Knockdown of eIF4E suppresses cell proliferation, invasion and enhances cisplatin cytotoxicity in human ovarian cancer cells

Eukaryotic Initiation Factor 4E (eIF4E) as a Target of Anti-Psoriatic Treatment

Eukaryotic initiation factor 4E (eIF4E) has been known to play a critical role in the regulation of gene expression and essential cellular processes, such as proliferation, apoptosis and differentiation. In this study, we explored its role in the pathophysiology of psoriasis. The inhibition of eIF4E by small interfering RNA or briciclib, an eIF4E small molecule inhibitor, downregulated the expression of eIF4E itself and its two complex partners eIF4A and G, as well as other eIFs (eg, eIF1A, eIF2α, eIF3A, eIF3B, eIF5, and eIF6). This inhibition also abolished psoriatic inflammation in both the imiquimod and TGFß mouse model, as well as in a human 3 dimensional-psoriasis tissue model. Downregulation of eIF4E and the other eIFs by application of briciclib (particularly when given topically) was linked to the normalization of cellular proliferation, epidermal hyperplasia, levels of proinflammatory cytokines (eg, TNFα, IL-1b, IL-17, and IL-22), and keratinocyte differentiation markers (eg, KRT16 and FLG). These results demonstrate translational imbalance and underline the crucial role played by eIF4E and other eIFs in the pathophysiology of psoriasis. This work opens up avenues for the development of novel topical antipsoriatic treatment strategies by targeting eIF4E.

Translational regulation of cell invasion through extracellular matrix-an emerging role for ribosomes

Many developmental and physiological processes require cells to invade and migrate through extracellular matrix barriers. This specialized cellular behavior is also misregulated in many diseases, such as immune disorders and cancer. Cell invasive activity is driven by pro-invasive transcriptional networks that activate the expression of genes encoding numerous different proteins that expand and regulate the cytoskeleton, endomembrane system, cell adhesion, signaling pathways, and metabolic networks. While detailed mechanistic studies have uncovered crucial insights into pro-invasive transcriptional networks and the distinct cell biological attributes of invasive cells, less is known about how invasive cells modulate mRNA translation to meet the robust, dynamic, and unique protein production needs of cell invasion. In this review we outline known modes of translation regulation promoting cell invasion and focus on recent studies revealing elegant mechanisms that expand ribosome biogenesis within invasive cells to meet the increased protein production requirements to invade and migrate through extracellular matrix barriers.

Regulation of Eukaryotic Translation Initiation Factor 4E as a Potential Anticancer Strategy

Eukaryotic translation initiation factors (eIFs) are highly expressed in cancer cells, especially eIF4E, the central regulatory node driving cancer cell growth and a potential target for anticancer drugs. eIF4E-targeting strategies primarily focus on inhibiting eIF4E synthesis, interfering with eIF4E/eIF4G interactions, and targeting eIF4E phosphorylation and peptide inhibitors. Although some small-molecule inhibitors are in clinical trials, no eIF4E inhibitors are available for clinical use. We provide an overview of the regulatory mechanisms of eIF4E and summarize the progress in developing and discovering eIF4E inhibitor strategies. We propose that interference with eIF4E/eIF4G interactions will provide a new perspective for the design of eIF4E inhibitors and may be a preferred strategy.

The eIF4EBP-eIF4E axis regulates CD4+ T cell differentiation through modulation of T cell activation and metabolism

CD4⁺ T cells are critical for adaptive immunity, differentiating into distinct effector and regulatory subsets. Although the transcriptional programs underlying their differentiation are known, recent research has highlighted the importance of mRNA translation in determining protein abundance. We previously conducted genome-wide analysis of translation in CD4⁺ T cells revealing distinct translational signatures distinguishing these subsets, identifying eIF4E as a central differentially translated transcript. As eIF4E is vital for eukaryotic translation, we examined how altered eIF4E activity affected T cell function using mice lacking eIF4E-binding proteins (BP^-/-). BP^-/- effector T cells showed elevated Th1 responses ex vivo and upon viral challenge with enhanced Th1 differentiation observed in vitro. This was accompanied by increased TCR activation and elevated glycolytic activity. This study highlights how regulating T cell-intrinsic eIF4E activity can influence T cell activation and differentiation, suggesting the eIF4EBP-eIF4E axis as a potential therapeutic target for controlling aberrant T cell responses.

Inferring cancer common and specific gene networks via multi-layer joint graphical model

Cancer is a complex disease caused primarily by genetic variants. Reconstructing gene networks within tumors is essential for understanding the functional regulatory mechanisms of carcinogenesis. Advances in high-throughput sequencing technologies have provided tremendous opportunities for inferring gene networks via computational approaches. However, due to the heterogeneity of the same cancer type and the similarities between different cancer types, it remains a challenge to systematically investigate the commonalities and specificities between gene networks of different cancer types, which is a crucial step towards precision cancer diagnosis and treatment. In this study, we propose a new sparse regularized multi-layer decomposition graphical model to jointly estimate the gene networks of multiple cancer types. Our model can handle various types of gene expression data and decomposes each cancer-type-specific network into three components, i.e., globally shared, partially shared and cancer-type-unique components. By identifying the globally and partially shared gene network components, our model can explore the heterogeneous similarities between different cancer types, and our identified cancer-type-unique components can help to reveal the regulatory mechanisms unique to each cancer type. Extensive experiments on synthetic data illustrate the effectiveness of our model in joint estimation of multiple gene networks. We also apply our model to two real data sets to infer the gene networks of multiple cancer subtypes or cell lines. By analyzing our estimated globally shared, partially shared, and cancer-type-unique components, we identified a number of important genes associated with common and specific regulatory mechanisms across different cancer types.

Translational Regulation by eIFs and RNA Modifications in Cancer

Translation is a fundamental process in all living organisms that involves the decoding of genetic information in mRNA by ribosomes and translation factors. The dysregulation of mRNA translation is a common feature of tumorigenesis. Protein expression reflects the total outcome of multiple regulatory mechanisms that change the metabolism of mRNA pathways from synthesis to degradation. Accumulated evidence has clarified the role of an increasing amount of mRNA modifications at each phase of the pathway, resulting in translational output. Translation machinery is directly affected by mRNA modifications, influencing translation initiation, elongation, and termination or altering mRNA abundance and subcellular localization. In this review, we focus on the translation initiation factors associated with cancer as well as several important RNA modifications, for which we describe their association with cancer.

Lnc-HZ01 with m6A RNA methylation inhibits human trophoblast cell proliferation and induces miscarriage by up-regulating BPDE-activated lnc-HZ01/MXD1 positive feedback loop

Environmental BaP (benzo(a)pyrene) and its metabolite BPDE (benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide) inhibit proliferation of human villous trophoblast cells, which might further induce recurrent miscarriage (RM). However, the underlying mechanisms remain largely unknown. In this work, we identified a novel lncRNA HZ01 (lnc-HZ01) that is up-regulated in both RM tissues and BPDE-exposed trophoblast cells. Lnc-HZ01 inhibits trophoblast cell proliferation and induces miscarriage. Mechanistically, lnc-HZ01 promotes MXD1 mRNA transcription by up-regulating its transcription factor c-JUN and also enhances MXD1 protein stability by up-regulating its deubiquitin enzyme USP36. Reversely, MXD1 up-regulates lnc-HZ01 level by enhancing its RNA stability due to the increased level of m6A RNA methylation on lnc-HZ01, the first example that m6A modification regulates trophoblast cell functions. Thus, lnc-HZ01 and MXD1 comprise a positive self-feedback loop, which is up-regulated in both RM tissues and BPDE-exposed trophoblast cells. Once this loop is activated by BaP or BPDE exposure, both pathways in this loop would be up-regulated, promote EIF4E transcription, inhibit trophoblast cell proliferation, and further induce miscarriage. This work provides new clinical and scientific understanding in unexplained miscarriage.

Targeting mTOR and eIF4E: a feasible scenario in ovarian cancer therapy

Ovarian carcinoma is one of the most common causes for cancer death in women; lack of early diagnosis and acquired resistance to platinum-based chemotherapy account for its poor prognosis and high mortality rate. As with other cancer types, ovarian cancer is characterized by dysregulated signaling pathways and protein synthesis, which together contribute to rapid cellular growth and invasiveness. The mechanistic/mammalian target of rapamycin (mTOR) pathway represents the core of different signaling pathways regulating a number of essential steps in the cell, among which protein synthesis and the eukaryotic initiation factor 4E (eIF4E), the mRNA cap binding protein, is one of its downstream effectors. eIF4E is a limiting factor in translation initiation and its overexpression is a hallmark in many cancers. Because its action is regulated by a number of factors that compete for the same binding site, eIF4E is an ideal target for developing novel antineoplastic drugs. Several inhibitors targeting the mTOR signaling pathway have been designed thus far, however most of these molecules show poor stability and high toxicity in vivo. This minireview explores the possibility of targeting mTOR and eIF4E proteins, thus impacting on translation initiation in ovarian cancer, describing the most promising experimental strategies and specific inhibitors that have been shown to have an effect on other kinds of cancers.

eIF4E Overexpression Is Associated with Poor Prognoses of Ovarian Cancer

Aim

Ovarian cancer is a common malignant tumor of the gynecological oncology worldwide, with a high incidence and mortality rate and poor prognosis. Searching for new diagnostic molecular biomarkers for ovarian cancer is extremely significant.

Methods

Here, we analyzed the expression rates of eIF4E and cyclin D1 proteins in 123 cases of cancer tissue samples and 38 cases of paracancerous tissue samples and studied the connection between the expression rates of eIF4E and cyclin D1 proteins by immunohistochemistry and statistically correlated with clinicopathological features in ovarian cancer.

Results

The results showed that the expression rates of eIF4E and cyclin D1 proteins in ovarian cancer tissues were significantly higher than those in noncancerous epithelial ovarian tissues (P = 0.001 and P = 0.032, respectively). Additionally, the results revealed that a higher expression rate of eIF4E (P = 0.008) was found in the advanced stage (stage III/IV), and also patients with cervical lymph node metastasis displayed higher expression of eIF4E (P < 0.001) and cyclin D1 (P = 0.033) than those without lymph node metastasis. Spearman's rank correlation test showed that there was a significant positive correlation between the eIF4E and cyclin D1 proteins in ovarian cancer. The Kaplan-Meier method showed that patients with lower expression of eIF4E had marginally better survival than those with high expression of eIF4E (P = 0.012). Multivariate Cox regression analysis further identified that positive expression of eIF4E was an independent prognostic factor.

Conclusion

In ovarian cancer, eIF4E might be a valuable biomarker to predict poor prognoses and a potential therapeutic target to develop valid treatment strategies.

Integrated bioinformatics analysis for the screening of hub genes and therapeutic drugs in ovarian cancer

Background

Ovarian cancer (OC) ranks fifth as a cause of gynecological cancer-associated death globally. Until now, the molecular mechanisms underlying the tumorigenesis and prognosis of OC have not been fully understood. This study aims to identify hub genes and therapeutic drugs involved in OC.

Methods

Four gene expression profiles (GSE54388, GSE69428, GSE36668, and GSE40595) were downloaded from the Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) in OC tissues and normal tissues with an adjusted P-value < 0.05 and a |log fold change (FC)| > 1.0 were first identified by GEO2R and FunRich software. Next, Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) analyses were performed for functional enrichment analysis of these DEGs. Then, the hub genes were identified by the cytoHubba plugin and the other bioinformatics approaches including protein-protein interaction (PPI) network analysis, module analysis, survival analysis, and miRNA-hub gene network construction was also performed. Finally, the GEPIA2 and DGIdb databases were utilized to verify the expression levels of hub genes and to select the candidate drugs for OC, respectively.

Results

A total of 171 DEGs were identified, including 114 upregulated and 57 downregulated DEGs. The results of the GO analysis indicated that the upregulated DEGs were mainly involved in cell division, nucleus, and protein binding, whereas the biological functions showing enrichment in the downregulated DEGs were mainly negative regulation of transcription from RNA polymerase II promoter, protein complex and apicolateral plasma membrane, and glycosaminoglycan binding. As for the KEGG-pathway, the upregulated DEGs were mainly associated with metabolic pathways, biosynthesis of antibiotics, biosynthesis of amino acids, cell cycle, and HTLV-I infection. Additionally, 10 hub genes (KIF4A, CDC20, CCNB2, TOP2A, RRM2, TYMS, KIF11, BIRC5, BUB1B, and FOXM1) were identified and survival analysis of these hub genes showed that OC patients with the high-expression of CCNB2, TYMS, KIF11, KIF4A, BIRC5, BUB1B, FOXM1, and CDC20 were statistically more likely to have poorer progression free survival. Meanwhile, the expression levels of the hub genes based on GEPIA2 were in accordance with those based on GEO. Finally, DGIdb database was used to identify 62 small molecules as the potentially targeted drugs for OC treatment.

Conclusions

In summary, the data may produce new insights regarding OC pathogenesis and treatment. Hub genes and candidate drugs may improve individualized diagnosis and therapy for OC in future.

The Prognostic Significance of Eukaryotic Translation Initiation Factors (eIFs) in Endometrial Cancer

Whilst the role of eukaryotic translation initiation factors (eIFs) has already been investigated in several human cancers, their role in endometrial cancer (EC) is relatively unknown. In the present retrospective study, 279 patients with EC (1180 samples) were included (mean age: 63.0 years, mean follow-up: 6.1 years). Samples were analysed for expression of 7 eIFs subunits (eIF2α, eIF3c, eIF3h, eIF4e, eIF4g, eIF5, eIF6) through immunohistochemistry and western blotting. Fifteen samples of healthy endometrium served as controls. Density and intensity were assessed and mean combined scores (CS) calculated for each patient. Upon immunohistochemistry, median eIF5 CS were significantly higher in EC as compared with non-neoplastic tissue (NNT, p < 0.001), whilst median eIF6 CS were significantly lower in EC (p < 0.001). Moreover, eIF5 (p = 0.002), eIF6 (p = 0.032) and eIF4g CS (p = 0.014) were significantly different when comparing NNT with EC grading types. Median eIF4g CS was higher in type II EC (p = 0.034). Upon western blot analysis, eIF4g (p < 0.001), peIF2α (p < 0.001) and eIF3h (p < 0.05) were significantly overexpressed in EC, while expression of eIF3c was significantly reduced in EC as compared with NNT (p < 0.001). The remaining eIFs were non-significant. Besides tumour stage (p < 0.001) and patient's age (p < 0.001), high eIF4g CS-levels were independently associated with poor prognosis (HR: 1.604, 95%CI: 1.037-2.483, p = 0.034). The other eIFs had no prognostic significance. Notably, the independent prognostic significance of eIF4g was lost when adding tumour type. Considering the difficulties in differentiating EC type I and II, eIF4g may serve as a novel prognostic marker indicating patient outcome.

Upregulation of eukaryotic translation initiation factor 4E associates with a poor prognosis in gallbladder cancer and promotes cell proliferation in vitro and in vivo

Eukaryotic translation initiation factor 4 (eIF4E) has been demonstrated to promote tumorigenesis in different types of cancer; however, whether eIF4E is involved in the development of GBC is unclear. The present study aimed to explore the biological function of eIF4E in gallbladder cancer (GBC) and identified that the expression level of eIF4E was significantly increased in GBC tissues compared with that in normal gallbladder tissues. The overall survival (OS) was also shorter in the group of patients with GBC with increased eIF4E expression. Increased eIF4E was correlated with advanced stage and higher histologic grade. Knockdown of eIF4E significantly inhibited cell proliferation, colony formation and cell cycle-associated protein expression levels in 2 GBC cell lines. The weight of the tumors in the eIF4E knockdown group was remarkably decreased compared with the control group. It also was revealed that knockdown of eIF4E is associated with upregulating cyclin-dependent kinase inhibitor 1B and down-regulating the expression levels of cyclin E1 and cyclin D1 in vitro and in vivo. These data demonstrated that eIF4E is a novel prognostic marker in GBC and may serve a critical role in the regulation of cell proliferation.

Long noncoding RNA OCC-1 suppresses cell growth through destabilizing HuR protein in colorectal cancer

Overexpressed in colon carcinoma-1 (OCC-1) is one of the earliest annotated long noncoding RNAs (lncRNAs) in colorectal cancer (CRC); however, its function remains largely unknown. Here, we revealed that OCC-1 plays a tumor suppressive role in CRC. OCC-1 knockdown by RNA interference promotes cell growth both in vitro and in vivo, which is largely due to its ability to inhibit G0 to G1 and G1 to S phase cell cycle transitions. In addition, overexpression of OCC-1 can suppress cell growth in OCC-1 knockdown cells. OCC-1 exerts its function by binding to and destabilizing HuR (ELAVL1), a cancer-associated RNA binding protein (RBP) which can bind to and stabilize thousands of mRNAs. OCC-1 enhances the binding of ubiquitin E3 ligase β-TrCP1 to HuR and renders HuR susceptible to ubiquitination and degradation, thereby reducing the levels of HuR and its target mRNAs, including the mRNAs directly associated with cancer cell growth. These findings reveal that lncRNA OCC-1 can regulate the levels of a large number of mRNAs at post-transcriptional level through modulating RBP HuR stability.

Eukaryotic initiation factor 4E (eIF4E): A recap of the cap-binding protein

Eukaryotic initiation factor 4E (eIF4E), a fundamental effector and rate limiting element of protein synthesis, binds the 7-methylguanosine cap at the 5' end of eukaryotic messenger RNA (mRNA) specifically as a constituent of eIF4F translation initiation complex thus facilitating the recruitment of mRNA to the ribosomes. This review focusses on the engagement of signals contributing to growth factor originated maxim and their role in the activation of eIF4E to achieve a collective influence on cellular growth, with a key focus on conjuring vital processes like protein synthesis. The review invites considerable interest in elevating the appeal of eIF4E beyond its role in regulating translation viz a viz cancer genesis, attributed to its phosphorylation state that improves the prospect for the growth of the cancerous cell. This review highlights the latest studies that have envisioned to target these pathways and ultimately the translational machinery for therapeutic intervention. The review also brings forward the prospect of eIF4E to act as a converging juncture for signaling pathways like mTOR/PI3K and Mnk/MAPK to promote tumorigenesis.

Targeting eIF4E signaling with ribavirin as a sensitizing strategy for ovarian cancer

The essential roles of eukaryotic translation initiation factor 4E (eIF4E) have been shown in various cancers, including ovarian cancer. In this work, we demonstrate that eIF4E inhibition in ovarian cancer can be achieved by ribavirin, a FDA-approved antiviral drug. We show that ribavirin at clinically relevant doses significantly inhibits growth and survival in multiple ovarian cancer cell lines, regardless of morphological and molecular subtypes. Mechanistically, ribavirin suppresses Akt/mTOR and eIF4E/p70S6K signaling pathways in ovarian cancer cells. We confirm that eIF4E is the critical molecular target of ribavirin, and furthermore that this is dependent on phosphorylation at S209. Notably, using both in vitro cell culture system and in vivo xenograft mouse model, we show that the combination of ribavirin with cisplatin (standard of care for patients with ovarian cancer) results in significantly greater efficacy than cisplatin alone in ovarian cancer. Interestingly, the sensitivity to ribavirin varies among a panel of ovarian cancer cell lines, mostly likely due to their differential expression level of eIF4E and dependency to eIF4E inhibition. The differential expression level is further observed in ovarian cancer tissues, with the higher level of eIF4E in the majority of ovarian cancer tissues compared to normal ovary tissues. Our work suggests that eIF4E expression varies among ovarian cancer. Additionally, ribavirin is a useful addition to ovarian cancer treatment, particularly to those with high dependency on eIF4E.

Downregulation of microRNA-15a suppresses the proliferation and invasion of renal cell carcinoma via direct targeting of eIF4E

The downregulation of microRNA-15a has been reported in several human tumors. However, its expression and functional importance in renal cell carcinoma (RCC) remain unknown. The aim of the present study was to investigate its expression, biological functions and underlying mechanisms in RCC tumorigenesis. The expression levels of miR-15a were examined by qRT-PCR in 40 RCC specimens and adjacent‑paired normal tissues. Cell Counting Kit-8 (CCK-8), colony formation, flow cytometry and Transwell assays were used to explore the potential influence of miR-15a transfection on RCC cell proliferation, the cell cycle, cell apoptosis, and cell invasion. Luciferase reporter assays were performed to confirm the potential target of miR-15a, in combination with qRT-PCR, western blotting and immunohistochemical assays. We found that miR-15a was significantly downregulated in most RCC specimens compared with adjacent normal tissues (P<0.01). Overexpression of miR-15a inhibited cellular growth, suppressed invasion and arrested cells at the G1/G0 phase, and induced cell apoptosis in RCC cells. Luciferase assays revealed that miR-15a directly targeted the binding site of the 3'-untranslated region (3'-UTR) of eIF4E, and inhibited its expression at both mRNA and protein levels. eIF4E expression was negatively associated with miR-15a expression in RCC tissues. eIF4E overexpression treatment partially abrogated the inhibitory effect of miR-15a on cell proliferation and invasion, as well as inactivated P13K/AKT/mTOR signaling in RCC cells. In conclusion, the present study indicated that miR-15a downregulation was associated with cell proliferation and invasion by directly targeting eIF4E during RCC progression. Thus, it may serve as a potential tumor suppressor and therapeutic target for the treatment of RCC.

Inhibiting ERK/Mnk/eIF4E broadly sensitizes ovarian cancer response to chemotherapy

PURPOSE

To investigate whether ERK/MNK/eIF4E contributes chemoresistance in ovarian cancer.

METHODS

The phosphorylated levels of Erk, Mnk, and eIF4E were systematically analyzed in ovarian cancer patients before and after chemotherapy, and ovarian cancer cells exposed to short- and long-term chemo-agent treatment. The roles of Erk/Mnk/eIF4E were investigated using pharmacological and genetic approaches.

RESULTS

Increased phosphorylation levels of ERK, Mnk1, and eIF4E were observed in ovarian cancer cell exposed to chemotherapeutic agents, and paclitaxel-resistant SK-OV-3-r cells, and is a common response of ovarian cancer patients undergoing chemotherapy. MEK inhibitor U0126 inhibits basal and chemodrug-induced phosphorylation of ERK as well as Mnk1 and eIF4E, suggesting that Mnk1/eIF4E are the downstream signaling of ERK pathway and chemotherapy agents activate ERK/MNK/eIF4E in a MEK-dependent manner. eIF4E overexpression promotes ovarian cancer cell growth without affecting migration. In addition, ovarian cancer cells with eIF4E overexpression are more resistant to chemotherapeutic agents in aspect of growth inhibition and apoptosis induction compared to control cells. In contrast, eIF4E depletion augments chemotherapeutic agents' effect in ovarian cancer cells. These demonstrate that eIF4E play roles in growth and chemoresistance in ovarian cancer. MEK inhibitor U0126 also significantly enhances chemotherapeutic agents' inhibitory effects.

CONCLUSIONS

Our work shows that ERK/Mnk/eIF4E activation is critically involved in ovarian cancer chemoresistance and inhibiting ERK/Mnk/eIF4E broadly sensitizes ovarian cancer response to chemotherapy.

Identification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis

Ovarian cancer is the first leading cause of mortality in gynecological malignancies. To identify key genes and microRNAs in ovarian cancer, mRNA microarray dataset GSE36668, GSE18520, GSE14407 and microRNA dataset GSE47841 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and microRNAs (DEMs) were obtained using GEO2R. Functional and pathway enrichment analysis were performed for DEGs using DAVID database. Protein-protein interaction (PPI) network was established by STRING and visualized by Cytoscape. Following, overall survival (OS) analysis of hub genes was performed by the Kaplan-Meier plotter online tool. Module analysis of the PPI network was performed using MCODE. Moreover, miRecords was applied to predict the targets of the DEMs. A total of 345 DEGs were obtained, which were mainly enriched in the terms related to cell cycle, mitosis, and ovulation cycle process. A PPI network was constructed, consisting of 141 nodes and 296 edges. Sixteen genes had high degrees in the network. High expression of four genes of the 16 genes was associated with worse OS of patients with ovarian cancer, including CCNB1, CENPF, KIF11, and ZWINT. A significant module was detected from the PPI network. The enriched functions and pathways included cell cycle, nuclear division, and oocyte meiosis. Additionally, a total of 36 DEMs were identified. The expression of KIF11 was negatively correlated with that of has-miR-424 and has-miR-381, and it was also the potential target of two microRNAs. In conclusion, these results identified key genes, which could provide potential targets for ovarian cancer diagnosis and treatment.