A CIBERSORTx-based immune cell scoring system could independently predict the prognosis of patients with myelodysplastic syndromes

Mouse testicular macrophages can independently produce testosterone and are regulated by Cebpb

BACKGROUND

Testicular macrophages (TM) have long been recognized for their role in immune response within the testicular environment. However, their involvement in steroid hormone synthesis, particularly testosterone, has not been fully elucidated. This study aims to explore the capability of TM to synthesize and secrete testosterone de novo and to investigate the regulatory mechanisms involved.

RESULTS

Transcriptomic analysis revealed significant expression of Cyp11a1, Cyp17a1, Hsd3b1, and Hsd17b3 in TM, which are key enzymes in the testosterone synthesis pathway. qPCR analysis and immunofluorescence validation confirmed the autonomous capability of TM to synthesize testosterone. Ablation of TM in mice resulted in decreased physiological testosterone levels, underscoring the significance of TM in maintaining testicular testosterone levels. Additionally, the study also demonstrated that Cebpb regulates the expression of these crucial genes, thereby modulating testosterone synthesis.

CONCLUSIONS

This research establishes that TM possess the autonomous capacity to synthesize and secrete testosterone, contributing significantly to testicular testosterone levels. The transcription factor Cebpb plays a crucial role in this process by regulating the expression of key genes involved in testosterone synthesis.

Effects of the commensal microbiota on spleen and mesenteric lymph node immune function: investigation in a germ-free piglet model

Commensal microbial-host interaction is crucial for host metabolism, growth, development, and immunity. However, research on microbial-host immunity in large animal models has been limited. This study was conducted to investigate the effects of the commensal microbiota on immune function in two model groups: germ-free (GF) and specific-pathogen-free (SPF) piglets. The weight and organ index of the spleen of the GF piglet were larger than those in the SPF piglet (P < 0.05). The histological structure of the red pulp area and mean area of germinal centers were larger in the SPF piglet than in the GF piglet (P < 0.05), whereas the areas of staining of B cells and T cells in the spleen and mesenteric lymph nodes (MLNs) were lower in the GF piglet (P < 0.05). We identified immune-related genes in the spleen and MLNs using RNA sequencing, and used real-time quantitative PCR to analyze the expression of core genes identified in gene set enrichment analysis. The expression levels of genes in the transforming growth factor-β/SMAD3 signaling pathway, Toll-like receptor 2/MyD88/nuclear factor-κB signaling pathway, and pro-inflammatory factor genes IL-6 and TNF-α in the spleen and MLNs were higher in the SPF piglet and in splenic lymphocytes compared with those in the GF and control group, respectively, under treatment with acetic acid, propionic acid, butyric acid, lipopolysaccharide (LPS), or concanavalin A (ConA). The abundances of plasma cells, CD8++ T cells, follicular helper T cells, and resting natural killer cells in the spleen and MLNs were significantly greater in the SPF piglet than in the GF piglet (P < 0.05). In conclusion, the commensal microbiota influenced the immune tissue structure, abundances of immune cells, and expression of immune-related pathways, indicating the importance of the commensal microbiota for spleen and MLNs development and function. In our study, GF piglet was used as the research model, eliminating the interference of microbiota in the experiment, and providing a suitable and efficient large animal research model for exploring the mechanism of "microbial-host" interactions.

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Stellae-123 gene expression signature improved risk stratification in taiwanese acute myeloid leukemia patients

The European Leukemia Net recommendations provide valuable guidance in treatment decisions of patients with acute myeloid leukemia (AML). However, the genetic complexity and heterogeneity of AML are not fully covered, notwithstanding that gene expression analysis is crucial in the risk stratification of AML. The Stellae-123 score, an AI-based model that captures gene expression patterns, has demonstrated robust survival predictions in AML patients across four western-population cohorts. This study aims to evaluate the applicability of Stellae-123 in a Taiwanese cohort. The Stellae-123 model was applied to 304 de novo AML patients diagnosed and treated at the National Taiwan University Hospital. We find that the pretrained (BeatAML-based) model achieved c-indexes of 0.631 and 0.632 for the prediction of overall survival (OS) and relapse-free survival (RFS), respectively. Model retraining within our cohort further improve the cross-validated c-indexes to 0.667 and 0.667 for OS and RFS prediction, respectively. Multivariable analysis identify both pretrained and retrained models as independent prognostic biomarkers. We further show that incorporating age, Stellae-123, and ELN classification remarkably improves risk stratification, revealing c-indices of 0.73 and 0.728 for OS and RFS, respectively. In summary, the Stellae-123 gene expression signature is a valuable prognostic tool for AML patients and model retraining can improve the accuracy and applicability of the model in different populations.

An analysis of the prognostic role of reactive oxygen species-associated genes in breast cancer

BACKGROUND

This study aimed to type breast cancer in relation to reactive oxygen species (ROS), clinical indicators, single nucleotide variant (SNV) mutations, functional differences, immune infiltration, and predictive responses to immunotherapy or chemotherapy, and constructing a prognostic model.

METHODS

We used uniCox analysis, ConsensusClusterPlus, and the proportion of ambiguous clustering (PAC) to analyze The Cancer Genome Atlas (TCGA) data to determine optimal groupings and obtain differentially expressed ROS-related genes. Clinical indicators were then combined with the classification results and the Chi-square test was used to assess differences. We further examined SNV mutations, and functional differences using gene set enrichment analysis (GSEA) analysis, the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, immune cell infiltration, and response to immunotherapy and chemotherapy. A prognostic model for breast cancer was constructed using these differentially expressed genes, immunotherapy or chemotherapy responses, and survival curves. RT-qPCR was used to detect the differences in the expression of LCE3D, CA1, PIRT and SMR3A in breast cancer cell lines and normal breast epithelial cell line.

RESULTS

We identified two distinct tumor types with significant differences in ROS-related gene expression, clinical indicators, SNV mutations, functional pathways, and immune infiltration. The response to specific chemotherapy drugs and immunotherapy treatments also documented significant differences. The prognostic model constructed with 16 genes linked to survival could efficiently divide patients into high- and low-risk groups. The high-risk group showed a poorer prognosis, higher tumor purity, distinct immune microenvironment, and lower immunotherapy response. RT-qPCR results showed that LCE3D, CA1, PIRT and SMR3A are highly expressed in breast cancer.

CONCLUSION

Our methodical examination presented an enhanced insight into the molecular and immunological heterogeneity of breast cancer. It can contribute to the understanding of prognosis and offer valuable insights for personalized treatment strategies. Further, the prognostic model can potentially serve as a powerful tool for risk stratification and therapeutic decision-making in clinical settings.

Immune-monitoring of myelodysplastic neoplasms: Recommendations from the i4MDS consortium

Advancements in comprehending myelodysplastic neoplasms (MDS) have unfolded significantly in recent years, elucidating a myriad of cellular and molecular underpinnings integral to disease progression. While molecular inclusions into prognostic models have substantively advanced risk stratification, recent revelations have emphasized the pivotal role of immune dysregulation within the bone marrow milieu during MDS evolution. Nonetheless, immunotherapy for MDS has not experienced breakthroughs seen in other malignancies, partly attributable to the absence of an immune classification that could stratify patients toward optimally targeted immunotherapeutic approaches. A pivotal obstacle to establishing "immune classes" among MDS patients is the absence of validated accepted immune panels suitable for routine application in clinical laboratories. In response, we formed International Integrative Innovative Immunology for MDS (i4MDS), a consortium of multidisciplinary experts, and created the following recommendations for standardized methodologies to monitor immune responses in MDS. A central goal of i4MDS is the development of an immune score that could be incorporated into current clinical risk stratification models. This position paper first consolidates current knowledge on MDS immunology. Subsequently, in collaboration with clinical and laboratory specialists, we introduce flow cytometry panels and cytokine assays, meticulously devised for clinical laboratories, aiming to monitor the immune status of MDS patients, evaluating both immune fitness and identifying potential immune "risk factors." By amalgamating this immunological characterization data and molecular data, we aim to enhance patient stratification, identify predictive markers for treatment responsiveness, and accelerate the development of systems immunology tools and innovative immunotherapies.

Single-cell genomics and regulatory networks for 388 human brains

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Bone marrow macrophages are involved in the ineffective hematopoiesis of myelodysplastic syndromes

Myelodysplastic syndromes (MDS) are a group of heterogeneous myeloid clonal disorders characterized by ineffective hematopoiesis. Accumulating evidence has shown that macrophages (MΦs) are important components in the regulation of tumor progression and hematopoietic stem cells (HSCs). However, the roles of bone marrow (BM) MΦs in regulating normal and malignant hematopoiesis in different clinical stages of MDS are largely unknown. Age-paired patients with lower-risk MDS (N = 15), higher-risk MDS (N = 15), de novo acute myeloid leukemia (AML) (N = 15), and healthy donors (HDs) (N = 15) were enrolled. Flow cytometry analysis showed increased pro-inflammatory monocyte subsets and a decreased classically activated (M1) MΦs/alternatively activated (M2) MΦs ratio in the BM of patients with higher-risk MDS compared to lower-risk MDS. BM MФs from patients with higher-risk MDS and AML showed impaired phagocytosis activity but increased migration compared with lower-risk MDS group. AML BM MΦs showed markedly higher S100A8/A9 levels than lower-risk MDS BM MΦs. More importantly, coculture experiments suggested that the HSC supporting abilities of BM MΦs from patients with higher-risk MDS decreased, whereas the malignant cell supporting abilities increased compared with lower-risk MDS. Gene Ontology enrichment comparing BM MΦs from lower-risk MDS and higher-risk MDS for genes was involved in hematopoiesis- and immunity-related pathways. Our results suggest that BM MΦs are involved in ineffective hematopoiesis in patients with MDS, which indicates that repairing aberrant BM MΦs may represent a promising therapeutic approach for patients with MDS.

Emerging Insights into Molecular Mechanisms of Inflammation in Myelodysplastic Syndromes

Inflammation impacts human hematopoiesis across physiologic and pathologic conditions, as signals derived from the bone marrow microenvironment, such as pro-inflammatory cytokines and chemokines, have been shown to alter hematopoietic stem cell (HSCs) homeostasis. Dysregulated inflammation can skew HSC fate-related decisions, leading to aberrant hematopoiesis and potentially contributing to the pathogenesis of hematological disorders such as myelodysplastic syndromes (MDS). Recently, emerging studies have used single-cell sequencing and muti-omic approaches to investigate HSC cellular heterogeneity and gene expression in normal hematopoiesis as well as in myeloid malignancies. This review summarizes recent reports mechanistically dissecting the role of inflammatory signaling and innate immune response activation due to MDS progression. Furthermore, we highlight the growing importance of using multi-omic techniques, such as single-cell profiling and deconvolution methods, to unravel MDSs' heterogeneity. These approaches have provided valuable insights into the patterns of clonal evolution that drive MDS progression and have elucidated the impact of inflammation on the composition of the bone marrow immune microenvironment in MDS.

Driver gene combinations dictate cutaneous squamous cell carcinoma disease continuum progression

The molecular basis of disease progression from UV-induced precancerous actinic keratosis (AK) to malignant invasive cutaneous squamous cell carcinoma (cSCC) and potentially lethal metastatic disease remains unclear. DNA sequencing studies have revealed a massive mutational burden but have yet to illuminate mechanisms of disease progression. Here we perform RNAseq transcriptomic profiling of 110 patient samples representing normal sun-exposed skin, AK, primary and metastatic cSCC and reveal a disease continuum from a differentiated to a progenitor-like state. This is accompanied by the orchestrated suppression of master regulators of epidermal differentiation, dynamic modulation of the epidermal differentiation complex, remodelling of the immune landscape and an increase in the preponderance of tumour specific keratinocytes. Comparative systems analysis of human cSCC coupled with the generation of genetically engineered murine models reveal that combinatorial sequential inactivation of the tumour suppressor genes Tgfbr2, Trp53, and Notch1 coupled with activation of Ras signalling progressively drives cSCC progression along a differentiated to progenitor axis. Taken together we provide a comprehensive map of the cSCC disease continuum and reveal potentially actionable events that promote and accompany disease progression.

Integrating bioinformatic resources to identify characteristics of rheumatoid arthritis-related usual interstitial pneumonia

BACKGROUND

Rheumatoid arthritis (RA) is often accompanied by a common extra-articular manifestation known as RA-related usual interstitial pneumonia (RA-UIP), which is associated with a poor prognosis. However, the mechanism remains unclear. To identify potential mechanisms, we conducted bioinformatics analysis based on high-throughput sequencing of the Gene Expression Omnibus (GEO) database.

RESULTS

Weighted gene co-expression network analysis (WGCNA) analysis identified 2 RA-positive related modules and 4 idiopathic pulmonary fibrosis (IPF)-positive related modules. A total of 553 overlapped differentially expressed genes (DEG) were obtained, of which 144 in the above modules were further analyzed. The biological process of "oxidative phosphorylation" was found to be the most relevant with both RA and IPF. Additionally, 498 up-regulated genes in lung tissues of RA-UIP were screened out and enriched by 7 clusters, of which 3 were closely related to immune regulation. The analysis of immune infiltration showed a characteristic distribution of peripheral immune cells in RA-UIP, compared with IPF-UIP in lung tissues.

CONCLUSIONS

These results describe the complex molecular and functional landscape of RA-UIP, which will help illustrate the molecular pathological mechanism of RA-UIP and identify new biomarkers and therapeutic targets for RA-UIP in the future.

Distinct genetic landscapes and their clinical implications in younger and older patients with myelodysplastic syndromes

Myelodysplastic syndromes (MDS) are a group of clinically and genetically diverse diseases that impose patients with an increased risk of leukemic transformation. While MDS is a disease of the elderly, the interplay between aging and molecular profiles is not fully understood, especially in the Asian population. Thus, we compared the genetic landscape between younger and older patients in a cohort of 698 patients with primary MDS to advance our understanding of the distinct pathogenesis and different survival impacts of gene mutations in MDS according to age. We found that the average mutation number was higher in the older patients than younger ones. The younger patients had more WT1 and CBL mutations, but less mutated ASXL1, DNMT3A, TET2, SF3B1, SRSF2, STAG2, and TP53 than the older patients. In multivariable survival analysis, RUNX1 mutations with higher variant allele frequency (VAF) and U2AF1 and TP53 mutations were independent poor prognostic indicators in the younger patients, whereas DNMT3A and IDH2 mutations with higher VAF and TP53 mutations conferred inferior outcomes in the older patients. In conclusion, we demonstrated the distinct genetic landscape between younger and older patients with MDS and suggested that mutations impact survival in an age-depended manner.

Deconvolution of whole blood transcriptomics identifies changes in immune cell composition in patients with systemic lupus erythematosus (SLE) treated with mycophenolate mofetil

BACKGROUND

Systemic lupus erythematosus (SLE) is a clinically and biologically heterogeneous autoimmune disease. We explored whether the deconvolution of whole blood transcriptomic data could identify differences in predicted immune cell frequency between active SLE patients, and whether these differences are associated with clinical features and/or medication use.

METHODS

Patients with active SLE (BILAG-2004 Index) enrolled in the BILAG-Biologics Registry (BILAG-BR), prior to change in therapy, were studied as part of the MASTERPLANS Stratified Medicine consortium. Whole blood RNA-sequencing (RNA-seq) was conducted at enrolment into the registry. Data were deconvoluted using CIBERSORTx. Predicted immune cell frequencies were compared between active and inactive disease in the nine BILAG-2004 domains and according to immunosuppressant use (current and past).

RESULTS

Predicted cell frequency varied between 109 patients. Patients currently, or previously, exposed to mycophenolate mofetil (MMF) had fewer inactivated macrophages (0.435% vs 1.391%, p = 0.001), naïve CD4 T cells (0.961% vs 2.251%, p = 0.002), and regulatory T cells (1.858% vs 3.574%, p = 0.007), as well as a higher proportion of memory activated CD4 T cells (1.826% vs 1.113%, p = 0.015), compared to patients never exposed to MMF. These differences remained statistically significant after adjusting for age, gender, ethnicity, disease duration, renal disease, and corticosteroid use. There were 2607 differentially expressed genes (DEGs) in patients exposed to MMF with over-representation of pathways relating to eosinophil function and erythrocyte development and function. Within CD4 + T cells, there were fewer predicted DEGs related to MMF exposure. No significant differences were observed for the other conventional immunosuppressants nor between patients according disease activity in any of the nine organ domains.

CONCLUSION

MMF has a significant and persisting effect on the whole blood transcriptomic signature in patients with SLE. This highlights the need to adequately adjust for background medication use in future studies using whole blood transcriptomics.

CD79A work as a potential target for the prognosis of patients with OSCC: analysis of immune cell infiltration in oral squamous cell carcinoma based on the CIBERSORTx deconvolution algorithm

OBJECTIVE

To analyze the abundance of infiltrating tumor immune cells in patients with oral squamous cell carcinoma (OSCC) and to search for potential targets that can predict patient prognosis.

METHODS

A total of 400 samples from 210 patients with OSCC were collected using The Cancer Genome Atlas (TCGA) database. CIBERSORTx was used to evaluate the infiltration abundance of tumor immune cells. Potential target genes were searched to predict patient prognosis through case grouping, differential analysis, and enrichment analysis. Surgical excisional tissue sections of patients with oral squamous cell carcinoma admitted to the Department of Oral and Maxillofacial Surgery, Second Affiliated Hospital of Shantou University Medical College, from 2015 to 2018 were collected and followed up.

RESULTS

The CIBERSORTx deconvolution algorithm was used to analyze the infiltration abundance of immune cells in the samples. Cases with a high infiltration abundance of naive and memory B lymphocytes improved the prognosis of OSCC patients. The prognosis of patients with low CD79A expression was significantly better than that of patients with high CD79A expression.

CONCLUSION

CD79A can predict the infiltration abundance of B lymphocytes in the tumor microenvironment of patients with OSCC. CD79A is a potential target for predicting the prognosis of patients with OSCC. This study provides novel ideas for the treatment of OSCC and for predicting patient prognosis.

Identification of telomere-related genes associated with aging-related molecular clusters and the construction of a diagnostic model in Alzheimer's disease based on a bioinformatic analysis

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative disease that is strongly associated with aging. Telomeres are DNA sequences that protect chromosomes from damage and shorten with age. Telomere-related genes (TRGs) may play a role in AD's pathogenesis.

OBJECTIVES

To identify TRGs related to aging clusters in AD patients, explore their immunological characteristics, and build a TRG-based prediction model for AD and AD subtypes.

METHODS

We analyzed the gene expression profiles of 97 AD samples from the GSE132903 dataset, using aging-related genes (ARGs) as clustering variables. We also assessed immune-cell infiltration in each cluster. We performed a weighted gene co-expression network analysis to identify cluster-specific differentially expressed TRGs. We compared four machine-learning models (random forest, generalized linear model [GLM], gradient boosting model, and support vector machine) for predicting AD and AD subtypes based on TRGs and validated TRGs by conducting an artificial neural network (ANN) analysis and a nomogram model.

RESULTS

We identified two aging clusters in AD patients with distinct immunological features: Cluster A had higher immune scores than Cluster B. Cluster A and the immune system are intimately associated, and this association could affect immunological function and result in AD via the digestive system. The GLM predicted AD and AD subtypes most accurately and was validated by the ANN analysis and nomogram model.

CONCLUSION

Our analyses revealed novel TRGs associated with aging clusters in AD patients and their immunological characteristics. We also developed a promising prediction model based on TRGs for assessing AD risk.

Whole transcriptome sequencing reveals HOXD11-AGAP3, a novel fusion transcript in the Indian acute leukemia cohort

Introduction: Acute leukemia is a heterogeneous disease with distinct genotypes and complex karyotypes leading to abnormal proliferation of hematopoietic cells. According to GLOBOCAN reports, Asia accounts for 48.6% of leukemia cases, and India reports ~10.2% of all leukemia cases worldwide. Previous studies have shown that the genetic landscape of AML in India is significantly different from that in the western population by WES. Methods: We have sequenced and analyzed 9 acute myeloid leukemia (AML) transcriptome samples in the present study. We performed fusion detection in all the samples and categorized the patients based on cytogenetic abnormalities, followed by a differential expression analysis and WGCNA analysis. Finally, Immune profiles were obtained using CIBERSORTx. Results: We found a novel fusion HOXD11-AGAP3 in 3 patients, BCR-ABL1 in 4, and KMT2A-MLLT3 in one patient. Categorizing the patients based on their cytogenetic abnormalities and performing a differential expression analysis, followed by WGCNA analysis, we observed that in the HOXD11-AGAP3 group, correlated co-expression modules were enriched with genes from pathways like Neutrophil degranulation, Innate Immune system, ECM degradation, and GTP hydrolysis. Additionally, we obtained HOXD11-AGAP3-specific overexpression of chemokines CCL28 and DOCK2. Immune profiling using CIBRSORTx revealed differences in the immune profiles across all the samples. We also observed HOXD11-AGAP3-specific elevated expression of lincRNA HOTAIRM1 and its interacting partner HOXA2. Discussion: The findings highlight population-specific HOXD11-AGAP3, a novel cytogenetic abnormality in AML. The fusion led to alterations in immune system represented by CCL28 and DOCK2 over-expression. Interestingly, in AML, CCL28 is known prognostic marker. Additionally, non-coding signatures (HOTAIRM1) were observed specific to the HOXD11-AGAP3 fusion transcript which are known to be implicated in AML.

A three-gene leukaemic stem cell signature score is robustly prognostic in chronic myelomonocytic leukaemia

Leukaemic stem cell (LSC) gene expression has recently been linked to prognosis in patients with acute myeloid leukaemia (17-gene LSC score, LSC-17) and myelodysplastic syndromes. Although chronic myelomonocytic leukaemia (CMML) is regarded as a stem cell disorder, the clinical and biological impact of LSCs on CMML patients remains elusive. Making use of multiple independent validation cohorts, we here describe a concise three-gene expression signature (LSC-3, derived from the LSC-17 score) as an independent and robust prognostic factor for leukaemia-free and overall survival in CMML. We propose that LSC-3 could be used to supplement existing risk stratification systems, to improve prognostic performance and guide management decisions.

An inflammation-related gene landscape predicts prognosis and response to immunotherapy in virus-associated hepatocellular carcinoma

Background

Due to the viral infection, chronic inflammation significantly increases the likelihood of hepatocellular carcinoma (HCC) development. Nevertheless, an inflammation-based signature aimed to predict the prognosis and therapeutic effect in virus-related HCC has rarely been established.

Method

Based on the integrated analysis, inflammation-associated genes (IRGs) were systematically assessed. We comprehensively investigated the correlation between inflammation and transcriptional profiles, prognosis, and immune cell infiltration. Then, an inflammation-related risk model (IRM) to predict the overall survival (OS) and response to treatment for virus-related HCC patients was constructed and verified. Also, the potential association between IRGs and tumor microenvironment (TME) was investigated. Ultimately, hub genes were validated in plasma samples and cell lines via qRT-PCR. After transfection with shCCL20 combined with overSLC7A2, morphological change of SMMC7721 and huh7 cells was observed. Tumorigenicity model in nude mouse was established.

Results

An inflammatory response-related gene signature model, containing MEP1A, CCL20, ADORA2B, TNFSF9, ICAM4, and SLC7A2, was constructed by conjoint analysis of least absolute shrinkage and selection operator (LASSO) Cox regression and gaussian finite mixture model (GMM). Besides, survival analysis attested that higher IRG scores were positively relevant to worse survival outcomes in virus-related HCC patients, which was testified by external validation cohorts (the ICGC cohort and GSE84337 dataset). Univariate and multivariate Cox regression analyses commonly proved that the IRG was an independent prognostic factor for virus-related HCC patients. Thus, a nomogram with clinical factors and IRG was also constructed to superiorly predict the prognosis of patients. Featured with microsatellite instability-high, mutation burden, and immune activation, lower IRG score verified a superior OS for sufferers. Additionally, IRG score was remarkedly correlated with the cancer stem cell index and drug susceptibility. The measurement of plasma samples further validated that CCL20 upexpression and SLC7A2 downexpression were positively related with virus-related HCC patients, which was in accord with the results in cell lines. Furthermore, CCL20 knockdown combined with SLC7A2 overexpression availably weakened the tumor growth in vivo.

Conclusions

Collectively, IRG score, serving as a potential candidate, accurately and stably predicted the prognosis and response to immunotherapy in virus-related HCC patients, which could guide individualized treatment decision-making for the sufferers.

Evaluation of the clinical significance of global mRNA alternative splicing in patients with acute myeloid leukemia

Aberrant alternative splicing (AS) is involved in leukemogenesis. This study explored the clinical impact of alterations in global AS patterns in 341 patients with acute myeloid leukemia (AML) newly diagnosed at the National Taiwan University Hospital and validated it using The Cancer Genome Atlas (TCGA) cohort. While studying normal cord blood CD34⁺ /CD38^- cells, we found that AML cells exhibited significantly different global splicing patterns. AML with mutated TP53 had a particularly high degree of genome-wide aberrations in the splicing patterns. Aberrance in the global splicing pattern was an independent unfavorable prognostic factor affecting the overall survival of patients with AML receiving standard intensive chemotherapy. The integration of global splicing patterns into the 2022 European LeukemiaNet risk classification could stratify AML patients into four groups with distinct prognoses in both our experimental and TCGA cohorts. We further identified four genes with AS alterations that harbored prognostic significance in both of these cohorts. Moreover, these survival-associated AS events are involved in several important cellular processes that might be associated with poor response to intensive chemotherapy. In summary, our study demonstrated the clinical and biological implications of differential global splicing patterns in AML patients. Further studies with larger prospective cohorts are required to confirm these findings.

Human fetal cerebellar cell atlas informs medulloblastoma origin and oncogenesis

Medulloblastoma (MB) is the most common malignant childhood brain tumour1,2, yet the origin of the most aggressive subgroup-3 form remains elusive, impeding development of effective targeted treatments. Previous analyses of mouse cerebella3-5 have not fully defined the compositional heterogeneity of MBs. Here we undertook single-cell profiling of freshly isolated human fetal cerebella to establish a reference map delineating hierarchical cellular states in MBs. We identified a unique transitional cerebellar progenitor connecting neural stem cells to neuronal lineages in developing fetal cerebella. Intersectional analysis revealed that the transitional progenitors were enriched in aggressive MB subgroups, including group 3 and metastatic tumours. Single-cell multi-omics revealed underlying regulatory networks in the transitional progenitor populations, including transcriptional determinants HNRNPH1 and SOX11, which are correlated with clinical prognosis in group 3 MBs. Genomic and Hi-C profiling identified de novo long-range chromatin loops juxtaposing HNRNPH1/SOX11-targeted super-enhancers to cis-regulatory elements of MYC, an oncogenic driver for group 3 MBs. Targeting the transitional progenitor regulators inhibited MYC expression and MYC-driven group 3 MB growth. Our integrated single-cell atlases of human fetal cerebella and MBs show potential cell populations predisposed to transformation and regulatory circuitries underlying tumour cell states and oncogenesis, highlighting hitherto unrecognized transitional progenitor intermediates predictive of disease prognosis and potential therapeutic vulnerabilities.

CD79A Work as a Potential Target For The Prognosis of Patients With HNSCC: Analysis of Immune Cell Infiltration In Head and Neck Squamous Cell Carcinoma Based on The CIBERSORTx Deconvolution Algorithm.. [DOI: 10.21203/rs.3.rs-2177047/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Objective To analyze the abundance of infiltrating tumor immune cells in patients with head and neck squamous cell carcinoma (HNSCC) and to search for potential targets that can predict patient prognosis. Methods A total of 400 samples from 210 patients with HNSCC were collected using The Cancer Genome Atlas (TCGA) database. CIBERSORTx was used to evaluate the infiltration abundance of tumor immune cells. Potential target genes were searched to predict patient prognosis through case grouping, differential analysis, and enrichment analysis. The correlation between target genes and tumor immune cell infiltration was verified using the TIMER2.0 database. Surgical excisional tissue sections of patients with head and neck squamous cell carcinoma admitted to the Department of Oral and Maxillofacial Surgery, Second Affiliated Hospital of Shantou University Medical College, from 2015 to 2018 were collected and followed up. Results The CIBERSORTx deconvolution algorithm was used to analyze the infiltration abundance of immune cells in the samples. Cases with a high infiltration abundance of naive and memory B lymphocytes exhibited a significantly improved prognosis. The prognosis of patients with high CD79A expression was significantly better than that of patients with low CD79A expression. In addition, CD79A expression was significantly correlated with B lymphocyte infiltration in the tumor microenvironment. Conclusion CD79A can predict the infiltration abundance of B lymphocytes in the tumor microenvironment of patients with HNSCC. CD79A is a potential target for predicting the prognosis of patients with HNSCC. This study provides novel ideas for the treatment of HNSCC and for predicting patient prognosis.

Higher RUNX1 expression levels are associated with worse overall and leukaemia-free survival in myelodysplastic syndrome patients

RUNX1 mutations are frequently detected in various myeloid neoplasms and implicate unfavourable clinical outcomes in patients with myelodysplastic syndrome (MDS) and acute myeloid leukaemia (AML). On the other hand, high expression of RUNX1 is also correlated with poor prognosis in AML patients. However, the clinical relevancy of RUNX1 expression in MDS patients remains elusive. This study aimed to investigate the prognostic and biologic impacts of RUNX1 expression in MDS patients. We recruited 341 MDS patients who had sufficient bone marrow samples for next-generation sequencing. Higher RUNX1 expression occurred more frequently in the patients with Revised International Prognostic Scoring System (IPSS-R) higher-risk MDS than the lower-risk group. It was closely associated with poor-risk cytogenetics and mutations in ASXL1, NPM1, RUNX1, SRSF2, STAG2, TET2 and TP53. Furthermore, patients with higher RUNX1 expression had significantly shorter leukaemia-free survival (LFS) and overall survival (OS) than those with lower expression. Subgroups analysis revealed that higher-RUNX1 group consistently had shorter LFS and OS than the lower-RUNX1 group, no matter RUNX1 was mutated or not. The same findings were observed in IPSS-R subgroups. In multivariable analysis, higher RUNX1 expression appeared as an independent adverse risk factor for survival. The prognostic significance of RUNX1 expression was validated in two external public cohorts, GSE 114922 and GSE15061. In summary, we present the characteristics and prognosis of MDS patients with various RUNX1 expressions and propose that RUNX1 expression complement RUNX1 mutation in MDS prognostication, wherein patients with wild RUNX1 but high expression may need more proactive treatment.