Decreased RORC expression and downstream signaling in HTLV-1-associated adult T-cell lymphoma/leukemia uncovers an antiproliferative IL17 link: A potential target for immunotherapy?

ZEB1 shapes AML immunological niches, suppressing CD8 T cell activity while fostering Th17 cell expansion

Acute myeloid leukemia (AML) progression is influenced by immune suppression induced by leukemia cells. ZEB1, a critical transcription factor in epithelial-to-mesenchymal transition, demonstrates immune regulatory functions in AML. Silencing ZEB1 in leukemic cells reduces engraftment and extramedullary disease in immune-competent mice, activating CD8 T lymphocytes and limiting Th17 cell expansion. ZEB1 in AML cells directly promotes Th17 cell development that, in turn, creates a self-sustaining loop and a pro-invasive phenotype, favoring transforming growth factor β (TGF-β), interleukin-23 (IL-23), and SOCS2 gene transcription. In bone marrow biopsies from AML patients, immunohistochemistry shows a direct correlation between ZEB1 and Th17. Also, the analysis of ZEB1 expression in larger datasets identifies two distinct AML groups, ZEB1high and ZEB1low, each with specific immunological and molecular traits. ZEB1high patients exhibit increased IL-17, SOCS2, and TGF-β pathways and a negative association with overall survival. This unveils ZEB1's dual role in AML, entwining pro-tumoral and immune regulatory capacities in AML blasts.

High seroprevalence of Leishmania infantum is linked to immune activation in people with HIV: a two-stage cross-sectional study in Bahia, Brazil

Visceral leishmaniasis is an opportunistic disease in HIV-1 infected individuals, unrecognized as a determining factor for AIDS diagnosis. The growing geographical overlap of HIV-1 and Leishmania infections is an emerging challenge worldwide, as co-infection increases morbidity and mortality for both infections. Here, we determined the prevalence of people living with HIV (PWH) with a previous or ongoing infection by Leishmania infantum and investigated the virological and immunological factors associated with co-infection. We adopted a two-stage cross-sectional cohort (CSC) design (CSC-I, n = 5,346 and CSC-II, n = 317) of treatment-naïve HIV-1-infected individuals in Bahia, Brazil. In CSC-I, samples collected between 1998 and 2013 were used for serological screening for leishmaniasis by an in-house Enzyme-Linked Immunosorbent Assay (ELISA) with SLA (Soluble Leishmania infantum Antigen), resulting in a prevalence of previous or ongoing infection of 16.27%. Next, 317 PWH were prospectively recruited from July 2014 to December 2015 with the collection of sociodemographic and clinical data. Serological validation by two different immunoassays confirmed a prevalence of 15.46 and 8.20% by anti-SLA, and anti-HSP70 serology, respectively, whereas 4.73% were double-positive (DP). Stratification of these 317 individuals in DP and double-negative (DN) revealed a significant reduction of CD4+ counts and CD4+/CD8+ ratios and a tendency of increased viral load in the DP group, as compared to DN. No statistical differences in HIV-1 subtype distribution were observed between the two groups. However, we found a significant increase of CXCL10 (p = 0.0076) and a tendency of increased CXCL9 (p = 0.061) in individuals with DP serology, demonstrating intensified immune activation in this group. These findings were corroborated at the transcriptome level in independent Leishmania- and HIV-1-infected cohorts (Swiss HIV Cohort and Piaui Northeast Brazil Cohort), indicating that CXCL10 transcripts are shared by the IFN-dominated immune activation gene signatures of both pathogens and positively correlated to viral load in untreated PWH. This study demonstrated a high prevalence of PWH with L. infantum seropositivity in Bahia, Brazil, linked to IFN-mediated immune activation and a significant decrease in CD4+ levels. Our results highlight the urgent need to increase awareness and define public health strategies for the management and prevention of HIV-1 and L. infantum co-infection.

Th17/IL-17 Axis in HTLV-1-Associated Myelopathy Tropical Spastic Paraparesis and Multiple Sclerosis: Novel Insights into the Immunity During HAMTSP

Human T lymphotropic virus-associated myelopathy/tropical spastic paraparesis (HTLV/TSP), also known as HTLV-associated myelopathy/tropical spastic paraparesis (HAM/TSP), and multiple sclerosis (MS) are chronic debilitating diseases of the central nervous system; although the etiology of which is different, similarities have been observed between these two demyelinating diseases, especially in clinical manifestation and immunopathogenesis. Exorbitant response of the immune system to the virus and neurons in CNS is the causative agent of HAM/TSP and MS, respectively. Helper T lymphocyte-17 cells (Th17s), a component of the immune system, which have a proven role in immunity and autoimmunity, mediate protection against bacterial/fungal infections. The role of these cells has been reviewed in several CNS diseases. A pivotal role for Th17s is presented in demyelination, even more axial than Th1s, during MS. The effect of Th17s is not well determined in HTLV-1-associated infections; however, the evidence that we have supplied in this review illustrates the attendance, also the role of Th17 cells during HAM/TSP. Furthermore, for better conception concerning the trace of these cells in HAM/TSP, a comparative characterization with MS, the resembling disease, has been applied here.

Deep learning for detecting and elucidating human T-cell leukemia virus type 1 integration in the human genome

Human T-cell leukemia virus type 1 (HTLV-1), a retrovirus, is the causative agent for adult T cell leukemia/lymphoma and many other human diseases. Accurate and high throughput detection of HTLV-1 virus integration sites (VISs) across the host genomes plays a crucial role in the prevention and treatment of HTLV-1-associated diseases. Here, we developed DeepHTLV, the first deep learning framework for VIS prediction de novo from genome sequence, motif discovery, and cis-regulatory factor identification. We demonstrated the high accuracy of DeepHTLV with more efficient and interpretive feature representations. Decoding the informative features captured by DeepHTLV resulted in eight representative clusters with consensus motifs for potential HTLV-1 integration. Furthermore, DeepHTLV revealed interesting cis-regulatory elements in regulation of VISs that have significant association with the detected motifs. Literature evidence demonstrated nearly half (34) of the predicted transcription factors enriched with VISs were involved in HTLV-1-associated diseases. DeepHTLV is freely available at https://github.com/bsml320/DeepHTLV.

High Expression of Inflammatory Cytokines and Chemokines in Human T-lymphotropic Virus 1-Associated Adult T-cell Leukemia/Lymphoma

Background: Human T-cell lymphotropic virus type 1 (HTLV-1) is the etiological agent of adult T-cell leukemia/lymphoma (ATLL) without any specific antiviral. Objectives: This study aimed to evaluate the expression level of inflammatory chemokines and pro-inflammatory cytokines in ATLL patients, asymptomatic carriers (ACs), and healthy individuals to assess the role of these inflammatory markers in ATLL pathogenicity. Methods: This study was conducted from May 2021 to August 2022. The ATLL blood samples were collected from the oncology wards of Imam Khomeini, Shariati, and Imam Hossein hospitals, in Tehran, Iran. The blood samples of ACs and normal control subjects were collected from blood donors referred to blood transfusion centers of Tehran and Alborz provinces, Iran. RNA extraction, complementary DNA (cDNA) synthesis, and real-time polymerase chain reaction (PCR) were done in targeted sample groups to investigate the correlation and expression rate of C-C motif chemokine ligand 3 (CCL3), C-C motif chemokine ligand 4 (CCL4), C-X-C motif chemokine ligand 8 (CXCL8), interleukin 23 subunit alpha (IL-23A), and interleukin 17 A (IL-17A). Results: A total of 30 samples were collected from 3 groups. The CCL3, CCL4, CXCL8, and IL-17A messenger RNA (mRNA) expression levels were significantly upregulated in the ATLL groups. There was a significant difference between CCL3 expression between the ACs and ATLL groups. In addition, CCL4 and CXCL8 expression levels were more significant in the ATLL group than in the normal control group. The IL-17A expression level significantly increased between groups. The IL-23A expression levels had no significant differences between the ATLL, ACs, and normal control groups. Conclusions: This study showed significant upregulation of pro-inflammatory cytokines and chemokines mRNAs in HTLV-1–associated ATLL compared to the ACs and normal control groups. Conducting more experiments to investigate the therapeutic effect of chemokines/cytokines in ATLL is essential.

A comprehensive pancancer analysis reveals the potential value of RAR-related orphan receptor C (RORC) for cancer immunotherapy

Background: RAR-related orphan receptor C (RORC) plays an important role in autoimmune responses and inflammation. However, its function in cancer immunity is still unclear. Its potential value in cancer immunotherapy (CIT) needs to be further studied.

Methods: Expression and clinical data for 33 cancers were obtained from UCSC-Xena. The correlation between RORC expression and clinical parameters was analyzed using the limma software package to assess the prognostic value of RORC. Timer2.0 and DriverDBv3 were used to analyze the RORC mutation and methylation profiles. RORC-associated signaling pathways were identified by GSEA. The correlations of RORC expression with tumor microenvironment factors were further assessed, including immune cell infiltration (obtained by CIBERSORT) and immunomodulators (in pancancer datasets from the Tumor-Immune System Interactions and Drug Bank [TISIDB] database). In addition, the correlations of RORC with four CIT biomarkers (tumor mutational burden, microsatellite instability, programmed death ligand-1, and mismatch repair) were explored. Furthermore, three CIT cohorts (GSE67501, GSE168204, and IMvigor210) from the Gene Expression Omnibus database and a previously published study were used to determine the association between RORC expression and CIT response.

Results: RORC was differentially expressed in many tumor tissues relative to normal tissues (20/33). In a small number of cancers, RORC expression was correlated with age (7/33), sex (4/33), and tumor stage (9/33). Furthermore, RORC expression showed prognostic value in many cancers, especially in kidney renal clear cell carcinoma (KIRC), brain lower grade glioma (LGG), and mesothelioma (MESO). The mutation rate of RORC in most cancer types was low, while RORC was hypermethylated or hypomethylated in multiple cancers. RORC was associated with a variety of biological processes and signal transduction pathways in various cancers. Furthermore, RORC was strongly correlated with immune cell infiltration, immunomodulators, and CIT biomarkers. However, no significant association was found between RORC and CIT response in the three CIT cohorts.

Conclusion Our findings revealed the potential immunotherapeutic value of RORC for various cancers and provides preliminary evidence for the application of RORC in CIT.

Identification and Verification of Tumor Immune Microenvironment-Related Prognostic Genes in Kidney Renal Clear Cell Carcinoma

Background

The tumor immune microenvironment is vital to kidney renal clear cell carcinoma (KIRC) progression, and immunotherapies have been shown to be effective in the management of KIRC. However, the prognostic genes associated with the tumor immune microenvironment in KIRC have not been fully identified. We obtained the KIRC RNA sequencing data and the clinical characteristics from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database. We screened the gene modules associated with the tumor immune microenvironment based on the ESTIMATE algorithm and weighted gene coexpression network analysis (WGCNA). Univariate Cox analysis and the LASSO method were used to construct a prognostic model. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the accuracy of our risk model. TIMER and Single-Sample Gene Set Enrichment Analysis (ssGSEA) were used to explore the correlation between prognostic genes and immune cell infiltration.

Results

Fifty-four genes in modules were significantly associated with the overall survival (OS) time of patients with KIRC. Furthermore, 12 hub genes were selected to construct the prognostic model. The prognostic model showed superior accuracy in both TCGA and ICGC cohorts using ROC curve analysis. Systematic analysis of immune cell infiltration revealed that nine genes were significantly correlated with levels of tumor-infiltrating immune cells.

Conclusions

Our findings indicated that the tumor immune microenvironment was an important determinant of KIRC outcomes and revealed potential biomarkers for predicting patient OS and for targeted immunotherapies.

The HTLV-1 viral oncoproteins Tax and HBZ reprogram the cellular mRNA splicing landscape

Viral infections are known to hijack the transcription and translation of the host cell. However, the extent to which viral proteins coordinate these perturbations remains unclear. Here we used a model system, the human T-cell leukemia virus type 1 (HTLV-1), and systematically analyzed the transcriptome and interactome of key effectors oncoviral proteins Tax and HBZ. We showed that Tax and HBZ target distinct but also common transcription factors. Unexpectedly, we also uncovered a large set of interactions with RNA-binding proteins, including the U2 auxiliary factor large subunit (U2AF2), a key cellular regulator of pre-mRNA splicing. We discovered that Tax and HBZ perturb the splicing landscape by altering cassette exons in opposing manners, with Tax inducing exon inclusion while HBZ induces exon exclusion. Among Tax- and HBZ-dependent splicing changes, we identify events that are also altered in Adult T cell leukemia/lymphoma (ATLL) samples from two independent patient cohorts, and in well-known cancer census genes. Our interactome mapping approach, applicable to other viral oncogenes, has identified spliceosome perturbation as a novel mechanism coordinated by Tax and HBZ to reprogram the transcriptome.

Tax and HBZ are two viral regulatory proteins encoded by the human T-cell leukemia virus type 1 (HTLV-1) via sense and antisense transcripts, respectively. Both proteins are known to drive oncogenic processes that culminate in a T-cell neoplasm, known as Adult T cell leukemia/lymphoma (ATLL). We measured the effects of Tax and HBZ on host gene expression pathway by analyzing the interactome with cellular transcriptional and post-transcriptional regulators, and the transcriptome and mRNA splicing of cell lines expressing either Tax or HBZ. We compared our results with data obtained from independent cohorts of Japanese and Afro-Caribbean patients, and identified common splicing changes that might represent clinically useful biomarkers for ATLL. Finally, we provide evidence that the viral protein Tax can reprogram initial steps of the T-cell transcriptome diversification by hijacking the U2AF complex, a key cellular regulator of pre-mRNA splicing.

Identification of prognostic marker genes in head and neck squamous cell carcinoma: A study based on The Cancer Genome Atlas database and experimental validation

BACKGROUND

Early detection and prognostic prediction are crucial in improving the survival of patients with head and neck squamous cell carcinoma (HNSCC). Therefore, we provided potential molecular markers in this study for early diagnosis and prognosis of this cancer based on The Cancer Genome Atlas (TCGA) database analysis and experimental validations.

METHODS

Differentially expressed genes (DEGs) between HNSCC tumor and normal samples were identified by TCGA database-based analyses. Univariate and multivariate Cox regression analyses were applied, respectively, to identify survival-related DEGs and independent prognostic factors in HNSCC. Further, RT-qPCR was employed to verify expression of DEGs in cancer and adjacent tissues from HNSCC patients recruited in our hospital, in which we also clarified the correlation between candidate genes and clinicopathological characteristics and prognosis of HNSCC patients.

RESULTS

TCGA data analyses yielded 59 DEGs. Cox analyses identified 13 candidate genes closely related to prognosis of HNSCC patients and established a five-gene signature comprising AC103702.2, LINC00941, RPL29, FOXL2, and CCL11. This five-gene signature could classify patients into high- and low-risk groups. The survival rate of the high-risk group was significantly lower than that of the low-risk group. Clinical tissue experiments further confirmed that AC103702.2, LINC00941, CCL11, and RPL29P19 genes were inversely associated with the prognosis of HNSCC patients, while CCL11 gene was positively associated. We also found that high-risk HNSCC patients presented a higher incidence of lymph node metastasis.

CONCLUSION

Five prognostic marker genes (AC103702.2, LINC00941, CCL11, RPL29P19, and FOXL2) as a gene cluster may serve as prognostic marker genes in HNSCC.

Four genes predict the survival of osteosarcoma patients based on TARGET database

Osteosarcoma represents one of the most aggressive tumors of bone among adolescents and young adults. Despite improvements in treatment, osteosarcoma has a grave prognosis. The identification of prognostic factors is still in its infancy. Weighted gene correlation network analysis (WGCNA) was conducted on mRNA-sequencing and clinical information (gender, survival and metastasis) of osteosarcoma patients from the TARGET database to obtain genes in modules associated with metastasis of osteosarcoma. The Cox regression analysis was then performed on the gene expression profile from TARGET to screen genes associated with patients' survival. Known genes related to osteosarcoma were obtained by intersecting osteosarcoma-related genes from DisGeNET and DiGSeE, followed by the construction of PPI network of osteosarcoma-related genes and survival-related genes in modules. The screened key genes were subject to multi-factor Cox proportional hazards model, and osteosarcoma patients were classified into high- and low- risk groups according to the risk score to evaluate the potential of key genes to predict the survival of osteosarcoma patients. The WGCNA showed that 4 genes in tan and 19 genes in pink modules were related to the survival of osteosarcoma patients. Osteosarcoma-related known genes (9) were obtained in intersection of DisGeNET and DiGSeE. PPI network identified 4 key genes (KRT5, HIPK2, MAP3K5 and CD5) closely associated with survival of osteosarcoma patients. HIPK2, MAP3K5 and CD5 expression was inversely correlated with survival risk, while KRT5 expression was positively correlated with survival risk. These results show KRT5, HIPK2, MAP3K5 and CD5 serve as prognostic factors of osteosarcoma patients.

Melatonin triggers autophagic cell death by regulating RORC in Hodgkin lymphoma

Melatonin (Mel) has been shown to involve in many essential cell functions via modulating many signaling pathways. We for the first time investigated that Mel exerted anti-tumor activities in Hodgkin lymphoma (HL) via inhibiting cell proliferation and promoting cell apoptosis. Further study revealed that Mel treatment increased expression of LC3-II and decreased p62 proteins with the enhanced production of autolysosome, indicating it induced activation of autophagy. Nevertheless, Mel treatment together with autophagy inhibitors 3-MA or CQ exacerbated the damage effect of Mel in HL cells, which means autophagy plays a protective role in this process. Furthermore, we found Mel treatment increased the expression of G protein-coupled receptors MT2 and retinoic acid-related orphan receptors (RORs), eg. RORA, RORB and RORC. While RORC has the highest increase in Mel treated HL cells. In addition, RORC overexpression induced autophagy activation. Therefore, Mel showed tumor-suppressive role due to an increased level of RORC induced autophagy in HL.