Multitarget Potential Drug Candidates for High-Grade Gliomas Identified by Multiple Reaction Monitoring Coupled with In Silico Drug Repurposing.

High-grade gliomas (HGGs) are extremely aggressive primary brain tumors with high mortality rates. Despite notable progress achieved by clinical research and biomarkers emerging from proteomics studies, efficacious drugs and therapeutic targets are limited. This study used targeted proteomics, in silico molecular docking, and simulation-based drug repurposing to identify potential drug candidates for HGGs. Importantly, we performed multiple reaction monitoring (MRM) on differentially expressed proteins with putative roles in the development and progression of HGGs based on our previous work and the published literature. Furthermore, in silico molecular docking-based drug repurposing was performed with a customized library of FDA-approved drugs to identify multitarget-directed ligands. The top drug candidates such as Pazopanib, Icotinib, Entrectinib, Regorafenib, and Cabozantinib were explored for their drug-likeness properties using the SwissADME. Pazopanib exhibited binding affinities with a maximum number of proteins and was considered for molecular dynamic simulations and cell toxicity assays. HGG cell lines showed enhanced cytotoxicity and cell proliferation inhibition with Pazopanib and Temozolomide combinatorial treatment compared to Temozolomide alone. To the best of our knowledge, this is the first study combining MRM with molecular docking and simulation-based drug repurposing to identify potential drug candidates for HGG. While the present study identified five multitarget-directed potential drug candidates, future clinical studies in larger cohorts are crucial to evaluate the efficacy of these molecular candidates. The research strategy and methodology used in the present study offer new avenues for innovation in drug discovery and development which may prove useful, particularly for cancers with low cure rates.

A proteome-level view of brain tumors for a better understanding of novel diagnosis, prognosis, and therapy.

INTRODUCTION: Brain tumors are complex and heterogeneous malignancies with significant challenges in diagnosis, prognosis, and therapy. Proteomics, the large-scale study of proteins and their functions, has emerged as a powerful tool to comprehensively investigate the molecular mechanisms underlying brain tumor regulation. AREAS COVERED: This review explores brain tumors from a proteomic standpoint, highlighting recent progress and insights gained through proteomic methods. It delves into the proteomic techniques employed and underscores potential biomarkers for early detection, prognosis, and treatment planning. Recent PubMed Central proteomic studies (2017-present) are discussed, summarizing findings on altered protein expression, post-translational changes, and protein interactions. This sheds light on brain tumor signaling pathways and their significance in innovative therapeutic approaches. EXPERT OPINION: Proteomics offers immense potential for revolutionizing brain tumor diagnosis and therapy. To unlock its full benefits, further translational research is crucial. Combining proteomics with other omics data enhances our grasp of brain tumors. Validating and translating proteomic biomarkers are vital for better patient results. Challenges include tumor complexity, lack of curated proteomic databases, and the need for collaboration between researchers and clinicians. Overcoming these challenges requires investment in technology, data sharing, and translational research.

Brain tumors are complex and diverse types of cancer that present significant challenges in their diagnosis, prognosis, and treatment. Proteomics, a field that focuses on studying proteins and their functions on a large scale has emerged as a powerful tool for understanding how brain tumors work at the molecular level. In this review, we offer a detailed look into the role of proteomics in studying brain tumor regulation, discussing recent advancements and insights gained from proteomic techniques. We explore various mass spectrometry-based proteomic methods, which help uncover unique protein patterns associated with brain tumors. By analyzing changes in protein expression, modifications, interactions, and location within cells, researchers have gained important knowledge about the underlying mechanisms of brain tumors. Proteomics also plays a crucial role in identifying potential biomarkers for early detection, predicting patient outcomes, and developing targeted therapies and immunotherapies. However, there are still challenges to overcome, such as integrating data from different 'omics' fields, standardizing protocols and analysis procedures and utilizing artificial intelligence to interpret complex proteomic data. We require more robust attempts at validating and translating all these findings for patient benefit.

Targeting MALAT1 Augments Sensitivity to PARP Inhibition by Impairing Homologous Recombination in Prostate Cancer.

PARP inhibitors (PARPi) have emerged as a promising targeted therapeutic intervention for metastatic castrate-resistant prostate cancer (mCRPC). However, the clinical utility of PARPi is limited to a subset of patients who harbor aberrations in the genes associated with the homologous recombination (HR) pathway. Here, we report that targeting metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), an oncogenic long noncoding RNA (lncRNA), contrives a BRCAness-like phenotype, and augments sensitivity to PARPi. Mechanistically, we show that MALAT1 silencing reprograms the homologous recombination (HR) transcriptome and makes prostate cancer cells more vulnerable to PARPi. Particularly, coinhibition of MALAT1 and PARP1 exhibits a decline in clonogenic survival, delays resolution of γH2AX foci, and reduces tumor burden in mice xenograft model. Moreover, we show that miR-421, a tumor suppressor miRNA, negatively regulates the expression of HR genes, while in aggressive prostate cancer cases, miR-421 is sequestered by MALAT1, leading to increased expression of HR genes. Conclusively, our findings suggest that MALAT1 ablation confers sensitivity to PARPi, thus highlighting an alternative therapeutic strategy for patients with castration-resistant prostate cancer (CRPC), irrespective of the alterations in HR genes. SIGNIFICANCE: PARPi are clinically approved for patients with metastatic CRPC carrying mutations in HR genes, but are ineffective for HR-proficient prostate cancer. Herein, we show that oncogenic lncRNA, MALAT1 is frequently overexpressed in advanced stage prostate cancer and plays a crucial role in maintaining genomic integrity. Importantly, we propose a novel therapeutic strategy that emphasizes MALAT1 inhibition, leading to HR dysfunction in both HR-deficient and -proficient prostate cancer, consequently augmenting their susceptibility to PARPi.

Loss of PERK function promotes ferroptosis by downregulating SLC7A11 (System Xc⁻) in colorectal cancer.

Ferroptosis, a genetically and biochemically distinct form of programmed cell death, is characterised by an iron-dependent accumulation of lipid peroxides. Therapy-resistant tumor cells display vulnerability toward ferroptosis. Endoplasmic Reticulum (ER) stress and Unfolded Protein Response (UPR) play a critical role in cancer cells to become therapy resistant. Tweaking the balance of UPR to make cancer cells susceptible to ferroptotic cell death could be an attractive therapeutic strategy. To decipher the emerging contribution of ER stress in the ferroptotic process, we observe that ferroptosis inducer RSL3 promotes UPR (PERK, ATF6, and IRE1α), along with overexpression of cystine-glutamate transporter SLC7A11 (System Xc-). Exploring the role of a particular UPR arm in modulating SLC7A11 expression and subsequent ferroptosis, we notice that PERK is selectively critical in inducing ferroptosis in colorectal carcinoma. PERK inhibition reduces ATF4 expression and recruitment to the promoter of SLC7A11 and results in its downregulation. Loss of PERK function not only primes cancer cells for increased lipid peroxidation but also limits in vivo colorectal tumor growth, demonstrating active signs of ferroptotic cell death in situ. Further, by performing TCGA data mining and using colorectal cancer patient samples, we demonstrate that the expression of PERK and SLC7A11 is positively correlated. Overall, our experimental data indicate that PERK is a negative regulator of ferroptosis and loss of PERK function sensitizes colorectal cancer cells to ferroptosis. Therefore, small molecule PERK inhibitors hold huge promise as novel therapeutics and their potential can be harnessed against the apoptosis-resistant condition.

Proteomic Investigation of COVID-19 Severity During the Tsunamic Second Wave in Mumbai.

Maharashtra was severely affected during the noxious second wave of COVID-19, with the highest number of cases recorded across India. The emergence of new symptoms and dysregulation of multiple organs resulted in high disease severity during the second wave which led to increased difficulties in understanding the molecular mechanisms behind the disease pathology. Exploring the underlying factors can help to relieve the burden on the medical communities to some extent by prioritizing the patients and, at the same time, opening avenues for improved treatments. In the current study, we have performed a mass-spectrometry-based proteomic analysis to investigate the disease pathology using nasopharyngeal swab samples collected from the COVID-19 patients in the Mumbai region of Maharashtra over the period of March-June 2021, the peak of the second wave. A total of 59 patients, including 32 non-severe and 27 severe cases, were considered for this proteomic study. We identified 23 differentially regulated proteins in severe patients as a host response to infection. In addition to the previously identified innate mechanisms of neutrophil and platelet degranulation, this study revealed significant alterations of anti-microbial peptide pathways in severe conditions, illustrating its role in the severity of the infectious strain of COVID-19 during the second wave. Furthermore, myeloperoxidase, cathepsin G, and profilin-1 were identified as potential therapeutic targets of the FDA-approved drugs dabrafenib, ZINC4097343, and ritonavir. This study has enlightened the role of the anti-microbial peptide pathway associated with the second wave in India and proposed its importance in potential therapeutics for COVID-19.

Integrative Proteomic and Pharmacological Analysis of Colon Cancer Reveals the Classical Lipogenic Pathway with Prognostic and Therapeutic Opportunities.

Despite recent advancements, the high mortality rate remains a concern in colon cancer (CAC). Identification of therapeutic markers could prove to be a great asset in CAC management. Multiple studies have reported hyperactivation of de novo lipogenesis (DNL), but its association with the pathology is unclear. This study aims to establish the importance as well as the prognostic and therapeutic potential of DNL in CAC. The key lipogenic enzymes fatty acid synthase along with ATP citrate lyase were quantified using an LC-MS/MS-based targeted proteomics approach in the samples along with the matched controls. The potential capacity of the proteins to distinguish between the tumor and controls was demonstrated using random forest-based class prediction analysis using the peptide intensities. Furthermore, in-depth proteomics of DNL inhibition in the CAC cell line revealed the significance of the pathway in proliferation and metastasis. DNL inhibition affected the major signaling pathways, including DNA repair, PI3K-AKT-mTOR pathway, membrane trafficking, proteasome, etc. The study revealed the upregulation of 26S proteasome machinery as a result of the treatment with subsequent induction of apoptosis. Again, in silico molecular docking-based drug repurposing was performed to find potential drug candidates. Furthermore, we have demonstrated that blocking DNL could be explored as a therapeutic option in CAC treatment.

EZH2-H3K27me3 mediated KRT14 upregulation promotes TNBC peritoneal metastasis.

Triple-Negative Breast Cancer (TNBC) has a poor prognosis and adverse clinical outcomes among all breast cancer subtypes as there is no available targeted therapy. Overexpression of Enhancer of zeste homolog 2 (EZH2) has been shown to correlate with TNBC's poor prognosis, but the contribution of EZH2 catalytic (H3K27me3) versus non-catalytic EZH2 (NC-EZH2) function in TNBC progression remains elusive. We reveal that selective hyper-activation of functional EZH2 (H3K27me3) over NC-EZH2 alters TNBC metastatic landscape and fosters its peritoneal metastasis, particularly splenic. Instead of H3K27me3-mediated repression of gene expression; here, it promotes KRT14 transcription by attenuating binding of repressor SP1 to its promoter. Further, KRT14 loss significantly reduces TNBC migration, invasion, and peritoneal metastasis. Consistently, human TNBC metastasis displays positive correlation between H3K27me3 and KRT14 levels. Finally, EZH2 knockdown or H3K27me3 inhibition by EPZ6438 reduces TNBC peritoneal metastasis. Altogether, our preclinical findings suggest a rationale for targeting TNBC with EZH2 inhibitors.

Modulation of DNA/RNA Methylation by Small-Molecule Modulators and Their Implications in Cancer.

Chromatin is an organized complex of DNA, histone proteins, and RNA. Chromatin modifications include DNA methylation, RNA methylation, and histone acetylation and methylation. The methylation of chromatin complexes predominantly alters the regulation of gene expression, and its deregulation is associated with several human diseases including cancer. Cancer is a disease characterized by dynamic changes in the genetic and epigenetic architecture of a cell. Altered DNA methylation by DNA methyltransferases (DNMTs) and m6A RNA methylation facilitate tumor initiation and progression and thus serve as critical targets for cancer therapy. Small-molecule modulators of these epigenetic targets are at the hotspots of current cancer drug discovery research. Indeed, recent studies have led to the discovery of several chemical modulators against these targets, some of which have already gained approval for cancer therapy while others are undergoing clinical trials. In this chapter, we will focus on the role of small-molecule modulators in regulating DNA/RNA methylation and their implications in cancer.

Demystifying the CXCR4 conundrum in cancer biology: Beyond the surface signaling paradigm.

The oncogenic chemokine duo CXCR4-CXCL12/SDF-1 (C-X-C Receptor 4-C-X-C Ligand 12/ Stromal-derived factor 1) has been the topic of intense scientific disquisitions since Muller et al., in her ground-breaking research, described this axis as a critical determinant of organ-specific metastasis in breast cancer. Elevated CXCR4 levels correlate with distant metastases, poor prognosis, and unfavourable outcomes in most solid tumors. Therapeutic impediment of the axis in clinics with Food and Drug Administration (FDA) approved inhibitors like AMD3100 or Plerixafor yield dubious results, contrary to pre-clinical developments. Clinical trials entailing inhibition of CXCR7 (C-X-C Receptor 7), another convicted chemokine receptor that exhibits affinity for CXCL12, reveal outcomes analogous to that of CXCR4-CXCL12 axis blockade. Of note, the cellular CXCR4 knockout phenotype varies largely from that of inhibitor treatments. These shaky findings pique great curiosity to delve further into the realm of this infamous chemokine receptor to provide a probable explanation. A multitude of recent reports suggests the presence of an increased intracellular CXCR4 pool in various cancers, both cytoplasmic and nuclear. This intracellular CXCR4 protein reserve seems active as it correlates with vital tumor attributes, viz. prognosis, aggressiveness, metastasis, and disease-free survival. Diminishing this entire intracellular CXCR4 load apart from the surface signals looks encouraging from a therapeutic point of view. Transcending beyond the classically accepted concept of ligand-mediated surface signaling, this review sheds new light on plausible associations of intracellularly compartmentalised CXCR4 with various aspects of tumorigenesis. Besides, this review also puts forward a comprehensive account of CXCR4 regulation in different cancers.

Cytokine chemokine network in tumor microenvironment: Impact on CSC properties and therapeutic applications.

A subpopulation of cells in many cancers has stem cell traits, mediates metastasis, and contributes to treatment resistance. These cells are considered as cancer stem cells (CSCs). CSC properties of tumor cells are immensely regulated by close interactions with tumor microenvironment components such as mesenchymal stem cells, tumor related fibroblasts, adipocytes, endothelial cells, and immune cells via the intricate network of cytokines, chemokines, and growth factors. Inflammatory cytokines including interleukin (IL)-1, IL-6, and IL-8 play a major role in these interactions via the activation of signal transduction pathways like Stat3/NF-κB etc. in stromal and tumor cells. The activation of these pathways increases the release of more cytokines, resulting in positive feedback loops which help in CSC self-renewal. The pathways controlled by these cytokine loops are similar to those that are active during chronic inflammation and wound healing, suggesting that they might have critical role in establishing relationship between inflammation and cancer. Anti-inflammatory drugs have been identified to inhibit these cytokines and their receptor mediated pathways. These agents have the potential to target CSCs by inhibiting signals from the tumor microenvironment and considered to be a potential candidate for future therapeutics. The significance of cytokines released from the tumor microenvironment in different phases of cancer, as well as their potential application in cancer therapeutics is discussed in this article.

Proteomics advances towards developing SARS-CoV-2 therapeutics using in silico drug repurposing approaches.

Standing amidst the COVID-19 pandemic, we have faced major medical and economic crisis in recent times which remains to be an unresolved issue till date. Although the scientific community has made significant progress towards diagnosis and understanding the disease; however, effective therapeutics are still lacking. Several omics-based studies, especially proteomics and interactomics, have contributed significantly in terms of identifying biomarker panels that can potentially be used for the disease prognosis. This has also paved the way to identify the targets for drug repurposing as a therapeutic alternative. US Food and Drug Administration (FDA) has set in motion more than 500 drug development programs on an emergency basis, most of them are focusing on repurposed drugs. Remdesivir is one such success of a robust and quick drug repurposing approach. The advancements in omics-based technologies has allowed to explore altered host proteins, which were earlier restricted to only SARS-CoV-2 protein signatures. In this article, we have reviewed major contributions of proteomics and interactomics techniques towards identifying therapeutic targets for COVID-19. Furthermore, in-silico molecular docking approaches to streamline potential drug candidates are also discussed.

Recent advances in mass-spectrometry based proteomics software, tools and databases.

The field of proteomics immensely depends on data generation and data analysis which are thoroughly supported by software and databases. There has been a massive advancement in mass spectrometry-based proteomics over the last 10 years which has compelled the scientific community to upgrade or develop algorithms, tools, and repository databases in the field of proteomics. Several standalone software, and comprehensive databases have aided the establishment of integrated omics pipeline and meta-analysis workflow which has contributed to understand the disease pathobiology, biomarker discovery and predicting new therapeutic modalities. For shotgun proteomics where Data Dependent Acquisition is performed, several user-friendly software are developed that can analyse the pre-processed data to provide mechanistic insights of the disease. Likewise, in Data Independent Acquisition, pipelines are emerged which can accomplish the task from building the spectral library to identify the therapeutic targets. Furthermore, in the age of big data analysis the implications of machine learning and cloud computing are appending robustness, rapidness and in-depth proteomics data analysis. The current review talks about the recent advancement, and development of software, tools, and database in the field of mass-spectrometry based proteomics.

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples.

Recent advances in mass spectrometry have resulted in deep proteomic analysis along with the generation of robust and reproducible datasets. However, despite the considerable technical advancements, sample preparation from biospecimens such as patient blood, CSF, and tissue still poses considerable challenges. For identifying biomarkers, tissue proteomics often provides an attractive sample source to translate the research findings from the bench to the clinic. It can reveal potential candidate biomarkers for early diagnosis of cancer and neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, etc. Tissue proteomics also yields a wealth of systemic information based on the abundance of proteins and helps to address interesting biological questions. Quantitative proteomics analysis can be grouped into two broad categories: a label-based and a label-free approach. In the label-based approach, proteins or peptides are labeled using stable isotopes such as SILAC (stable isotope labeling with amino acids in cell culture) or by chemical tags such as ICAT (isotope-coded affinity tags), TMT (tandem mass tag) or iTRAQ (isobaric tag for relative and absolute quantitation). Label-based approaches have the advantage of more accurate quantitation of proteins and using isobaric labels, multiple samples can be analyzed in a single experiment. The label-free approach provides a cost-effective alternative to label-based approaches. Hundreds of patient samples belonging to a particular cohort can be analyzed and compared with other cohorts based on clinical features. Here, we have described an optimized quantitative proteomics workflow for tissue samples using label-free and label-based proteome profiling methods, which is crucial for applications in life sciences, especially biomarker discovery-based projects.

CXCR4 intracellular protein promotes drug resistance and tumorigenic potential by inversely regulating the expression of Death Receptor 5.

Chemokine receptor CXCR4 overexpression in solid tumors has been strongly associated with poor prognosis and adverse clinical outcome. However, blockade of CXCL12-CXCR4 signaling axis by inhibitors like Nox-A12, FDA approved CXCR4 inhibitor drug AMD3100 have shown limited clinical success in cancer treatment. Therefore, exclusive contribution of CXCR4-CXCL12 signaling in pro-tumorigenic function is questionable. In our pursuit to understand the impact of chemokine signaling in carcinogenesis, we reveal that instead of CXCR4-CXCL12 signaling, presence of CXCR4 intracellular protein augments paclitaxel resistance and pro-tumorigenic functions. In search of pro-apoptotic mechanisms for CXCR4 mediated drug resistance; we discover that DR5 is a new selective target of CXCR4 in breast and colon cancer. Further, we detect that CXCR4 directs the differential recruitment of transcription factors p53 and YY1 to the promoter of DR5 in course of its transcriptional repression. Remarkably, inhibiting CXCR4-ligand-mediated signals completely fails to block the above phenotype. Overexpression of different mutant versions of CXCR4 lacking signal transduction capabilities also result in marked downregulation of DR5 expression in colon cancer indeed confirms the reverse relationship between DR5 and intracellular CXCR4 protein expression. Irrespective of CXCR4 surface expression, by utilizing stable gain and loss of function approaches, we observe that intracellular CXCR4 protein selectively resists and sensitizes colon cancer cells against paclitaxel therapy in vitro and in vivo. Finally, performing TCGA data mining and using human breast cancer patient samples, we demonstrate that expression of CXCR4 and DR5 are inversely regulated. Together, our data suggest that targeting CXCR4 intracellular protein may be critical to dampen the pro-tumorigenic functions of CXCR4.

Proteomics and Machine Learning Approaches Reveal a Set of Prognostic Markers for COVID-19 Severity With Drug Repurposing Potential.

The pestilential pathogen SARS-CoV-2 has led to a seemingly ceaseless pandemic of COVID-19. The healthcare sector is under a tremendous burden, thus necessitating the prognosis of COVID-19 severity. This in-depth study of plasma proteome alteration provides insights into the host physiological response towards the infection and also reveals the potential prognostic markers of the disease. Using label-free quantitative proteomics, we performed deep plasma proteome analysis in a cohort of 71 patients (20 COVID-19 negative, 18 COVID-19 non-severe, and 33 severe) to understand the disease dynamics. Of the 1200 proteins detected in the patient plasma, 38 proteins were identified to be differentially expressed between non-severe and severe groups. The altered plasma proteome revealed significant dysregulation in the pathways related to peptidase activity, regulated exocytosis, blood coagulation, complement activation, leukocyte activation involved in immune response, and response to glucocorticoid biological processes in severe cases of SARS-CoV-2 infection. Furthermore, we employed supervised machine learning (ML) approaches using a linear support vector machine model to identify the classifiers of patients with non-severe and severe COVID-19. The model used a selected panel of 20 proteins and classified the samples based on the severity with a classification accuracy of 0.84. Putative biomarkers such as angiotensinogen and SERPING1 and ML-derived classifiers including the apolipoprotein B, SERPINA3, and fibrinogen gamma chain were validated by targeted mass spectrometry-based multiple reaction monitoring (MRM) assays. We also employed an in silico screening approach against the identified target proteins for the therapeutic management of COVID-19. We shortlisted two FDA-approved drugs, namely, selinexor and ponatinib, which showed the potential of being repurposed for COVID-19 therapeutics. Overall, this is the first most comprehensive plasma proteome investigation of COVID-19 patients from the Indian population, and provides a set of potential biomarkers for the disease severity progression and targets for therapeutic interventions.

Proteomic investigation reveals dominant alterations of neutrophil degranulation and mRNA translation pathways in patients with COVID-19.

The altered molecular proteins and pathways in response to COVID-19 infection are still unclear. Here, we performed a comprehensive proteomics-based investigation of nasopharyngeal swab samples from patients with COVID-19 to study the host response by employing simple extraction strategies. Few of the host proteins such as interleukin-6, L-lactate dehydrogenase, C-reactive protein, Ferritin, and aspartate aminotransferase were found to be upregulated only in COVID-19-positive patients using targeted multiple reaction monitoring studies. The most important pathways identified by enrichment analysis were neutrophil degranulation, interleukin-12 signaling pathways, and mRNA translation of proteins thus providing the detailed investigation of host response in COVID-19 infection. Thus, we conclude that mass spectrometry-detected host proteins have a potential for disease severity progression; however, suitable validation strategies should be deployed for the clinical translation. Furthermore, the in silico docking of potential drugs with host proteins involved in the interleukin-12 signaling pathway might aid in COVID-19 therapeutic interventions.

Salinomycin inhibits epigenetic modulator EZH2 to enhance death receptors in colon cancer stem cells.

Drug resistance is one of the trademark features of Cancer Stem Cells (CSCs). We and others have recently shown that paucity of functional death receptors (DR4/5) on the cell surface of tumour cells is one of the major reasons for drug resistance, but their involvement in the context of in CSCs is poorly understood. By harnessing CSC specific cytotoxic function of salinomycin, we discovered a critical role of epigenetic modulator EZH2 in regulating the expression of DRs in colon CSCs. Our unbiased proteome profiler array approach followed by ChIP analysis of salinomycin treated cells indicated that the expression of DRs, especially DR4 is epigenetically repressed in colon CSCs. Concurrently, EZH2 knockdown demonstrated increased expression of DR4/DR5, significant reduction of CSC phenotypes such as spheroid formation in-vitro and tumorigenic potential in-vivo in colon cancer. TCGA data analysis of human colon cancer clinical samples shows strong inverse correlation between EZH2 and DR4. Taken together, this study provides an insight about epigenetic regulation of DR4 in colon CSCs and advocates that drug-resistant colon cancer can be therapeutically targeted by combining TRAIL and small molecule EZH2 inhibitors.

A proteogenomic approach to target neoantigens in solid tumors.

INTRODUCTION: Proteogenomic techniques find applications in identifying novel cancer-specific peptides called neoantigens; they are non-self peptides derived from tumor-specific non-synonymous mutations. These peptides with MHCs are recognized by the T cells and induce an antitumor response. Due to their selective expression of tumor cells, neoantigens are considered attractive targets for cancer immunotherapy. AREAS COVERED: In this review, we have discussed the proteogenomic strategies to identify neoantigens. We have also provided a neoantigen identification pipeline using data from whole-exome sequencing, RNA sequencing, and MHC peptidomics. Further, we have reviewed recent tools for neoantigen discovery. EXPERT COMMENTARY: The limitations in instrument sensitivity and availability of bioinformatics tools have restricted the identification of neoantigens from tumor samples. Nonetheless, the recent improvement in genome sequencing, mass spectrometry technologies, and the development of reliable algorithms for epitope prediction provide hope for efficient identification of neoantigens. Translating this workflow on patient samples would represent a massive advancement in neoantigen identification methods, leading to the constitution of novel personalized neoantigen cancer vaccines.