multiple experimental conditions can be observed with the opportunity for high throughput integration. Additionally, this workflow is not limited to a proteomic aspect, as metabolomic and lipidomic studies can be integrated for a multi-omics workflow. Our analysis showed coverage of over 8000 proteins while also garnering insights into cellular communication in the context of prostate cancer development and progression. Identified proteins covered a variety of cellular processes and pathways, allowing for the investigation of multiple aspects into cellular biology. This workflow demonstrates advantages for integrating intra- and extracellular proteomic analyses as well as potential for multi-omics researchers. This approach possesses great value for future investigations into the systems biology aspects of disease development and progression.
Proteomic characterization of Opisthorchis felineus exosome-like vesicles and their uptake by human cholangiocytes.
Pakharukova MY, Savina E, Ponomarev DV … +6 more , Gubanova NV, Zaparina O, Zakirova EG, Cheng G, Tikhonova OV, Mordvinov VA
J Proteomics · 2023 Jul · PMID 37225040 · Publisher ↗
The epidemiologically important food-borne trematode Opisthorchis felineus infests the liver biliary tract of fish-eating mammals and causes disorders, including bile duct neoplasia. Many parasitic species release extrac...
The epidemiologically important food-borne trematode Opisthorchis felineus infests the liver biliary tract of fish-eating mammals and causes disorders, including bile duct neoplasia. Many parasitic species release extracellular vesicles (EVs) that mediate host-parasite interaction. Currently, there is no information on O. felineus EVs. Using gel electrophoresis followed by liquid chromatography coupled with tandem mass spectrometry, we aimed to characterize the proteome of EVs released by the adult O. felineus liver fluke. Differential abundance of proteins between whole adult worms and EVs was assessed by semiquantitative iBAQ (intensity-based absolute quantification). Imaging, flow cytometry, inhibitor assays, and colocalization assays were performed to monitor the uptake of the EVs by H69 human cholangiocytes. The proteomic analysis reliably identified 168 proteins (at least two peptides matched a protein). Among major proteins of EVs were ferritin, tetraspanin CD63, helminth defense molecule 1, globin 3, saposin B type domain-containing protein, 60S ribosomal protein, glutathione S-transferase GST28, tubulin, and thioredoxin peroxidase. Moreover, as compared to the whole adult worm, EVs proved to be enriched with tetraspanin CD63, saposin B, helminth defense molecule 1, and Golgi-associated plant pathogenesis-related protein 1 (GAPR1). We showed that EVs are internalized by human H69 cholangiocytes via clathrin-dependent endocytosis, whereas phagocytosis and caveolin-dependent endocytosis do not play a substantial role in this process. Our study describes for the first time proteomes and differential abundance of proteins in whole adult O. felineus worms and EVs released by this food-borne trematode. Studies elucidating the regulatory role of individual components of EVs of liver flukes should be continued to determine which components of EV cargo play the most important part in the pathogenesis of fluke infection and in a closely linked pathology: bile duct neoplasia. SIGNIFICANCE: The food-borne trematode Opisthorchis felineus is a pathogen that causes hepatobiliary disorders in humans and animals. Our study describes for the first time the release of EVs by the liver fluke O. felineus, their microscopic and proteomic characterization, and internalization pathways by human cholangiocytes. Differential abundance of proteins between whole adult worms and EVs was assessed. EVs are enriched with canonical EV markers as well as parasite specific proteins, i.e. tetraspanin CD63, saposin B, helminth defense molecule 1, and others. Our findings will form the basis of the search for potential immunomodulatory candidates with therapeutic potential in the context of inflammatory diseases, as well as novel vaccine candidates.
Proteomic analysis of murine Tsc1-deficient neural stem progenitor cells.
Chiaradia E, Miller I, Renzone G … +6 more , Tognoloni A, Polchi A, De Marco F, Tancini B, Scaloni A, Magini A
J Proteomics · 2023 Jul · PMID 37207814 · Publisher ↗
Tuberous sclerosis complex (TSC) is a rare, multisystem genetic disorder that leads to the development of benign tumors in multiple organs and neurological symptoms. TSC clinical manifestations show a great heterogenicit...
Tuberous sclerosis complex (TSC) is a rare, multisystem genetic disorder that leads to the development of benign tumors in multiple organs and neurological symptoms. TSC clinical manifestations show a great heterogenicity, with most patients presenting severe neuropsychiatric and neurological disorders. TSC is caused by loss-of-function mutations in either TSC1 or TSC2 genes, leading to overexpression of the mechanistic target of rapamycin (mTOR) and, consequently, abnormal cellular growth, proliferation and differentiation as well as to cell migration defects. Beside the growing interest, TSC remains a disorder poorly understood, with limited perspectives in the field of therapeutic strategies. Here we used murine postnatal subventricular zone (SVZ) neural stem progenitor cells (NSPCs) deficient of Tsc1 gene as a TSC model to unravel novel molecular aspects of the pathophysiology of this disease. 2D-DIGE-based proteomic analysis detected 55 differently represented spots in Tsc1-deficient cells, compared to wild-type counterparts, which were associated with 36 protein entries after corresponding trypsinolysis and nanoLC-ESI-Q-Orbitrap-MS/MS analysis. Proteomic results were validated using various experimental approaches. Bioinformatics associated differently represented proteins with oxidative stress and redox pathways, methylglyoxal biosynthesis, myelin sheath, protein S-nitrosylation and carbohydrate metabolism. Because most of these cellular pathways have already been linked to TSC features, these results were useful to clarify some molecular aspects of TSC etiopathogenesis and suggested novel promising therapeutic protein targets. SIGNIFICANCE: Tuberous Sclerosis Complex (TSC) is a multisystemic disorder caused by inactivating mutations of TSC1 or TSC2 genes, which induce overactivation of the mTOR component. The molecular mechanisms underlying the pathogenesis of TSC remain unclear, probably due to complexity of mTOR signaling network. To have a picture of protein abundance changes occurring in TSC disorder, murine postnatal subventricular zone (SVZ) neural stem progenitor cells (NSPCs) deficient of Tsc1 gene were used as a model of disease. Thus, Tsc1-deficient SVZ NSPCs and wild-type cells were comparatively evaluated by proteomics. This analysis evidenced changes in the abundance of proteins involved in oxidative/nitrosative stress, cytoskeleton remodelling, neurotransmission, neurogenesis and carbohydrate metabolism. These proteins might clarify novel molecular aspects of TSC etiopathogenesis and constitute putative molecular targets for novel therapeutic management of TSC-related disorders.
Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum.
Ahsan N, Fornelli L, Najar FZ … +8 more , Gamagedara S, Hossan MR, Rao RSP, Punyamurtula U, Bauer A, Yang Z, Foster SB, Kane MA
Proteomics · 2023 Oct · PMID 37199141 · Full text
Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-spe...
Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.
A proteomic signature and potential pharmacological opportunities in the adaptive resistance to MEK and PI3K kinase inhibition in pancreatic cancer cells.
Aguilar-Valdés A, González-Vela F, Sánchez-Vidal H … +1 more , Martínez-Aguilar J
Proteomics · 2023 Aug · PMID 37140101 · Publisher ↗
Pancreatic cancer is one of the most lethal cancer types and is becoming a leading cause of cancer-related deaths. The limited benefit offered by chemotherapy agents has propelled the search for alternative approaches th...
Pancreatic cancer is one of the most lethal cancer types and is becoming a leading cause of cancer-related deaths. The limited benefit offered by chemotherapy agents has propelled the search for alternative approaches that target specific molecular drivers of cancer growth and progression. Mutant KRas and effector pathways Raf/MEK/ERK and PI3K/Akt are key players in pancreatic cancer; however, preclinical studies have shown adaptive tumour response to combined MEK and PI3K kinase inhibition leading to treatment resistance. There is a critical unmet need to decipher the molecular basis underlying adaptation to this targeted approach. Here, we aimed to identify common protein expression alterations associated with adaptive resistance in KRas-mutant pancreatic cancer cells, and test if it can be overcome by selected already available small molecule drugs. We found a group of 14 proteins with common expression change in resistant cells, including KRas, caveolin-1, filamin-a, eplin, IGF2R and cytokeratins CK-8, -18 and -19. Notably, several proteins have previously been observed in pancreatic cancer cells with intrinsic resistance to the combined kinase inhibition treatment, suggesting a proteomic signature. We also found that resistant cells are sensitive to small molecule drugs ERK inhibitor GDC-0994, S6K1 inhibitor DG2 and statins.
How valuable can proteogenomics be in clinical breast cancer research?
Tran-Huynh AM, Holt MV, Anurag M
Expert Rev Proteomics · 2023 · PMID 37066845 · Publisher ↗
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Using feature selection and Bayesian network identify cancer subtypes based on proteomic data.
Wang Y, Gao X, Ru X … +2 more , Sun P, Wang J
J Proteomics · 2023 May · PMID 37024076 · Publisher ↗
The Cancer Proteome Atlas (TCPA) project collects reverse-phase protein arrays (RPPA)-based proteome datasets from nearly 8000 samples across 32 cancer types. This study aims to investigate the pan-cancer proteome signat...
The Cancer Proteome Atlas (TCPA) project collects reverse-phase protein arrays (RPPA)-based proteome datasets from nearly 8000 samples across 32 cancer types. This study aims to investigate the pan-cancer proteome signature and identify cancer subtypes of glioma, kidney cancer, and lung cancer based on TCPA data. We first visualized the tumor clustering models using t-distributed stochastic neighbour embedding (t-SNE) and bi-clustering heatmap. Then, three feature selection methods (pyHSICLasso, XGBoost, and Random Forest) were performed to select protein features for classifying cancer subtypes in training dataset, and the LibSVM algorithm was empolyed to test classification accuracy in the validation dataset. Clustering analysis revealed that different kinds of tumors have relatively distinct proteomic profiling based on tissue or origin. We identified 20, 10, and 20 protein features with the highest accuracies in classifying subtypes of glioma, kidney cancer, and lung cancer, respectively. The predictive abilities of the selected proteins were confirmed by receiving operating characteristic (ROC) analysis. Finally, the Bayesian network was utilized to explore the protein biomarkers that have direct causal relationships with cancer subtypes. Overall, we highlight the theoretical and technical applications of machine learning based feature selection approaches in the analysis of high-throughput biological data, particularly for cancer biomarker research. SIGNIFICANCE: Functional proteomics is a powerful approach for characterizing cell signaling pathways and understanding their phenotypic effects on cancer development. The TCPA database provides a platform to explore and analyze TCGA pan-cancer RPPA-based protein expression. With the advent of the RPPA technology, the availability of high-throughput data in TCPA platform has made it possible to use machine learning methods to identify protein biomarkers and further differentiate subtypes of cancer based on proteomic data. In this study, we highlight the role of feature selection and Bayesian network in discovery protein biomarker for classifying cancer subtypes based on functional proteomic data. The application of machine learning methods in the analysis of high-throughput biological data, particularly for cancer biomarker researches, which have potential clinical values in developing individualized treatment strategies.
Proteomic and N-glycoproteomic analyses of total subchondral bone protein in patients with primary knee osteoarthritis.
Feng G, Zhou Y, Yan J … +7 more , Wang Z, Yang Y, Zhao W, Wang N, Lu Z, Chen Y, Jin Q
J Proteomics · 2023 May · PMID 37024074 · Publisher ↗
N-glycosylation is an important post-translational modification necessary to maintain the structural and functional properties of proteins. Impaired N-glycosylation has been observed in several diseases. It is significan...
N-glycosylation is an important post-translational modification necessary to maintain the structural and functional properties of proteins. Impaired N-glycosylation has been observed in several diseases. It is significantly modified by the state of cells and is used as a diagnostic or prognostic indicator for multiple human diseases, including cancer and osteoarthritis (OA). Aim of the study was to explore the N-glycosylation levels of subchondral bone proteins in patients with primary knee OA (KOA) and screen for potential biological markers for the diagnosis and treatment of primary KOA. A comparative analysis of total protein N-glycosylation under the cartilage was performed in medial subchondral bone (MSB, N = 5) and lateral subchondral bone (LSB, N = 5) specimens from female patients with primary KOA. To analyse the N-glycosylation sites of the proteins, non-labelled quantitative proteomic and N-glycoproteomic analyses were performed based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) data. Parallel reaction monitoring (PRM) validation experiments were carried out on differential N-glycosylation sites of proteins in selected specimens, including MSB (N = 5) and LSB (N = 5), from patients with primary KOA. In total, 1149 proteins with 1369 unique N-chain glycopeptides were detected, and 1215 N-glycosylation sites were found, in which ptmRS scores for 1163 N-glycosylation sites were ≥ 0.9. In addition, N-glycosylation of the total protein in MSB compared to that in LSB was identified, in which 295 N-glycosylation sites were significantly different, including 75 upregulated and 220 downregulated N-glycosylation sites in MSB samples. Importantly, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses of proteins with differential N-glycosylation sites showed that they were primarily associated with metabolic pathways including ECM-receptor interactions, focal adhesion, protein digestion and absorption, amoebiasis, and complement and coagulation cascades. Finally, PRM experiments confirmed the N-glycosylation sites of collagen type VI, alpha 3 (COL6A3, VAVVQHAPSESVDN[+3]ASMPPVK), aggrecan core protein (ACAN, FTFQEAAN[+3]EC[+57]R, TVYVHAN[+3]QTGYPDPSSR), laminin subunit gamma-1 (LAMC1, IPAIN[+3]QTITEANEK), matrix-remodelling-associated protein 5 (MXRA5, ITLHEN[+3]R), cDNA, FLJ92775, highly similar to Homo sapiens melanoma cell adhesion molecule (MCAM), mRNA(B2R642, C[+57]VASVPSIPGLN[+3]R), and aminopeptidase fragment (Q59E93, AEFN[+3]ITLIHPK) in the array data of the top 20 N-glycosylation sites. These abnormal N-glycosylation patterns provide reliable insights for the development of diagnostic and therapeutic methods for primary KOA.
Updates on the study of lysosomal protein dynamics: possibilities for the clinic.
Arora D, Hackenberg Y, Li J … +1 more , Winter D
Expert Rev Proteomics · 2023 · PMID 36919490 · Publisher ↗
INTRODUCTION: The lysosome is the main degradative organelle of almost all mammalian cells, fulfilling important functions in macromolecule recycling, metabolism, and signaling. Lysosomal dysfunction is connected to a co...
INTRODUCTION: The lysosome is the main degradative organelle of almost all mammalian cells, fulfilling important functions in macromolecule recycling, metabolism, and signaling. Lysosomal dysfunction is connected to a continuously growing number of pathologic conditions, and lysosomal proteins present potential biomarkers for a variety of diseases. Therefore, there is an increasing interest in their analysis in patient samples. AREAS COVERED: We provide an overview of OMICs studies which identified lysosomal proteins as potential biomarkers for pathological conditions, covering proteomics, genomics, and transcriptomics approaches, identified through PubMed searches. With respect to discovery proteomics analyses, mainly lysosomal luminal and associated proteins were detected, while membrane proteins were found less frequently. Comprehensive coverage of the lysosomal proteome was only achieved by ultra-deep-coverage studies, but targeted approaches allowed for the reproducible quantification of lysosomal proteins in diverse sample types. EXPERT OPINION: The low abundance of lysosomal proteins complicates their reproducible analysis in patient samples. Whole proteome shotgun analyses fail in many instances to cover the lysosomal proteome, which is due to under-sampling and/or a lack of sensitivity. With the current state of the art, targeted proteomics assays provide the best performance for the characterization of lysosomal proteins in patient samples.
A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics.
Pham TV, Nguyen VV, Vu D … +4 more , Henneman AA, Richardson RA, Piersma SR, Jimenez CR
Proteomics · 2023 Apr · PMID 36906835 · Publisher ↗
Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performanc...
Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.
Optimised plasma sample preparation and LC-MS analysis to support large-scale proteomic analysis of clinical trial specimens: Application to the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial.
O'Rourke MB, Januszewski AS, Sullivan DR … +10 more , Lengyel I, Stewart AJ, Arya S, Ma RC, Galande S, Hardikar AA, Joglekar MV, Keech AC, Jenkins AJ, Molloy MP
Proteomics Clin Appl · 2023 May · PMID 36891577 · Full text
PURPOSE: Robust, affordable plasma proteomic biomarker workflows are needed for large-scale clinical studies. We evaluated aspects of sample preparation to allow liquid chromatography-mass spectrometry (LC-MS) analysis o...
PURPOSE: Robust, affordable plasma proteomic biomarker workflows are needed for large-scale clinical studies. We evaluated aspects of sample preparation to allow liquid chromatography-mass spectrometry (LC-MS) analysis of more than 1500 samples from the Fenofibrate Intervention and Event Lowering in Diabetes (FIELD) trial of adults with type 2 diabetes. METHODS: Using LC-MS with data-independent acquisition we evaluated four variables: plasma protein depletion, EDTA or citrated anti-coagulant blood collection tubes, plasma lipid depletion strategies and plasma freeze-thaw cycles. Optimised methods were applied in a pilot study of FIELD participants. RESULTS: LC-MS of undepleted plasma conducted over a 45 min gradient yielded 172 proteins after excluding immunoglobulin isoforms. Cibachrome-blue-based depletion yielded additional proteins but with cost and time expenses, while immunodepleting albumin and IgG provided few additional identifications. Only minor variations were associated with blood collection tube type, delipidation methods and freeze-thaw cycles. From 65 batches involving over 1500 injections, the median intra-batch quantitative differences in the top 100 proteins of the plasma external standard were less than 2%. Fenofibrate altered seven plasma proteins. CONCLUSIONS AND CLINICAL RELEVANCE: A robust plasma handling and LC-MS proteomics workflow for abundant plasma proteins has been developed for large-scale biomarker studies that balance proteomic depth with time and resource costs.
Proteomic analysis reveals CAAP1 negatively correlates with platinum resistance in ovarian cancer.
Ni M, Zhou J, Gong W … +7 more , Jiang R, Li X, Dai W, Yin Z, Chen Z, Zheng Z, Zhu J
J Proteomics · 2023 Apr · PMID 36870674 · Publisher ↗
The present study sought to investigate the correlation between CAAP1 and platinum resistance in ovarian cancer and to preliminarily explore the potential biological function of CAAP1. Proteomic analysis was used to anal...
The present study sought to investigate the correlation between CAAP1 and platinum resistance in ovarian cancer and to preliminarily explore the potential biological function of CAAP1. Proteomic analysis was used to analyze differentially expressed proteins in platinum-sensitive and -resistant tissue samples of ovarian cancer. The Kaplan-Meier plotter was used for prognostic analysis. Immunohistochemistry assay and chi-square test were employed to explore the relationship between CAAP1 and platinum resistance in tissue samples. Lentivirus transfection, immunoprecipitation-mass spectrometry, and bioinformatics analysis were used to determine the potential biological function of CAAP1. Based on results, the expression level of CAAP1 was significantly higher in platinum-sensitive tissues compared to that in resistant tissues. Chi-square test demonstrated that there is a negative correlation between high expression of CAAP1 and platinum resistance. Overexpression of CAAP1 increased cis‑platinum sensitivity of the A2780/DDP cell line likely via the mRNA splicing pathway by interacting with the splicing factor AKAP17A. In summary, there is a negative correlation between high expression of CAAP1 and platinum resistance. CAAP1 might be a potential biomarker for platinum resistance in ovarian cancer. SIGNIFICANCE: Platinum resistance is a key factor affecting the survival of ovarian cancer patients. Understanding the mechanisms of platinum resistance is highly important for ovarian cancer management. Here, we performed the DIA- and DDA-based proteomics to analyze differentially expressed proteins in tissue and cell samples of ovarian cancer. We found that the protein identified as CAAP1, which was first reported to be involved in the regulation of apoptosis, may be negatively correlates with platinum resistance in ovarian cancer. In addition, we also found that CAAP1 enhanced the sensitivity of platinum-resistant cells to cis‑platinum via the mRNA splicing pathway by interacting with the splicing factor AKAP17A. Our data would be useful to reveal novel molecular mechanisms of platinum resistance in ovarian cancer.
Age-stratified proteomic characteristics and identification of promising precise clinical treatment targets of colorectal cancer.
Wang Q, Zhou Y, Zhou G … +5 more , Qin G, Tan C, Yin T, Zhao D, Yao S
J Proteomics · 2023 Apr · PMID 36870673 · Publisher ↗
Colorectal cancer (CRC) is an extremely lethal disease worldwide. However, the underlying pathogenesis remains unclear. This study aimed to reveal the distinct characteristics of age-stratified CRC at the protein level a...
Colorectal cancer (CRC) is an extremely lethal disease worldwide. However, the underlying pathogenesis remains unclear. This study aimed to reveal the distinct characteristics of age-stratified CRC at the protein level and explore precise treatment targets. Patients who underwent surgical removal with pathologically confirmed CRC at China-Japan Friendship Hospital from January 2020 to October 2021 were recruited, cancer and para-carcinoma tissues (> 5 cm) were detected by mass spectrometry. Ninety-six clinical samples were collected and divided into three groups according to age: young (≤ 50 years), middle-aged (51-69 years), and old (≥ 70 years). Quantitative proteomic analysis was performed, as well as comprehensive bioinformatic analysis based on the Human Protein Atlas, Clinical Proteomic Tumor Analysis Consortium and Connectivity Map databases. The numbers of upregulated and downregulated proteins were 1315 and 560 in the young group, 757 and 311 in the old group, and 1052 and 468 in the middle-aged group, respectively. Bioinformatic analysis showed that these differentially expressed proteins had different molecular functions and participated in extensive signaling pathways. We also revealed ADH1B, ARRDC1, GATM, GTF2H4, MGME1, and LILRB2 as possible cancer-promoting molecules, which might serve as potential prognostic biomarkers and precise therapeutic targets for CRC. SIGNIFICANCE: This study comprehensively characterized the proteomic profiles of age-stratified colorectal cancer patients, focusing on the differentially expressed proteins between cancer and paracancerous tissues in different age groups, in an effort to find corresponding potential prognostic biomarkers and therapeutic targets. In addition, this study provides potentially valuable clinical small molecule inhibitory agents.
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