Establishment and validation of the autophagy-related ceRNA network in irreversible pulpitis.

BACKGROUND: The molecular mechanisms underlying the onset and progression of irreversible pulpitis have been studied for decades. Many studies have indicated a potential correlation between autophagy and this disease. Against the background of the competing endogenous RNA (ceRNA) theory, protein-coding RNA functions are linked with long noncoding RNAs (lncRNAs) and microRNAs (miRNAs). This mechanism has been widely studied in various fields but has rarely been reported in the context of irreversible pulpitis. The hub genes selected under this theory may represent the key to the interaction between autophagy and irreversible pulpitis. RESULTS: Filtering and differential expression analyses of the GSE92681 dataset, which contains data from 7 inflamed and 5 healthy pulp tissue samples, were conducted. The results were intersected with autophagy-related genes (ARGs), and 36 differentially expressed ARGs (DE-ARGs) were identified. Functional enrichment analysis and construction of the protein‒protein interaction (PPI) network of DE-ARGs were performed. Coexpression analysis was conducted between differentially expressed lncRNAs (DElncRNAs) and DE-ARGs, and 151 downregulated and 59 upregulated autophagy-related DElncRNAs (AR-DElncRNAs) were identified. StarBase and multiMiR were then used to predict related microRNAs of AR-DElncRNAs and DE-ARGs, respectively. We established ceRNA networks including 9 hub lncRNAs (HCP5 and AC112496.1 ↑; FENDRR, AC099850.1, ZSWIM8-AS1, DLX6-AS1, LAMTOR5-AS1, TMEM161B-AS1 and AC145207.5 ↓), which were validated by a qRT‒PCR analysis of pulp tissue from patients with irreversible pulpitis. CONCLUSION: We constructed two networks consisting of 9 hub lncRNAs based on the comprehensive identification of autophagy-related ceRNAs. This study may provide novel insights into the interactive relationship between autophagy and irreversible pulpitis and identifies several lncRNAs that may serve as potential biological markers.

Transcriptome Profiling in Autoimmune Diseases

Autoimmune diseases are a group of different inflammatory disorders characterized by systemic or localized inflammation, affecting approximately 0.1–1% of the general population. Several studies suggest that genetic risk loci are shared between different autoimmune diseases and pathogenic mechanisms may also be shared. The strategy of performing differential gene expression profiles in autoimmune disorders has unveiled new transcripts that may be shared among these disorders. Microarray technology and bioinformatics offer the most comprehensive molecular evaluations and it is widely used to understand the changes in gene expression in specific organs or in peripheral blood cells. The major goal of transcriptome studies is the identification of specific biomarkers for different diseases. It is believed that such knowledge will contribute to the development of new drugs, new strategies for early diagnosis, avoiding tissue autoimmune destruction, or even preventing the development of autoimmune disease. In this review, we primarily focused on the transcription profiles of three typical autoimmune disorders, including type 1 diabetes mellitus (destruction of pancreatic islet beta cells), systemic lupus erythematosus (immune complex systemic disorder affecting several organs and tissues), and multiple sclerosis (inflammatory and demyelinating disease of the nervous system). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2014, 2022.

Aid or Antagonize: Nuclear Long Noncoding RNAs Regulate Host Responses and Outcomes of Viral Infections.

Long noncoding RNAs (lncRNAs) are transcripts measuring >200 bp in length and devoid of protein-coding potential. LncRNAs exceed the number of protein-coding mRNAs and regulate cellular, developmental, and immune pathways through diverse molecular mechanisms. In recent years, lncRNAs have emerged as epigenetic regulators with prominent roles in health and disease. Many lncRNAs, either host or virus-encoded, have been implicated in critical cellular defense processes, such as cytokine and antiviral gene expression, the regulation of cell signaling pathways, and the activation of transcription factors. In addition, cellular and viral lncRNAs regulate virus gene expression. Viral infections and associated immune responses alter the expression of host lncRNAs regulating immune responses, host metabolism, and viral replication. The influence of lncRNAs on the pathogenesis and outcomes of viral infections is being widely explored because virus-induced lncRNAs can serve as diagnostic and therapeutic targets. Future studies should focus on thoroughly characterizing lncRNA expressions in virus-infected primary cells, investigating their role in disease prognosis, and developing biologically relevant animal or organoid models to determine their suitability for specific therapeutic targeting. Many cellular and viral lncRNAs localize in the nucleus and epigenetically modulate viral transcription, latency, and host responses to infection. In this review, we provide an overview of the role of nuclear lncRNAs in the pathogenesis and outcomes of viral infections, such as the Influenza A virus, Sendai Virus, Respiratory Syncytial Virus, Hepatitis C virus, Human Immunodeficiency Virus, and Herpes Simplex Virus. We also address significant advances and barriers in characterizing lncRNA function and explore the potential of lncRNAs as therapeutic targets.

COVID-19: Mechanisms, risk factors, genetics, non-coding RNAs and neurologic impairments.

The novel coronavirus infection (COVID-19) causes a severe acute illness with the development of respiratory distress syndrome in some cases. COVID-19 is a global problem of mankind to this day. Among its most important aspects that require in-depth study are pathogenesis and molecular changes in severe forms of the disease. A lot of literature data is devoted to the pathogenetic mechanisms of COVID-19. Without dwelling in detail on some paths of pathogenesis discussed, we note that at present there are many factors of development and progression. Among them, this is the direct role of both viral non-coding RNAs (ncRNAs) and host ncRNAs. One such class of ncRNAs that has been extensively studied in COVID-19 is microRNAs (miRNAs) and long non-coding RNAs (lncRNAs). Moreover, Initially, it was believed that this COVID-19 was limited to damage to the respiratory system. It has now become clear that COVID-19 affects not only the liver and kidneys, but also the nervous system. In this review, we summarized the current knowledge of mechanisms, risk factors, genetics and neurologic impairments in COVID-19. In addition, we discuss and evaluate evidence demonstrating the involvement of miRNAs and lnRNAs in COVID-19 and use this information to propose hypotheses for future research directions.

Downregulation of MALAT1 is a hallmark of tissue and peripheral proliferative T cells in COVID-19.

T cells play key protective but also pathogenic roles in COVID-19. We studied the expression of long non-coding RNAs (lncRNAs) in COVID-19 T-cell transcriptomes by integrating previously published single-cell RNA sequencing datasets. The long intergenic non-coding RNA MALAT1 was the most highly transcribed lncRNA in T cells, with Th1 cells demonstrating the lowest and CD8+ resident memory cells the highest MALAT1 expression, amongst CD4+ and CD8+ T-cells populations, respectively. We then identified gene signatures that covaried with MALAT1 in single T cells. A significantly higher number of transcripts correlated negatively with MALAT1 than those that correlated. Enriched functional annotations of the MALAT1- anti-correlating gene signature included processes associated with T-cell activation such as cell division, oxidative phosphorylation, and response to cytokine. The MALAT1 anti-correlating gene signature shared by both CD4+ and CD8+ T-cells marked dividing T cells in both the lung and blood of COVID-19 patients. Focussing on the tissue, we used an independent patient cohort of post-mortem COVID-19 lung samples and demonstrated that MALAT1 suppression was indeed a marker of MKI67+ proliferating CD8+ T cells. Our results reveal MALAT1 suppression and its associated gene signature are a hallmark of human proliferating T cells.

Post-transcriptional control of haemostatic genes: mechanisms and emerging therapeutic concepts in thrombo-inflammatory disorders.

The haemostatic system is pivotal to maintaining vascular integrity. Multiple components involved in blood coagulation have central functions in inflammation and immunity. A derailed haemostasis is common in prevalent pathologies such as sepsis, cardiovascular disorders, and lately, COVID-19. Physiological mechanisms limit the deleterious consequences of a hyperactivated haemostatic system through adaptive changes in gene expression. While this is mainly regulated at the level of transcription, co- and posttranscriptional mechanisms are increasingly perceived as central hubs governing multiple facets of the haemostatic system. This layer of regulation modulates the biogenesis of haemostatic components, for example in situations of increased turnover and demand. However, they can also be 'hijacked' in disease processes, thereby perpetuating and even causally entertaining associated pathologies. This review summarizes examples and emerging concepts that illustrate the importance of posttranscriptional mechanisms in haemostatic control and crosstalk with the immune system. It also discusses how such regulatory principles can be used to usher in new therapeutic concepts to combat global medical threats such as sepsis or cardiovascular disorders.

Long non-coding RNAs in virus-related cancers.

Some viral infections lead to tumourigenesis explained by a variety of underlying molecular mechanisms. Long non-coding RNAs (lncRNAs) have the potential to be added to this list due to their diverse mechanisms in biological functions and disease processes via gene alternation, transcriptional regulation, protein modification, microRNA sponging and interaction with RNA/DNA/proteins. In this review, we summarise the dysregulation and mechanism of lncRNAs in virus-related cancers focussing on Hepatitis B virus, Epstein-Barr virus, Human Papillomavirus. We will also discuss the potential implications of lncRNAs in COVID-19.

Emerging role of microRNAs and long non-coding RNAs in COVID-19 with implications to therapeutics.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection which is commonly known as COVID-19 (COronaVIrus Disease 2019) has creeped into the human population taking tolls of life and causing tremendous economic crisis. It is indeed crucial to gain knowledge about their characteristics and interactions with human host cells. It has been shown that the majority of our genome consists of non-coding RNAs. Non-coding RNAs including micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs) display significant roles in regulating gene expression in almost all cancers and viral diseases. It is intriguing that miRNAs and lncRNAs remarkably regulate the function and expression of major immune components of SARS-CoV-2. MiRNAs act via RNA interference mechanism in which they bind to the complementary sequences of the viral RNA strand, inducing the formation of silencing complex that eventually degrades or inhibits the viral RNA and viral protein expression. LncRNAs have been extensively shown to regulate gene expression in cytokine storm and thus emerges as a critical target for COVID-19 treatment. These lncRNAs also act as competing endogenous RNAs (ceRNAs) by sponging miRNAs and thus affecting the expression of downstream targets during SARS-CoV-2 infection. In this review, we extensively discuss the role of miRNAs and lncRNAs, describe their mechanism of action and their different interacting human targets cells during SARS-CoV-2 infection. Finally, we discuss possible ways how an interference with their molecular function could be exploited for new therapies against SARS-CoV-2.

Role of different types of RNA molecules in the severity prediction of SARS-CoV-2 patients.

SARS-CoV-2 pandemic is the current threat of the world with enormous number of deceases. As most of the countries have constraints on resources, particularly for intensive care and oxygen, severity prediction with high accuracy is crucial. This prediction will help the medical society in the selection of patients with the need for these constrained resources. Literature shows that using clinical data in this study is the common trend and molecular data is rarely utilized in this prediction. As molecular data carry more disease related information, in this study, three different types of RNA molecules ( lncRNA, miRNA and mRNA) of SARS-COV-2 patients are used to predict the severity stage and treatment stage of those patients. Using seven different machine learning algorithms along with several feature selection techniques shows that in both phenotypes, feature importance selected features provides the best accuracy along with random forest classifier. Further to this, it shows that in the severity stage prediction miRNA and lncRNA give the best performance, and lncRNA data gives the best in treatment stage prediction. As most of the studies related to molecular data uses mRNA data, this is an interesting finding.

Buffy Coat Transcriptomic Analysis Reveals Alterations in Host Cell Protein Synthesis and Cell Cycle in Severe COVID-19 Patients.

Transcriptome studies have reported the dysregulation of cell cycle-related genes and the global inhibition of host mRNA translation in COVID-19 cases. However, the key genes and cellular mechanisms that are most affected by the severe outcome of this disease remain unclear. For this work, the RNA-seq approach was used to study the differential expression in buffy coat cells of two groups of people infected with SARS-CoV-2: (a) Mild, with mild symptoms; and (b) SARS (Severe Acute Respiratory Syndrome), who were admitted to the intensive care unit with the severe COVID-19 outcome. Transcriptomic analysis revealed 1009 up-regulated and 501 down-regulated genes in the SARS group, with 10% of both being composed of long non-coding RNA. Ribosome and cell cycle pathways were enriched among down-regulated genes. The most connected proteins among the differentially expressed genes involved transport dysregulation, proteasome degradation, interferon response, cytokinesis failure, and host translation inhibition. Furthermore, interactome analysis showed Fibrillarin to be one of the key genes affected by SARS-CoV-2. This protein interacts directly with the N protein and long non-coding RNAs affecting transcription, translation, and ribosomal processes. This work reveals a group of dysregulated processes, including translation and cell cycle, as key pathways altered in severe COVID-19 outcomes.

COVID-19-associated lncRNAs as predictors of survival in uterine corpus endometrial carcinoma: A prognostic model.

Background: Patients with uterine corpus endometrial carcinoma (UCEC) may be susceptible to the coronavirus disease-2019 (COVID-19). Long non-coding RNAs take on a critical significance in UCEC occurrence, development, and prognosis. Accordingly, this study aimed to develop a novel model related to COVID-19-related lncRNAs for optimizing the prognosis of endometrial carcinoma. Methods: The samples of endometrial carcinoma patients and the relevant clinical data were acquired in the Carcinoma Genome Atlas (TCGA) database. COVID-19-related lncRNAs were analyzed and obtained by coexpression. Univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses were performed to establish a COVID-19-related lncRNA risk model. Kaplan-Meier analysis, principal component analysis (PCA), and functional enrichment annotation were used to analyze the risk model. Finally, the potential immunotherapeutic signatures and drug sensitivity prediction targeting this model were also discussed. Results: The risk model comprising 10 COVID-19-associated lncRNAs was identified as a predictive ability for overall survival (OS) in UCEC patients. PCA analysis confirmed a reliable clustering ability of the risk model. By regrouping the patients with this model, different clinic-pathological characteristics, immunotherapeutic response, and chemotherapeutics sensitivity were also observed in different groups. Conclusion: This risk model was developed based on COVID-19-associated lncRNAs which would be conducive to the precise treatment of patients with UCEC.

Noncoding RNome as Enabling Biomarkers for Precision Health.

Noncoding RNAs (ncRNAs), in the form of structural, catalytic or regulatory RNAs, have emerged to be critical effectors of many biological processes. With the advent of new technologies, we have begun to appreciate how intracellular and circulatory ncRNAs elegantly choreograph the regulation of gene expression and protein function(s) in the cell. Armed with this knowledge, the clinical utility of ncRNAs as biomarkers has been recently tested in a wide range of human diseases. In this review, we examine how critical factors govern the success of interrogating ncRNA biomarker expression in liquid biopsies and tissues to enhance our current clinical management of human diseases, particularly in the context of cancer. We also discuss strategies to overcome key challenges that preclude ncRNAs from becoming standard-of-care clinical biomarkers, including sample pre-analytics standardization, data cross-validation with closer attention to discordant findings, as well as correlation with clinical outcomes. Although harnessing multi-modal information from disease-associated noncoding RNome (ncRNome) in biofluids or in tissues using artificial intelligence or machine learning is at the nascent stage, it will undoubtedly fuel the community adoption of precision population health.

Assessing the suitability of long non-coding RNAs as therapeutic targets and biomarkers in SARS-CoV-2 infection.

Long non-coding RNAs (lncRNAs) are RNA transcripts that are over 200 nucleotides and rarely encode proteins or peptides. They regulate gene expression and protein activities and are heavily involved in many cellular processes such as cytokine secretion in respond to viral infection. In severe COVID-19 cases, hyperactivation of the immune system may cause an abnormally sharp increase in pro-inflammatory cytokines, known as cytokine release syndrome (CRS), which leads to severe tissue damage or even organ failure, raising COVID-19 mortality rate. In this review, we assessed the correlation between lncRNAs expression and cytokine release syndrome by comparing lncRNA profiles between COVID-19 patients and health controls, as well as between severe and non-severe cases. We also discussed the role of lncRNAs in CRS contributors and showed that the lncRNA profiles display consistency with patients' clinic symptoms, thus suggesting the potential of lncRNAs as drug targets or biomarkers in COVID-19 treatment.

Non-coding RNA in idiopathic interstitial pneumonia and Covid-19 pulmonary fibrosis.

Pulmonary fibrosis is the key feature of majority of idiopathic interstitial pneumonias (IIPs) as well as many patients with post-COVID-19. The pathogenesis of pulmonary fibrosis is a complex molecular process that involves myriad of cells, proteins, genes, and regulatory elements. The non-coding RNA mainly miRNA, circRNA, and lncRNA are among the key regulators of many protein coding genes and pathways that are involved in pulmonary fibrosis. Identification and molecular mechanisms, by which these non-coding RNA molecules work, are crucial to understand the molecular basis of the disease. Additionally, elucidation of molecular mechanism could also help in deciphering a potential diagnostic/prognostic marker as well as therapeutic targets for IIPs and post-COVID-19 pulmonary fibrosis. In this review, we have provided the latest findings and discussed the role of these regulatory elements in the pathogenesis of pulmonary fibrosis associated with Idiopathic Interstitial Pneumonia and Covid-19.

Long noncoding RNA CHROMR regulates antiviral immunity in humans.

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of gene expression, yet their contribution to immune regulation in humans remains poorly understood. Here, we report that the primate-specific lncRNA CHROMR is induced by influenza A virus and SARS-CoV-2 infection and coordinates the expression of interferon-stimulated genes (ISGs) that execute antiviral responses. CHROMR depletion in human macrophages reduces histone acetylation at regulatory regions of ISG loci and attenuates ISG expression in response to microbial stimuli. Mechanistically, we show that CHROMR sequesters the interferon regulatory factor (IRF)-2-dependent transcriptional corepressor IRF2BP2, thereby licensing IRF-dependent signaling and transcription of the ISG network. Consequently, CHROMR expression is essential to restrict viral infection of macrophages. Our findings identify CHROMR as a key arbitrator of antiviral innate immune signaling in humans.

Differential expression analysis of mRNAs, lncRNAs, and miRNAs expression profiles and construction of ceRNA networks in PEDV infection.

BACKGROUND: Porcine Epidemic Diarrhea Virus (PEDV) is a coronavirus that seriously affects the swine industry. MicroRNAs and long noncoding RNAs are two relevant non-coding RNAs (ncRNAs) class and play crucial roles in a variety of physiological processes. Increased evidence indicates a complex interaction between mRNA and ncRNA. However, our understanding of the function of ncRNA involved in host-PEDV interaction is limited. RESULTS: A total of 1,197 mRNA transcripts, 539 lncRNA transcripts, and 208 miRNA transcripts were differentially regulated at 24 h and 48 h post-infection. Gene ontology (GO) and KEGG pathway enrichment analysis showed that DE mRNAs and DE lncRNAs were mainly involved in biosynthesis, innate immunity, and lipid metabolism. Moreover, we constructed a miRNA-mRNA-pathway network using bioinformatics, including 12 DE mRNAs, 120 DE miRNAs, and 11 pathways. Finally, the target genes of DE miRNAs were screened by bioinformatics, and we constructed immune-related lncRNA-miRNA-mRNA ceRNA networks. Then, the selected DE genes were validated by qRT-PCR, which were consistent with the results from RNA-Seq data. CONCLUSIONS: This study provides the comprehensive analysis of the expression profiles of mRNAs, lncRNAs, and miRNAs during PEDV infection. We characterize the ceRNA networks which can provide new insights into the pathogenesis of PEDV.

Identification and integrated analysis of lncRNAs and miRNAs in IPEC-J2 cells provide novel insight into the regulation of the innate immune response by PDCoV infection.

BACKGROUND: Noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), are pivotal regulators involved in the pathogenic mechanism of multiple coronaviruses. Porcine deltacoronavirus (PDCoV) has evolved multiple strategies to escape the innate immune response of host cells, but whether ncRNAs are involved in this process during PDCoV infection is still unknown. RESULTS: In this study, the expression profiles of miRNAs, lncRNAs and mRNAs in IPEC-J2 cells infected with PDCoV at 0, 12 and 24 hours postinfection (hpi) were identified through small RNA and RNA sequencing. The differentially expressed miRNAs (DEmiRNAs), lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were screened from the comparison group of IPEC-J2 cells at 0 and 12 hpi as well as the comparison group of IPEC-J2 cells at 12 and 24 hpi. The target genes of these DEncRNAs were predicted. The bioinformatics analysis of the target genes revealed multiple significantly enriched functions and pathways. Among them, the genes that were associated with innate immunity were specifically screened. The expression of innate immunity-related ncRNAs and mRNAs was validated by RT-qPCR. Competing endogenous RNA (ceRNA) regulatory networks among innate immunity-related ncRNAs and their target mRNAs were established. Moreover, we found that the replication of PDCoV was significantly inhibited by two innate immunity-related miRNAs, ssc-miR-30c-3p and ssc-miR-374b-3p, in IPEC-J2 cells. CONCLUSIONS: This study provides a data platform to conduct studies of the pathogenic mechanism of PDCoV from a new perspective and will be helpful for further elucidation of the functional role of ncRNAs involved in PDCoV escaping the innate immune response.

Non-coding RNAs: the silent regulators of health and diseases.

Non-coding RNAs (ncRNAs) like miRNAs, siRNA, lncRNAs, circRNAs, piRNAs, snoRNAs, snRNAs etc. form a collective group of RNAs that is instrumental to the various functions of the genome. With the advent of cutting-edge molecular biology tools and techniques, scientists have unearthed several mechanisms through which these ncRNAs act. Although our understanding may still be limited, yet scientists have been able to establish ncRNAs as major regulators of genetic inter-plays that dictate various pathophysiological conditions. This special issue of Molecular Biology Reports features a collection of research and review articles on ncRNAs and their involvement in different pathophysiological conditions that include different types of cancers. It is expected that this special issue will motivate researchers in the field to delve deeper into the world of ncRNAs and attempt to develop new diagnostic and therapeutic interventions for challenging clinical conditions.

Comparative Analysis of Long Non-Coding RNA Expression and Immune Response in Mild and Severe COVID-19.

Background: Coronavirus disease 2019 (COVID-19) is a worldwide emergency, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Long non-coding RNAs (lncRNAs) do not encode proteins but could participate in immune response. Methods: In our study, 39 COVID-19 patients were enrolled. The microarray of peripheral blood mononuclear cells from healthy and COVID-19 patients was applied to identify the expression profiles of lncRNAs and mRNAs. Identified differentially expressed (DE) lncRNAs were validated by qRT-PCR. Then, the lncRNA-mRNA network was constructed and visualized using Cytoscape (3.6.1) based on the Pearson correlation coefficient. The enrichment of DE mRNAs was analyzed using Metascape. The difference in frequencies of immune cells and cytokines was detected using CIBERSORT and ImmPort based on DE mRNAs. Results: All patients with COVID-19 displayed lymphopenia, especially in T cells, and hyper-inflammatory responses, including IL-6 and TNF-α. Four immune-related lncRNAs in COVID-19 were found and further validated, including AC136475.9, CATG00000032642.1, G004246, and XLOC_013290. Functional analysis enriched in downregulation of the T-cell receptor and the antigen processing and presentation as well as increased apoptotic proteins, which could lead to T-cell cytopenia. In addition, they participated in monocyte remodeling, which contributed to releasing cytokines and chemokines and then recruiting more monocytes and aggravating the clinical severity of COVID-19 patients. Conclusion: Taken together, four lncRNAs were in part of immune response in COVID-19, which was involved in the T-cell cytopenia by downregulating the antigen processing and presentation, the T-cell receptor, and an increased proportion of monocytes, with a distinct change in cytokines and chemokines.

Non-Coding RNAs in Rheumatoid Arthritis: Implications for Biomarker Discovery.

Recent advances in gene expression analysis techniques and increased access to technologies such as microarrays, qPCR arrays, and next-generation sequencing, in the last decade, have led to increased awareness of the complexity of the inflammatory responses that lead to pathology. This finding is also the case for rheumatic diseases, importantly and specifically, rheumatoid arthritis (RA). The coincidence in major genetic and epigenetic regulatory events leading to RA's inflammatory state is now well-recognized. Research groups have characterized the gene expression profile of early RA patients and identified a group of miRNAs that is particularly abundant in the early stages of the disease and miRNAs associated with treatment responses. In this perspective, we summarize the current state of RNA-based biomarker discovery and the context of technology adoption/implementation due to the COVID-19 pandemic. These advances have great potential for clinical application and could provide preclinical disease detection, follow-up, treatment targets, and biomarkers for treatment response monitoring.