xCell: digitally portraying the tissue cellular heterogeneity landscape

Impacts of Nutlin-3a and exercise on murine double minute 2-enriched glioma treatment

JOURNAL/nrgr/04.03/01300535-202504000-00029/figure1/v/2024-07-06T104127Z/r/image-tiff Recent research has demonstrated the impact of physical activity on the prognosis of glioma patients, with evidence suggesting exercise may reduce mortality risks and aid neural regeneration. The role of the small ubiquitin-like modifier (SUMO) protein, especially post-exercise, in cancer progression, is gaining attention, as are the potential anti-cancer effects of SUMOylation. We used machine learning to create the exercise and SUMO-related gene signature (ESLRS). This signature shows how physical activity might help improve the outlook for low-grade glioma and other cancers. We demonstrated the prognostic and immunotherapeutic significance of ESLRS markers, specifically highlighting how murine double minute 2 (MDM2), a component of the ESLRS, can be targeted by nutlin-3. This underscores the intricate relationship between natural compounds such as nutlin-3 and immune regulation. Using comprehensive CRISPR screening, we validated the effects of specific ESLRS genes on low-grade glioma progression. We also revealed insights into the effectiveness of Nutlin-3a as a potent MDM2 inhibitor through molecular docking and dynamic simulation. Nutlin-3a inhibited glioma cell proliferation and activated the p53 pathway. Its efficacy decreased with MDM2 overexpression, and this was reversed by Nutlin-3a or exercise. Experiments using a low-grade glioma mouse model highlighted the effect of physical activity on oxidative stress and molecular pathway regulation. Notably, both physical exercise and Nutlin-3a administration improved physical function in mice bearing tumors derived from MDM2-overexpressing cells. These results suggest the potential for Nutlin-3a, an MDM2 inhibitor, with physical exercise as a therapeutic approach for glioma management. Our research also supports the use of natural products for therapy and sheds light on the interaction of exercise, natural products, and immune regulation in cancer treatment.

MOICS, a novel classier deciphering immune heterogeneity and aid precise management of clear cell renal cell carcinoma at multiomics level

Recent studies have indicated that the tumor immune microenvironment plays a pivotal role in the initiation and progression of clear cell renal cell carcinoma (ccRCC). However, the characteristics and heterogeneity of tumor immunity in ccRCC, particularly at the multiomics level, remain poorly understood. We analyzed immune multiomics datasets to perform a consensus cluster analysis and validate the clustering results across multiple internal and external ccRCC datasets; and identified two distinctive immune phenotypes of ccRCC, which we named multiomics immune-based cancer subtype 1 (MOICS1) and subtype 2 (MOICS2). The former, MOICS1, is characterized by an immune-hot phenotype with poor clinical outcomes, marked by significant proliferation of CD4+ and CD8+ T cells, fibroblasts, and high levels of immune inhibitory signatures; the latter, MOICS2, exhibits an immune-cold phenotype with favorable clinical characteristics, characterized by robust immune activity and high infiltration of endothelial cells and immune stimulatory signatures. Besides, a significant negative correlation between immune infiltration and angiogenesis were identified. We further explored the mechanisms underlying these differences, revealing that negatively regulated endopeptidase activity, activated cornification, and neutrophil degranulation may promote an immune-deficient phenotype, whereas enhanced monocyte recruitment could ameliorate this deficiency. Additionally, significant differences were observed in the genomic landscapes between the subtypes: MOICS1 exhibited mutations in TTN, BAP1, SETD2, MTOR, MUC16, CSMD3, and AKAP9, while MOICS2 was characterized by notable alterations in the TGF-β pathway. Overall, our work demonstrates that multi-immune omics remodeling analysis enhances the understanding of the immune heterogeneity in ccRCC and supports precise patient management.

Molecular classification of geriatric breast cancer displays distinct senescent subgroups of prognostic significance

Breast cancer in the elderly presents distinct biological characteristics and clinical treatment responses compared with cancer in younger patients. Comprehensive Geriatric Assessment is recommended for evaluating treatment efficacy in elderly cancer patients based on physiological classification. However, research on molecular classification in older cancer patients remains insufficient. In this study, we identified two subgroups with distinct senescent clusters among geriatric breast cancer patients through multi-omics analysis. Using various machine learning algorithms, we developed a comprehensive scoring model called "Sene_Signature," which more accurately distinguished elderly breast cancer patients compared with existing methods and better predicted their prognosis. The Sene_Signature was correlated with tumor immune cell infiltration, as supported by single-cell transcriptomics, RNA sequencing, and pathological data. Furthermore, we observed increased drug responsiveness in patients with a high Sene_Signature to treatments targeting the epidermal growth factor receptor and cell-cycle pathways. We also established a user-friendly web platform to assist investigators in assessing Sene_Signature scores and predicting treatment responses for elderly breast cancer patients. In conclusion, we developed a novel model for evaluating prognosis and therapeutic responses, providing a potential molecular classification that assists in the pre-treatment assessment of geriatric breast cancer.

Investigating the molecular mechanisms between type 1 diabetes and mild cognitive impairment using bioinformatics analysis, with a focus on immune response

The immune system is involved in the development and progression of several diseases. Type 1 diabetes mellitus (T1DM), an autoimmune disorder, influences the progression of several other conditions; however, the link between T1DM and mild cognitive impairment (MCI) remains unclear. This study investigated the underlying immune response mechanisms that contribute to the development and progression of T1DM and MCI. Microarray datasets for MCI (GSE63060) and T1DM (GSE30208) were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package. To explore the functional implications of these DEGs, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were conducted using ClusterProfiler. Protein-protein interaction networks for the DEGs were constructed using the STRING database and visualized using Cytoscape. The Molecular Complex Detection algorithm was used to analyze DEGs. Immune cell infiltration in patients with T1DM and MCI was analyzed using the xCell method. Gene set enrichment analysis was used to gain in-depth insights into the functional characteristics of T1DM and MCI. Immune-related genes were obtained from the GeneCards and ImmPort databases. Machine learning algorithms were used to identify potential hub genes associated with immunity for T1DM and MCI diagnosis, and the diagnostic value was assessed using the receiver operating characteristic curve. The identified genes were validated using quantitative polymerase chain reaction. In the T1DM and MCI datasets, 610 DEGs showed consistent trends, of which 232 and 378 were upregulated and downregulated, respectively. Immune response analysis revealed significant changes in the immune cells associated with MCI and T1DM. Using immune-related genes, DEGs, and machine learning techniques, we identified CD3D in the MCI and T1DM groups. We observed a gradual decline in the cognitive function of mice with T1DM as the disease progressed. CD3D expression increased with increasing disease severity; CD3D primarily affected CD4+ T cells. This study revealed a complex interaction between T1DM and MCI, providing novel insights into the intricate relationship between immune dysregulation and cognitive impairment and expanding our understanding of these two interconnected disorders. These findings will facilitate the development of therapeutic interventions and identification of potential therapeutic targets.

The effect of immunotherapy PD-1 blockade on acute bone cancer pain: Insights from transcriptomic and microbiomic profiling

INTRODUCTION

The skeletal system ranks as the third most common site for cancer metastasis, often leading to pain with nociceptive and neuropathic features. Programmed cell death protein 1 (PD-1)-targeting therapeutic antibodies offer effective cancer treatment but can cause treatment-related acute pain. Understanding the mechanisms of this pain and identifying potential interventions is still a challenge.

METHODS

A murine model of bone cancer pain was established using Lewis lung carcinoma (LLC) cells, followed by intravenous administration of nivolumab, a human anti-PD-1 monoclonal antibody. Pain thresholds were measured, and micro-CT images of the skeletal system were obtained. High-throughput sequencing of the spinal cord/colon transcriptome during the acute phase of bone cancer pain and gut microbiota analysis at the end of the treatment were performed. Immunofluorescence staining and western blot experiments assessed spinal cord microglia activation and acute pain-associated molecules.

RESULTS

PD-1 inhibition with nivolumab protected against bone degradation initiated by LLC cell administration but consistently induced acute pain during nivolumab treatment. Spinal cord and colon transcriptomics revealed an immunopathological pattern during tumor progression and the acute pain phase, with notable changes in interleukin and S100 gene families. Gut microbiota analysis post-immunotherapy showed a decline in beneficial bacteria associated with short-chain fatty acid (SCFA) production. Activation of spinal cord microglia and enhanced glycolytic metabolism were confirmed as key factors in inducing acute pain following immunotherapy.

CONCLUSIONS

This study reveals that nivolumab induces acute pain by activating microglia and enhancing glycolytic metabolism in the treatment of bone cancer and uncovers connections between transcriptomic changes, gut microbiota, and acute pain following immune checkpoint blockade (ICB) treatment. It offers novel insights into the relationship between immune checkpoint blockade therapies and pain management.

PANoptosis signaling enables broad immune response in psoriasis: From pathogenesis to new therapeutic strategies

Background

Accumulating evidence suggests that regulated cell death, such as pyroptosis, apoptosis, and necroptosis, is deeply involved in the pathogenesis of psoriasis. As a newly recognized form of systematic cell death, PANoptosis is involved in a variety of inflammatory disorders through amplifying inflammatory and immune cascades, but its role in psoriasis remains elusive.

Objectives

To reveal the role of PANoptosis in psoriasis for a potential therapeutic strategy.

Methods

Multitranscriptomic analysis and experimental validation were used to identify PANoptosis signaling in psoriasis. RNA-seq and scRNA-seq analyses were performed to establish a PANoptosis-mediated immune response in psoriasis, which revealed hub genes through WGCNA and predicted disulfiram as a potential drug. The effect and mechanism of disulfiram were verified in imiquimod (IMQ)-induced psoriasis.

Results

Here, we found a highlighted PANoptosis signature in psoriasis patients through multitranscriptomic analysis and experimental validation. Based on this, two distinct PANoptosis patterns (non/high) were identified, which were the options for clinical classification. The high-PANoptosis-related group had a higher response rate to immune cell infiltration (such as M1 macrophages and keratinocytes). Subsequently, WGCNA showed the hub genes (e.g., S100A12, CYCS, NOD2, STAT1, HSPA4, AIM2, MAPK7), which were significantly associated with clinical phenotype, PANoptosis signature, and identified immune response in psoriasis. Finally, we explored disulfiram (DSF) as a candidate drug for psoriasis through network pharmacology, which ameliorated IMQ-mediated psoriatic symptoms through antipyroptosis-mediated inflammation and enhanced apoptotic progression. By analyzing the specific ligand-receptor interaction pairs within and between cell lineages, we speculated that DSF might exert its effects by targeting keratinocytes directly or targeting M1 macrophages to downregulate the proliferation of keratinocytes.

Conclusions

PANoptosis with its mediated immune cell infiltration provides a roadmap for research on the pathogenesis and therapeutic strategies of psoriasis.

Novel immune cross-talk between inflammatory bowel disease and IgA nephropathy

The mechanisms underlying the complex correlation between immunoglobulin A nephropathy (IgAN) and inflammatory bowel disease (IBD) remain unclear. This study aimed to identify the optimal cross-talk genes, potential pathways, and mutual immune-infiltrating microenvironments between IBD and IgAN to elucidate the linkage between patients with IBD and IgAN. The IgAN and IBD datasets were obtained from the Gene Expression Omnibus (GEO). Three algorithms, CIBERSORTx, ssGSEA, and xCell, were used to evaluate the similarities in the infiltrating microenvironment between the two diseases. Weighted gene co-expression network analysis (WGCNA) was implemented in the IBD dataset to identify the major immune infiltration modules, and the Boruta algorithm, RFE algorithm, and LASSO regression were applied to filter the cross-talk genes. Next, multiple machine learning models were applied to confirm the optimal cross-talk genes. Finally, the relevant findings were validated using histology and immunohistochemistry analysis of IBD mice. Immune infiltration analysis showed no significant differences between IBD and IgAN samples in most immune cells. The three algorithms identified 10 diagnostic genes, MAPK3, NFKB1, FDX1, EPHX2, SYNPO, KDF1, METTL7A, RIDA, HSDL2, and RIPK2; FDX1 and NFKB1 were enhanced in the kidney of IBD mice. Kyoto Encyclopedia of Genes and Genomes analysis showed 15 mutual pathways between the two diseases, with lipid metabolism playing a vital role in the cross-talk. Our findings offer insights into the shared immune mechanisms of IgAN and IBD. These common pathways, diagnostic cross-talk genes, and cell-mediated abnormal immunity may inform further experimental studies.

The molecular subtypes of autoimmune diseases

Autoimmune diseases (ADs) are characterized by their complexity and a wide range of clinical differences. Despite patients presenting with similar symptoms and disease patterns, their reactions to treatments may vary. The current approach of personalized medicine, which relies on molecular data, is seen as an effective method to address the variability in these diseases. This review examined the pathologic classification of ADs, such as multiple sclerosis and lupus nephritis, over time. Acknowledging the limitations inherent in pathologic classification, the focus shifted to molecular classification to achieve a deeper insight into disease heterogeneity. The study outlined the established methods and findings from the molecular classification of ADs, categorizing systemic lupus erythematosus (SLE) into four subtypes, inflammatory bowel disease (IBD) into two, rheumatoid arthritis (RA) into three, and multiple sclerosis (MS) into a single subtype. It was observed that the high inflammation subtype of IBD, the RA inflammation subtype, and the MS "inflammation & EGF" subtype share similarities. These subtypes all display a consistent pattern of inflammation that is primarily driven by the activation of the JAK-STAT pathway, with the effective drugs being those that target this signaling pathway. Additionally, by identifying markers that are uniquely associated with the various subtypes within the same disease, the study was able to describe the differences between subtypes in detail. The findings are expected to contribute to the development of personalized treatment plans for patients and establish a strong basis for tailored approaches to treating autoimmune diseases.

Comparison of stromal vascular fraction cell composition between Coleman fat and extracellular matrix/stromal vascular fraction gel

As a mechanically condensed product of Coleman fat, extracellular matrix/stromal vascular fraction gel (ECM/SVF-gel) eliminates adipocytes, concentrates SVF cells, and improves fat graft retention. This study aims to compare SVF cell composition between Coleman fat and ECM/SVF-gel. Matched Coleman fat and ECM/SVF-gel of 28 healthy women were subjected to RNA-seq, followed by functional enrichment and cell-type-specific enrichment analyses, and deconvolution of SVF cell subsets, reconstructing SVF cell composition in the transcriptome level. ECM/SVF-gels had 9 upregulated and 73 downregulated differentially expressed genes (DEGs). Downregulated DEGs were mainly associated with inflammatory and immune responses, and enriched in fat macrophages. M2 macrophages, resting CD4+ memory T cells, M1 macrophages, resting mast cells, and M0 macrophages ranked in the top five most prevalent immune cells in the two groups. The proportions of the principal non-immune cells (e.g., adipose-derived stem cells, pericytes, preadipocytes, microvascular endothelial cells) had no statistical differences between the two groups. Our findings reveal ECM/SVF-gels share the same dominant immune cells beneficial to fat graft survival with Coleman fat, but exhibiting obvious losses of immune cells (especially macrophages), while non-immune cells necessary for adipose regeneration might have no significant loss in ECM/SVF-gels and their biological effects could be markedly enhanced by the ECM/SVF-gel's condensed nature.

DNA methylation heterogeneity attributable to a complex tumor immune microenvironment prompts prognostic risk in glioma

Gliomas are malignant tumours of the human nervous system with different World Health Organization (WHO) classifications, glioblastoma (GBM) with higher grade and are more malignant than lower-grade glioma (LGG). To dissect how the DNA methylation heterogeneity in gliomas is influenced by the complex cellular composition of the tumour immune microenvironment, we first compared the DNA methylation profiles of purified human immune cells and bulk glioma tissue, stratifying three tumour immune microenvironmental subtypes for GBM and LGG samples from The Cancer Genome Atlas (TCGA). We found that more intermediate methylation sites were enriched in glioma tumour tissues, and used the Proportion of sites with Intermediate Methylation (PIM) to compare intertumoral DNA methylation heterogeneity. A larger PIM score reflected stronger DNA methylation heterogeneity. Enhanced DNA methylation heterogeneity was associated with stronger immune cell infiltration, better survival rates, and slower tumour progression in glioma patients. We then created a Cell-type-associated DNA Methylation Heterogeneity Contribution (CMHC) score to explore the impact of different immune cell types on heterogeneous CpG site (CpGct) in glioma tissues. We identified eight prognosis-related CpGct to construct a risk score: the Cell-type-associated DNA Methylation Heterogeneity Risk (CMHR) score. CMHR was positively correlated with cytotoxic T-lymphocyte infiltration (CTL), and showed better predictive performance for IDH status (AUC = 0.96) and glioma histological phenotype (AUC = 0.81). Furthermore, DNA methylation alterations of eight CpGct might be related to drug treatments of gliomas. In conclusion, we indicated that DNA methylation heterogeneity is associated with a complex tumour immune microenvironment, glioma phenotype, and patient's prognosis.

Enhanced cancer cell proliferation and aggressive phenotype counterbalance in breast cancer with high BRCA1 gene expression

PURPOSE

While comprehensive research exists on the mutation of the DNA repair gene BRCA1, limited information is available regarding the clinical significance of BRCA1 gene expression. Given that cancer cell proliferation is aggrevated by DNA repair, we hypothesized that high BRCA1 gene expression breast cancer (BC) might be linked with aggressive tumor biology and poor clinical outcomes.

METHODS

The cohorts: The Cancer Genome Atlas (TCGA, n = 1069), METABRIC (n = 1903), and SCAN-B (n = 3273) were utilzed to obtain data of 6245 BC patients.

RESULTS

BC patients without BRCA1 mutation exhibited higher BRCA1 expression, which was associated with DNA repair functionality. However, no such correlation was observed with BRCA2 expression. The association of high BRCA1 expression with cancer cell proliferation was evidenced by significant enrichment of cell proliferation-related gene sets, higher histological grade, and proliferation score. Furthermore, increased levels of homologous recombination deficiency, intratumoral heterogeneity, and altered fractions were associated with high BRCA1 expression. Moreover, BC with high BRCA1 expression exhibited reduced infiltration of dendritic cells and CD8 T-cells, while showing increased infiltration of Th1 cells. Surprisingly, BRCA1 expression was not associated with the survival of BC irrespective of the subtypes. Conversely, BC with low BRCA1 expression enriched cancer aggravating pathway gene sets, such as Cancer Stem Cell-related signaling (NOTCH and HEDGEHOG), Angiogenesis, Epithelial-Mesenchymal Transition, Inflammatory Response, and TGF-beta signaling.

CONCLUSION

Despite being linked to heightened proliferation of cancer cells and unassertive phenotype, BRCA1 expression did not show any association with survival in BC.

Transcriptomic profiles of myxofibrosarcoma and undifferentiated pleomorphic sarcoma correlate with clinical and genomic features

Myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) are two common and aggressive subtypes of soft tissue sarcoma. The aim of this study was to assess potential transcriptomic differences between MFS and UPS tumours and to evaluate the extent to which differences in gene expression profiles were associated with genomic and clinical features. The study included 162 patients with tumours diagnosed as MFS (N = 62) or UPS (N = 100). The patients had been diagnosed and treated at two Swedish sarcoma centres during a 30-year period. For gene expression profiling and gene fusion detection all tumours were analysed using RNA-sequencing and could be compared with data on clinical outcome (N = 155), global copy number profiles (N = 145), and gene mutations (N = 128). Gene expression profiling revealed three transcriptomic clusters (TCs) without any clear separation of MFS and UPS. One TC was associated with longer metastasis-free survival. These tumours had lower tumour mutation burden (TMB), were enriched for a copy number signature representative of focal LOH and chromosomal instability on a diploid background, and were relatively immune-depleted. MFS and UPS showed extensive genomic overlap, with whole genome doubling occurring more frequently among the latter. The results support the idea that MFS and UPS tumours have largely overlapping genomic and transcriptomic features, with UPS tumours showing more aggressive behaviour and more complex genomes. Independently of the tumour type, clinically relevant subgroups were revealed by gene expression analysis, and the finding of multiple genomic subgroups strongly suggest the existence of subgroups of relevance to treatment stratification. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

A novel high-risk model identified by epithelial-mesenchymal transition predicts prognosis and radioresistance in rectal cancer

Many studies have shown that tumor cells that survive radiotherapy are more likely to metastasize, but the underlying mechanism remains unclear. Here we aimed to identify epithelial-mesenchymal transition (EMT)-related key genes, which associated with prognosis and radiosensitivity in rectal cancer. First, we obtained differentially expressed genes by analyzing the RNA expression profiles of rectal cancer retrieved from The Cancer Genome Atlas database, EMT-related genes, and radiotherapy-related databases, respectively. Then, Lasso and Cox regression analyses were used to establish an EMT-related prognosis model (EMTPM) based on the identified independent protective factor Fibulin5 (FBLN5) and independent risk gene EHMT2. The high-EMTPM group exhibited significantly poorer prognosis. Then, we evaluated the signature in an external clinical validation cohort. Through in vivo experiments, we further demonstrated that EMTPM effectively distinguishes radioresistant from radiosensitive patients with rectal cancer. Moreover, individuals in the high-EMTPM group showed increased expression of immune checkpoints compared to their counterparts. Finally, pan-cancer analysis of the EMTPM model also indicated its potential for predicting the prognosis of lung squamous cell carcinoma and breast cancer patients undergoing radiotherapy. In summary, we established a novel predictive model for rectal cancer prognosis and radioresistance based on FBLN5 and EHMT2 expressions, and suggested that immune microenvironment may be involved in the process of radioresistance. This predictive model could be used to select management strategies for rectal cancer.

SCGB1A1 as a novel biomarker and promising therapeutic target for the management of HNSCC

Head and neck cancer (HNC) is the sixth most common type of cancer worldwide, and head and neck squamous cell carcinoma (HNSCC) accounts for 90% of HNC cases. Furthermore, HNSCC accounts for 400,000 cancer-associated deaths worldwide each year. However, at present there is an absence of a versatile biomarker that can be used for diagnosis, prognosis evaluation and as a therapeutic target for HNSCC. In the present study, bioinformatics analysis was used to assess the relationship between hub genes and the clinical features of patients with HNSCC. The findings from the bioinformatics analysis were then verified using clinical samples and in vitro experiments. A total of 51 overlapping genes were identified from the intersection of differentially expressed genes and co-expressed genes. The top 10 hub genes were obtained from a protein-protein interaction network of overlapping genes. Among the hub genes, only secretoglobin family 1A member 1 (SCGB1A1) was significantly associated with both overall and disease-free survival. Specifically, upregulated SCGB1A1 expression levels were associated with prolonged overall and disease-free survival. Moreover, the SCGB1A1 expression levels were negatively correlated with drug sensitivity. Notably, it was demonstrated that SCGB1A1 was involved in tumor immunoreaction by affecting the infiltration of cells and checkpoint regulation of immune cells. Additionally, it was shown that SCGB1A1 regulated multiple key cancer-related signaling pathways, including extracellular matrix receptor interaction, transforming growth factor-β and tumor metabolism signaling pathways. Based on the results of the present study, SCGB1A1 may serve as a novel biomarker for predicting the diagnosis, prognosis and therapeutic effectiveness of certain drugs in patients with HNSCC. Moreover, SCGB1A1 may serve as a potential therapeutic target for the management of HNSCC.

Prognostic prediction signature and molecular subtype for liver cancer: A CTC/CTM‑related gene prediction model and independent external validation

Liver cancer is the second leading cause of tumor-related death worldwide, and a serious threat to lives and health. Circulating tumor cells (CTCs) facilitate the progression of various cancers, including liver cancer. The relationship between CTC/circulating tumor microemboli-related genes (CRGs) and the prognosis of liver cancer is unclear. The aim of the present study was to identify CTC/circulating tumour microemboli-related genes (CRGs) in hepatocellular carcinoma and to investigate their clinical significance. Transcriptomic data from The Cancer Genome Atlas (International Cancer Genome Consortium (ICGC) and GSE117623 databases were combined, and differentially expressed CRGs were identified. These were subsequently analyzed via least absolute shrinkage and selection operator and multivariate Cox analyses, and a five-gene risk signature was constructed. The signature was validated in the ICGC and GSE14520 dataset with survival analysis and receiver operating characteristic curve analysis. Immunocyte infiltration, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE), and the somatic mutation rate were also compared between high- and low-risk groups, based on the median predictive index, to further evaluate the immunotherapeutic value of the model. Molecular subtypes of liver cancer were characterized by the non-negative matrix factorization method and potential therapeutic compounds were evaluated for different subtypes. Nomograms were utilized to predict the prognosis of patients, and the signature was compared with previous literature models. Additionally, the biological function of one of the CRGs, tumor protein p53 inducible protein 3 (TP53I3), in liver cancer was further explored through in vitro experiments. Analysis of the prognostic characteristics of the five CRGs led to the identification of two liver cancer subtypes. Patients in the low-risk group had a longer survival compared with those in the high-risk group, and patients in the latter group were associated with a higher TMB, immunocyte infiltration and somatic mutation rate, and lower TIDE scores. The prognostic profile was validated in the ICGC and GSE14520 datasets and exhibited a good predictive performance. In vitro analysis showed that the knockdown of TP53I3 suppressed liver cancer cell proliferation. In summary, CRGs were used to develop a new prognostic signature to predict the prognosis of patients with liver cancer. This signature may be used to assess the prognosis of patients and may provide new insights for clinical management strategies. In addition, TP53I3 is potentially a therapeutic target for liver cancer.

MATR3 promotes liver cancer progression by suppressing DHX58-mediated type I interferon response

MATR3 is a nuclear matrix protein implicated in various cancers; however, its specific role in tumor progression remains unclear. The study utilized the TCGA database to reveal that MATR3 expression is upregulated in liver cancer and is correlated with poor prognosis. Functionally, MATR3 promoted liver cancer cell proliferation and metastasis. Comprehensive RNA sequencing analysis showed that MATR3 significantly affected the type I IFN signaling pathway and DHX58 is a downstream target of MATR3. Further experiments showed that MATR3 bound to DHX58 mRNA through its RRM structural domain and recruited YTHDF2, an m6A reader, leading to degradation of DHX58 mRNA and suppression of the type I IFN signaling pathway. The knockout of MATR3 in liver cancer cells triggered a natural immune response that stimulated CD8+ T cells to eliminate liver cancer cells. This study demonstrated that MATR3 downregulates type I IFN signaling in liver cancer cells through m6A modification and inhibits immune cell infiltration within tumors. These findings expand our understanding of the role of MATR3 in liver cancer.

Dual targeting chimeric antigen receptor cells enhance antitumour activity by overcoming T cell exhaustion in pancreatic cancer

BACKGROUND AND PURPOSE

Although our previous data indicated that claudin 18 isoform 2 (CLDN18.2)-targeted chimeric antigen receptor (CAR) T cells displayed remarkable clinical efficacy in CLDN18.2-positive gastric cancer, their efficacy is limited in pancreatic ductal adenocarcinoma (PDAC). The tumour microenvironment (TME) is one of the main obstacles to the efficacy of CAR-T and remodelling the TME may be a possible way to overcome this obstacle. The TME of PDAC is characterized by abundant cancer-related fibroblasts (CAFs), which hinder the infiltration and function of CLDN18.2-targeted CAR-T cells. The expression of fibroblast activation protein alpha (FAP) is an important feature of active CAFs, providing potential targets for eliminating CAFs.

EXPERIMENTAL APPROACH

In this study, we generated 10 FAP/CLDN 18.2 dual-targeted CAR-T cells and evaluated their anti-tumour ability in vitro and in vivo.

KEY RESULTS

Compared with conventional CAR-T cells, some dual-targeted CAR-T cells showed improved therapeutic effects in mouse pancreatic cancers. Further, dual-targeted CAR-T cells with better anti-tumour effect could suppress the recruitment of myeloid-derived suppressor cells (MDSCs) to improve the immunosuppressive TME, which contributes to the survival of CD8+ T cells. Moreover, dual-targeted CAR-T cells reduced the exhaustion of T cells in transforming TGF-β dependent manner.

CONCLUSION AND IMPLICATIONS

The dual-targeted CAR-T cells obtained enhancement of T effector function, inhibition of T cell exhaustion, and improvement of tumour microenvironment. Our findings provide a theoretical rationale for dual-targeted FAP/CLDN 18.2 CAR-T cells therapy in PDAC.

Genomic and transcriptomic profiling of inflammatory breast cancer reveals distinct molecular characteristics to non-inflammatory breast cancers

PURPOSE

Inflammatory breast cancer (IBC), a rare and highly aggressive form of breast cancer, accounts for 10% of breast cancer-related deaths. Previous omics studies of IBC have focused solely on one of genomics or transcriptomics and did not discover common differences that could distinguish IBC from non-IBC.

METHODS

Seventeen IBC patients and five non-IBC patients as well as additional thirty-three Asian breast cancer samples from TCGA-BRCA were included for the study. We performed whole-exon sequencing (WES) to investigate different somatic genomic alterations, copy number variants, and large structural variants between IBC and non-IBC. Bulk RNA sequencing (RNA-seq) was performed to examine the differentially expressed genes, pathway enrichment, and gene fusions. WES and RNA-seq data were further investigated in combination to discover genes that were dysregulated in both genomics and transcriptomics.

RESULTS

Copy number variation analysis identified 10 cytobands that showed higher frequency in IBC. Structural variation analysis showed more frequent deletions in IBC. Pathway enrichment and immune infiltration analysis indicated increased immune activation in IBC samples. Gene fusions including CTSC-RAB38 were found to be more common in IBC. We demonstrated more commonly dysregulated RAS pathway in IBC according to both WES and RNA-seq. Inhibitors targeting RAS signaling and its downstream pathways were predicted to possess promising effects in IBC treatment.

CONCLUSION

We discovered differences unique in Asian women that could potentially explain IBC etiology and presented RAS signaling pathway as a potential therapeutic target in IBC treatment.

Prognostic value of TMTC1 in pan-cancer analysis

Background

Transmembrane and tetratricopeptide repeat containing 1 (TMTC1) is a recently discovered enzyme involved in the O-mannosylation of cadherins and protocadherins. It has been implicated in various types of cancer, but the overall prognostic significance of TMTC1 in pan-cancer and its potential as an immunotherapeutic target remain unclear.

Methods

We applied various bioinformatics methods to investigate the potential oncogenic roles of TMTC1 using public databases. This analysis involved examining the expression, prognosis, genetic alterations, immune infiltration, immunotherapy response, drug sensitivity, and regulatory mechanisms of the TMTC1 gene in diverse cancer types.

Results

In this study, we observed that TMTC1 expression is reduced in 19 types of cancer (ACC, BLCA, BRCA, CESC, COAD, ESCA, GBM, KICH, KIRC, KIRP, LAML, LUAD, LUSC, PRAD, READ, STAD, THCA, UCEC, and UCS) compared to normal tissues. Conversely, TMTC1 expression is elevated in OV and PAAD relative to normal tissues. Moreover, our analysis revealed that high expression of TMTC1 was associated with worse overall survival (OS) outcomes in patients with ACC, BLCA, COAD, GBM, KIRP, OV, STAD, and UCEC, but better OS outcomes in patients with CESC, KIRC, LUSC, and PAAD. Notably, patients with TMTC1 mutations or deep deletions demonstrated longer OS, while those with TMTC1 amplification showed shorter OS. There was a significant correlation between the expression level of TMTC1 and the infiltration of cancer-associated fibroblasts (CAFs) and endothelial cells. Using data from six real-world immunotherapy cohorts of BLCA, SKCM and RCC, we discovered that high TMTC1 expression was associated with better OS or progression-free survival (PFS). Lastly, through TMTC1-related gene enrichment analysis, some biological processes and pathways were found to be significantly enriched, such as vascular endothelial growth factor receptor signaling pathway and ECM-receptor interaction.

Conclusions

Our study demonstrates the prognostic significance of TMTC1 in pan-cancer and highlights its potential as an immunotherapeutic target.

Tumor microbiota of renal cell carcinoma affects clinical prognosis by influencing the tumor immune microenvironment

Despite reported influences of the intratumoral microbiome on cancer progression, its role in this subtype remains unclear. This study aimed to characterize the microbial landscape and signatures of kidney renal clear cell carcinoma using RNA-Seq data from The Cancer Genome Atlas. Following microbial decontamination, differential microbial analysis was conducted between tumorous and adjacent non-tumorous samples. Compared to non-tumorous samples, tumorous microbiota exhibited reduced α and β diversity and distinct phylum-level communities. Differential microbial analysis between patients exhibiting long and short overall survival revealed ten significant differential microbial genera, with six genera correlating with a positive prognosis (Plasmodium, Babesia, Toxoplasma, Cytobacillus, Alicyclobacillus, Verrucomicrobium) and four with a negative prognosis (Colletotrichum, Leuconostoc, Gluconobacter, and Parabacteroides). Employing Cox regression analysis and support vector machines, a prognosis-related microbiome risk signature was developed, achieving an AUC of 0.809. Based on this risk signature, two microbiome-based subtypes were found to be significantly associated with distinct clinical prognoses and immune microenvironments. These findings were corroborated by significant correlations between prognostic-relevant microorganisms and 30 immune-related differentially expressed genes. Specifically, microbial genera associated with a negative prognosis were linked to a pro-tumor acute inflammatory immune response, whereas genera related to a positive prognosis were associated with an anti-tumor adaptive immune response. In conclusion, microbiome-based subtyping revealed correlations between tumor microbiome, clinical prognosis, and tumor microenvironment, indicating intratumoral microbiota as a promising prognostic biomarker for kidney renal clear cell carcinoma.

Inhibition of PRMT5 moderately suppresses prostate cancer growth in vivo but enhances its response to immunotherapy

Protein arginine methylation is a common post-translational modification (PTM) catalyzed by nine protein arginine methyltransferases (PRMTs). As the major symmetric arginine methyltransferase that methylates both histone and non-histone substrates, PRMT5 plays key roles in a number of biological processes critical for development and tumorigenesis. PRMT5 overexpression has been reported in multiple cancer types including prostate cancer (PCa), but the exact biological and mechanistic understanding of PRMT5 in aggressive PCa remains ill-defined. Here, we show that PRMT5 is upregulated in PCa, correlates with worse patient survival, promotes corrupted RNA splicing, and functionally cooperates with an array of pro-tumorigenic pathways to enhance oncogenesis. PRMT5 inhibition via either genetic knockdown or pharmacological inhibition reduces stemness with paralleled differentiation and arrests cell cycle progression without causing appreciable apoptosis. Strikingly, the severity of antitumor effect of PRMT5 inhibition correlates with disease aggressiveness, with AR+ PCa being less affected. Molecular characterization pinpoints MYC, but not (or at least to a lesser degree) AR, as the main partner of PRMT5 to form a positive feedback loop to exacerbate malignancy in both AR+ and AR- PCa cells. Inspired by the surprising finding that PRMT5 negatively correlates with tumor immune infiltration and transcriptionally suppresses an immune-gene program, we further show that although PRMT5 inhibitor (PRMT5i) EPZ015666 or anti-PD-1 immunotherapy alone exhibits limited antitumor effects, combination of PRMT5i with anti-PD-1 displays superior efficacy in inhibiting castration-resistant PCa (CRPC) in vivo. Finally, to expand the potential use of PRMT5i through a synthetic lethality concept, we also perform a global CRISPR/Cas9 knockout screen to unravel that many clinical-grade drugs of known oncogenic pathways can be repurposed to target CRPC when used in combination with PRMT5i at low doses. Collectively, our findings establish a rationale to exploit PRMT5i in combination with immunotherapy or other targeted therapies to treat aggressive PCa.

Machine learning based on biological context facilitates the identification of microvascular invasion in intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma is a rare disease associated with a poor prognosis, primarily due to early recurrence and metastasis. An important feature of this condition is microvascular invasion (MVI). However, current predictive models based on imaging have limited efficacy in this regard. This study employed a random forest model to construct a predictive model for MVI identification and uncover its biological basis. Single-cell transcriptome sequencing, whole exome sequencing, and proteome sequencing were performed. The area under the curve of the prediction model in the validation set was 0.93. Further analysis indicated that MVI-associated tumor cells exhibited functional changes related to epithelial-mesenchymal transition and lipid metabolism due to alterations in the nuclear factor-kappa B and mitogen-activated protein kinase signaling pathways. Tumor cells were also differentially enriched for the interleukin-17 signaling pathway. There was less infiltration of SLC30A1+ CD8+ T cells expressing cytotoxic genes in MVI-associated intrahepatic cholangiocarcinoma, whereas there was more infiltration of myeloid cells with attenuated expression of the major histocompatibility complex II pathway. Additionally, MVI-associated intercellular communication was closely related to the SPP1-CD44 and ANXA1-FPR1 pathways. These findings resulted in a brilliant predictive model and fresh insights into MVI.

Resting natural killer cells promote the progress of colon cancer liver metastasis by elevating tumor-derived stem cell factor

The abundance and biological contribution of natural killer (NK) cells in cancer are controversial. Here, we aim to uncover clinical relevance and cellular roles of NK cells in colon cancer liver metastasis (CCLM). Here, we integrated single-cell RNA-sequencing, spatial transcriptomics (ST), and bulk RNA-sequencing datasets to investigate NK cells' biological properties and functions in the microenvironment of primary and liver metastatic tumors. Results were validated through an in vitro co-culture experiment based on bioinformatics analysis. Useing single-cell RNA-sequencing and ST, we mapped the immune cellular landscape of colon cancer and well-matched liver metastatic cancer. We discovered that GZMK+ resting NK cells increased significantly in tumor tissues and were enriched in the tumor regions of both diseases. After combining bulk RNA and clinical data, we observed that these NK cell subsets contributed to a worse prognosis. Meanwhile, KIR2DL4+ activated NK cells exhibited the opposite position and relevance. Pseudotime cell trajectory analysis revealed the evolution of activated to resting NK cells. In vitro experiments further confirmed that tumor-cell-co-cultured NK cells exhibited a decidual-like status, as evidenced by remarkable increasing CD9 expression. Functional experiments finally revealed that NK cells exhibited tumor-activating characteristics by promoting the dissociation of SCF (stem cell factor) on the tumor cells membrane depending on cell-to-cell interaction, as the supernatant of the co-culture system enhanced tumor progression. In summary, our findings revealed resting NK cells exhibited a clinical relevance with CCLM, which may be exploited for novel strategies to improve therapeutic outcomes for patients with CCLM.

Identification and Verification of Potential Markers Related to Myocardial Fibrosis by Bioinformatics Analysis

Mounting evidence indicates that myocardial fibrosis (MF) is frequently intertwined with immune and metabolic disorders. This comprehensive review aims to delve deeply into the crucial role of immune-related signature genes in the pathogenesis and progression of MF. This exploration holds significant importance as understanding the underlying mechanisms of MF is essential for developing effective diagnostic and therapeutic strategies. The dataset GSE9735 about myocardial fibrosis and non-fibrosis was downloaded from GEO database. Differentially expressed genes (DEGs) were identified by 'limma' package in R software. Then, the biological function of DEG was determined by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. XCell was used to estimate the composition pattern of matrix and immune cells. Protein-protein interaction (PPI) network was constructed based on STRING analysis software, and Hub genes were screened and functional modules were analyzed. The correlation between hub genes and immune cell subtypes was analyzed. Hub genes with |correlation coefficient|> 0.45 and p-value < 0.05 were used as characteristic biomarkers. Finally, the logistic regression model is used to verify the three markers in the training set and verification set (GSE97358 and GSE225336). A total of 635 DEGs were identified. Functional enrichment analysis shows that inflammation and immune response, extracellular matrix and structural remodeling play an important role in the pathological mechanism of MF. Immune cell infiltration analysis showed that immune cells (Plasma cells, Eosinophils, Chondrocytes and Th2 cells) significantly changed in MF pathological conditions. In PPI network analysis, IL1β, TTN, PTPRC, IGF1, ALDH1A1, CYP26A1, ALDH1A3, MYH11, CSF1R and CD80 were identified as hub genes, among which IL1β, CYP26A1 and GNG2 were regarded as immune-related characteristic markers. The AUC scores of the three biomarkers are all above 0.65, which proves that they have a good discrimination effect in MF. In this study, three immune-related genes were identified as diagnostic biomarkers of MF, which provided a new perspective for exploring the molecular mechanism of MF. This study takes a comprehensive approach to understanding the intricate relationship between myocardial fibrosis and immune metabolism. By identifying key immune-related biomarkers, this study not only reveals the molecular basis of myocardial fibrosis but also paves the way for the development of novel diagnostic tools and therapeutic strategies. These findings are critical for improving patient prognosis and may have broader implications for studying and treating other cardiovascular diseases associated with immune dysregulation.

The SRC-family serves as a therapeutic target in triple negative breast cancer with acquired resistance to chemotherapy

BACKGROUND

Resistance to chemotherapy, combined with heterogeneity among resistant tumors, represents a significant challenge in the clinical management of triple negative breast cancer (TNBC). By dissecting molecular pathways associated with treatment resistance, we sought to define patient sub-groups and actionable targets for next-line treatment.

METHODS

Bulk RNA sequencing and reverse phase protein array profiling were performed on isogenic patient-derived xenografts (PDX) representing paclitaxel-sensitive and -resistant tumors. Pathways identified as upregulated in the resistant model were further explored as targets in PDX explants. Their clinical relevance was assessed in two distinct patient cohorts (NeoAva and MET500).

RESULTS

Increased activity in signaling pathways involving SRC-family kinases (SFKs)- and MAPK/ERK was found in treatment resistant PDX, with targeted inhibitors being significantly more potent in resistant tumors. Up-regulation of SFKs- and MAPK/ERK-pathways was also detected in a sub-group of chemoresistant patients after neoadjuvant treatment. Furthermore, High SFK expression (of either SRC, FYN and/or YES1) was detected in metastatic lesions of TNBC patients with fast progressing disease (median disease-free interval 27 vs 105 months).

CONCLUSIONS

Upregulation of SFK-signaling is found in a subset of chemoresistant tumors and is persistent in metastatic lesions. Based on pre-clinical results, these patients may respond favorably to treatment targeting SFKs.

CTLA4 blockade abrogates KEAP1/STK11-related resistance to PD-(L)1 inhibitors

For patients with advanced non-small-cell lung cancer (NSCLC), dual immune checkpoint blockade (ICB) with CTLA4 inhibitors and PD-1 or PD-L1 inhibitors (hereafter, PD-(L)1 inhibitors) is associated with higher rates of anti-tumour activity and immune-related toxicities, when compared with treatment with PD-(L)1 inhibitors alone. However, there are currently no validated biomarkers to identify which patients will benefit from dual ICB1,2. Here we show that patients with NSCLC who have mutations in the STK11 and/or KEAP1 tumour suppressor genes derived clinical benefit from dual ICB with the PD-L1 inhibitor durvalumab and the CTLA4 inhibitor tremelimumab, but not from durvalumab alone, when added to chemotherapy in the randomized phase III POSEIDON trial3. Unbiased genetic screens identified loss of both of these tumour suppressor genes as independent drivers of resistance to PD-(L)1 inhibition, and showed that loss of Keap1 was the strongest genomic predictor of dual ICB efficacy-a finding that was confirmed in several mouse models of Kras-driven NSCLC. In both mouse models and patients, KEAP1 and STK11 alterations were associated with an adverse tumour microenvironment, which was characterized by a preponderance of suppressive myeloid cells and the depletion of CD8+ cytotoxic T cells, but relative sparing of CD4+ effector subsets. Dual ICB potently engaged CD4+ effector cells and reprogrammed the tumour myeloid cell compartment towards inducible nitric oxide synthase (iNOS)-expressing tumoricidal phenotypes that-together with CD4+ and CD8+ T cells-contributed to anti-tumour efficacy. These data support the use of chemo-immunotherapy with dual ICB to mitigate resistance to PD-(L)1 inhibition in patients with NSCLC who have STK11 and/or KEAP1 alterations.

Molecular characterization of PANoptosis-related genes as novel signatures for peripheral nerve injury based on time-series transcriptome sequencing

Programmed cell death (PCD) pathways play pivotal roles in the development and progression of peripheral nerve injury (PNI). PANoptosis, as a novel form of PCD pathway with key features of pyroptosis, apoptosis and necroptosis, is implicated in the pathogenesis of multiple neurologic diseases. This study aimed to identify PANoptosisrelated biomarkers and characterize their molecular roles and immune landscape in PNI. PANoptosis-related genes (PRGs) were retrieved from Reactome pathway database and previous literatures. Differentially expressed PANoptosis-related genes (DEPRGs) were identified based on a time-series transcriptome sequencing dataset. DEPRGs were predicted to be enriched in inflammatory response, inflammatory complex, PCD and NOD-like receptor signaling pathway through GO, KEGG, Reactome and GSEA analysis. Hub genes, including Ripk3, Pycard and Il18, were then recognized through PPI network and multiple algorithms. The molecular regulatory mechanisms of hub genes were elucidated by transcription factor network and competing endogenous RNA network. Moreover, the immune cell landscape of hub genes was analyzed. Eventually, the expression levels of hub genes were verified through external dataset and animal model. Ripk3, Pycard and Il18 were remarkably upregulated in PNI samples, which were in consistent with the results of bioinformatic analysis. This study uncovered the molecular characterization of PANoptosis-related genes in PNI and illustrated the novel PANoptosis biomarker for PNI.

Integrative analysis of anoikis-related genes prognostic signature with immunotherapy and identification of CDKN3 as a key oncogene in lung adenocarcinoma

Anoikis, a form of programmed cell death induced by loss of cell contact, is closely associated with tumor invasion and metastasis, making it highly significant in lung cancer research. We examined the expression patterns and prognostic relevance of Anoikis-related genes (ARGs) in lung adenocarcinoma (LUAD) using the TCGA-LUAD database. This study identified molecular subtypes associated with Anoikis in LUAD and conducted functional enrichment analyses. We constructed an ARG risk score using univariate least absolute shrinkage and selection operator (LASSO) Cox regression, validated externally with GEO datasets and clinical samples. The clinical applicability of the prognostic model was evaluated using nomograms, calibration curves, decision curve analysis (DCA), and time-dependent AUC assessments. We identified four prognostically significant genes (PLK1, SLC2A1, CDKN3, PHLDA2) and two ARG-related molecular subtypes. ARGs were generally upregulated in LUAD and correlated with multiple pathways including the cell cycle and DNA replication. The prognostic model indicated that the low-risk group had better outcomes and significant correlations with clinicopathological features, tumor microenvironment, immune therapy responses, drug sensitivity, and pan-RNA epigenetic modification-related genes. Patients with low-risk LUAD were potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. Prognostic ARGs' distribution and expression across various immune cell types were further analyzed using single-cell RNA sequencing. The pivotal role of CDKN3 in LUAD was confirmed through qRT-PCR and gene knockout experiments, demonstrating that CDKN3 knockdown inhibits tumor cell proliferation, migration, and invasion. Additionally, we constructed a ceRNA network involving CDKN3/hsa-miR-26a-5p/SNHG6, LINC00665, DUXAP8, and SLC2A1/hsa-miR-218-5p/RNASEH1-AS1, providing new insights for personalized and immune therapy decisions in LUAD patients.

TFF3 and PVRL2 co-targeting identified by multi-omics approach as an effective cancer immunosuppression strategy

BACKGROUND

The immunosuppressive tumour microenvironment (TME) plays a critical role in cancer progression and relapse by significantly influencing cancer pathogenesis through autocrine and paracrine signalling. Trefoil factor 3 (TFF3), a secreted protein, has been implicated in modulating the TME to promote cancer advancement. Herein, we investigated the potential association between TFF3 and key immunosuppressive TME components to distinguish a co-targetable oncotherapeutic strategy.

METHODS

The TFF3-PVRL2 association were identified and investigated by integrating multiple bioinformatic-tools. The virtual compound screening for PVRL2 inhibitors was done with EasyVS. The TFF3-PVRL2 protein-level correlation was validated by immunoblotting, and the effectiveness of co-inhibiting TFF3 and PVRL2 was assessed using siRNA and AMPC (a TFF3 inhibitor).

RESULTS

Analysis of the TISIDB database revealed a positive correlation between TFF3 and PVRL2 mRNA levels across multiple cancer types. This correlation was confirmed at the protein level through immunoblot analysis. Further evaluation using TCGA pan-cancer datasets demonstrated that TFF3 and PVRL2 interact to establish an immunosuppressive TME, promoting cancer progression in BRCA, LUAD, PAAD, PRAD, and STAD. Enrichment analyses of positively correlated genes, PPI network hub proteins, and ceRNA networks involving TFF3 and PVRL2, conducted using LinkedOmics, STRING, and Cytoscape, provided insights into their potential co-functions in cancer. A cell-based assay was performed to evaluate the combined therapeutic efficacy of targeting both, TFF3 and PVRL2 and virtual screening identified potential drugs for inhibiting PVRL2.

CONCLUSION

PVRL2 has emerged as a promising immunoinhibitory target with significant associations with TFF3 and represents a key co-targetable molecule for effective oncotherapeutic strategies.

Immune-related glycosylation genes based classification predicts prognosis and therapy options of osteosarcoma

Osteosarcoma is the most common primary bone malignancy, with a very poor prognosis. Aberrant glycosylation is close involvement in osteosarcoma. Accordingly, this study aimed at investigating the role of glycosylation genes in the prognosis and therapy options of osteosarcoma. The microenvironment of osteosarcoma was assessed using estimate algorithm. A total of 20 immune-related glycosylation genes (IRGGs) was identified using Pearson correlation analysis. Accordingly, osteosarcoma patients were divided into C1 and C2 type using consensus clustering. Multiple algorithms (Xcell, MCP-counter, ssGSEA, epic, quantiseq), cancer immune cycle analysis, and GSVA were applied to estimate the immune, molecule and metabolism characteristics of osteosarcoma, indicating that C1 type was featured with high immune infiltration, high glycosylation, enriched MEK signaling, and good prognosis, while C2 type was characterized by more metastasis, enriched immunotherapy-positive gene signatures, high tumor mutation burden, and poor prognosis. Results from TIDE algorithm and immunotherapy datasets suggested the C2 type's preference of immune checkpoint inhibitors (ICIs), while data of GDSC, CMap analysis and cell experiments indicated that C1 type was sensitivity to MEK inhibitor PD0325901. In addition, univariate Cox and Lasso analysis was combined to establish an IRGGs' risk score containing 6 genes (B3GNT8, FUT7, GAL3ST4, GALNT14, HS3ST2, and MFNG). The data of DCA and ROC indicated its well prediction of prognosis in osteosarcoma. Finally, cellular location analysis showed that the 6 genes not only distributed in tumor cells but also in immune cells. In summary, the classification and risk score based on IRGGs effectively predicted the prognosis and therapy options of osteosarcoma. Further studies on IRGGs may contribute to the understanding of cancer immunity in osteosarcoma.

The genomic and transcriptomic landscape of metastastic urothelial cancer

Metastatic urothelial carcinoma (mUC) is a lethal cancer, with limited therapeutic options. Large-scale studies in early settings provided critical insights into the genomic and transcriptomic characteristics of non-metastatic UC. The genomic landscape of mUC remains however unclear. Using Whole Exome (WES) and mRNA sequencing (RNA-seq) performed on metastatic biopsies from 111 patients, we show that driver genomic alterations from mUC were comparable to primary UC (TCGA data). APOBEC, platin, and HRD mutational signatures are the most prevalent in mUC, identified in 56%, 14%, and 9% of mUC samples, respectively. Molecular subtyping using consensus transcriptomic classification in mUC shows enrichment in neuroendocrine subtype. Paired samples analysis reveals subtype heterogeneity and temporal evolution. We identify potential therapeutic targets in 73% of mUC patients, of which FGFR3 (26%), ERBB2 (7%), TSC1 (7%), and PIK3CA (13%) are the most common. NECTIN4 and TACSTD2 are highly expressed regardless of molecular subtypes, FGFR3 alterations and sites of metastases.

Proteomic basis for pancreatic acinar cell carcinoma and pancreatoblastoma as similar yet distinct entities

Acinar cell carcinoma (ACC) and pancreatoblastoma (PBL) are rare pancreatic malignancies with acinar differentiation. Proteogenomic profiling of ACC and PBL revealed distinct protein expression patterns compared to pancreatic ductal adenocarcinoma (PDAC) and benign pancreas. ACC and PBL exhibited similarities, with enrichment in proteins related to RNA processing, chromosome organization, and the mitoribosome, while PDACs overexpressed proteins associated with actin-based processes, extracellular matrix, and immune-active stroma. Pathway activity differences in metabolic adaptation, epithelial-to-mesenchymal transition, and DNA repair were characterized between these diseases. PBL showed upregulation of Wnt-CTNNB1 and IGF2 pathways. Seventeen ACC-specific proteins suggested connections to metabolic diseases with mitochondrial dysfunction, while 34 PBL-specific proteins marked this pediatric cancer with an embryonic stem cell phenotype and alterations in chromosomal proteins and the cell cycle. This study provides novel insights into the proteomic landscapes of ACC and PBL, offering potential targets for diagnostic and therapeutic development.

Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells

The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus, represents one of the most significant global health crises in recent history. Despite extensive research into the immune mechanisms and therapeutic options for COVID-19, there remains a paucity of studies focusing on plasma cells. In this study, we utilized the DESeq2 package to identify differentially expressed genes (DEGs) between COVID-19 patients and controls using datasets GSE157103 and GSE152641. We employed the xCell algorithm to perform immune infiltration analyses, revealing notably elevated levels of plasma cells in COVID-19 patients compared to healthy individuals. Subsequently, we applied the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to identify COVID-19 related plasma cell module genes. Further, positive cluster biomarker genes for plasma cells were extracted from single-cell RNA sequencing data (GSE171524), leading to the identification of 122 shared genes implicated in critical biological processes such as cell cycle regulation and viral infection pathways. We constructed a robust protein-protein interaction (PPI) network comprising 89 genes using Cytoscape, and identified 20 hub genes through cytoHubba. These genes were validated in external datasets (GSE152418 and GSE179627). Additionally, we identified three potential small molecules (GSK-1070916, BRD-K89997465, and idarubicin) that target key hub genes in the network, suggesting a novel therapeutic approach. These compounds were characterized by their ability to down-regulate AURKB, KIF11, and TOP2A effectively, as evidenced by their low free binding energies determined through computational analyses using cMAP and AutoDock. This study marks the first comprehensive exploration of plasma cells' role in COVID-19, offering new insights and potential therapeutic targets. It underscores the importance of a systematic approach to understanding and treating COVID-19, expanding the current body of knowledge and providing a foundation for future research.

Germline polygenic risk scores are associated with immune gene expression signature and immune cell infiltration in breast cancer

The tumor immune microenvironment (TIME) plays key roles in tumor progression and response to immunotherapy. Previous studies have identified individual germline variants associated with differences in TIME. Here, we hypothesize that common variants associated with breast cancer risk or cancer-related traits, represented by polygenic risk scores (PRSs), may jointly influence immune features in TIME. We derived 154 immune traits from bulk gene expression profiles of 764 breast tumors and 598 adjacent normal tissue samples from 825 individuals with breast cancer in the Nurses' Health Study (NHS) and NHSII. Immunohistochemical staining of four immune cell markers were available for a subset of 205 individuals. Germline PRSs were calculated for 16 different traits including breast cancer, autoimmune diseases, type 2 diabetes, ages at menarche and menopause, body mass index (BMI), BMI-adjusted waist-to-hip ratio, alcohol intake, and tobacco smoking. Overall, we identified 44 associations between germline PRSs and immune traits at false discovery rate q < 0.25, including 3 associations with q < 0.05. We observed consistent inverse associations of inflammatory bowel disease (IBD) and Crohn disease (CD) PRSs with interferon signaling and STAT1 scores in breast tumor and adjacent normal tissue; these associations were replicated in a Norwegian cohort. Inverse associations were also consistently observed for IBD PRS and B cell abundance in normal tissue. We also observed positive associations between CD PRS and endothelial cell abundance in tumor. Our findings suggest that the genetic mechanisms that influence immune-related diseases are also associated with TIME in breast cancer.

Infiltration of Common Myeloid Progenitor (CMP) Cells is Associated With Less Aggressive Tumor Biology, Lower Risk of Brain Metastasis, Better Response to Immunotherapy, and Higher Patient Survival in Breast Cancer

OBJECTIVE

To investigate the clinical relevance of common myeloid progenitor (CMP) cells in breast tumor microenvironment (TME).

BACKGROUND

The role of rare cells in TME is less studied. In Silico transcriptomic analyses of real-world data enable us to detect and quantify rare cells, including CMP cells.

METHODS

A total of 5176 breast cancer (BC) patients from SCAN-B, METABRIC, and 5 single-cell sequence cohorts were analyzed using the xCell algorithm. The high group was defined as more than two-thirds of the CMP scores in each cohort.

RESULTS

CMP cells consist of 0.07% to 0.25% of bulk breast tumor cells, more in estrogen receptor-positive (ER+) compared with triple-negative (TN) subtype (0.1% to 0.75%, 0.18% to 0.33% of immune cells, respectively). CMP cells did not correlate with any of the myeloid lineages or stem cells in TME. CMP infiltration was higher in smaller tumors, with lower Nottingham grade, and in ER+/HER2- than in TNBC consistently in both SCAN-B and METABRIC cohorts. High CMP was significantly associated with a lower risk of brain metastasis and with better survival, particularly in ER+/HER2-. High CMP enriched epithelial-to-mesenchymal transition and angiogenesis pathways, and less cell proliferation and DNA repair gene sets. High CMP ER+/HER2- was associated with less immune cell infiltration and cytolytic activity ( P <0.001). CMP infiltration correlated with neoadjuvant chemoimmunotherapy response for both ER+/HER2- and TNBC in the ISPY-2 cohort (AUC=0.69 and 0.74, respectively).

CONCLUSIONS

CMP in BC is inversely associated with cell proliferation and brain metastasis, better response to immunotherapy, and survival. This is the first to report the clinical relevance of CMP infiltration in BC.

Potential applications of dual haptoglobin expression in the reclassification and treatment of hepatocellular carcinoma

HCC is a malignancy characterized by high incidence and mortality rates. Traditional classifications of HCC primarily rely on tumor morphology, phenotype, and multicellular molecular levels, which may not accurately capture the cellular heterogeneity within the tumor. This study integrates scRNA-seq and bulk RNA-seq to spotlight HP as a critical gene within a subgroup of HCC malignant cells. HP is highly expressed in HCC malignant cells and lowly expressed in T cells. Within malignant cells, elevated HP expression interacts with C3, promoting Th1-type responses via the C3/C3AR1 axis. In T cells, down-regulating HP expression favors the expression of Th1 cell-associated marker genes, potentially enhancing Th1-type responses. Consequently, we developed a "HP-promoted Th1 response reclassification" gene set, correlating higher activity scores with improved survival rates in HCC patients. Additionally, four predictive models for neoadjuvant treatment based on HP and C3 expression were established: 1) Low HP and C3 expression with high Th2 cell infiltration; 2) High HP and low C3 expression with high Th2 cell infiltration; 3) High HP and C3 expression with high Th1 cell infiltration; 4) Low HP and high C3 expression with high Th1 cell infiltration. In conclusion, the HP gene selected from the HCC malignant cell subgroup (Malignant_Sub 6) might serve as a potential ally against the tumor by promoting Th1-type immune responses. The establishment of the "HP-promoted Th1 response reclassification" gene set offers predictive insights for HCC patient survival prognosis and neoadjuvant treatment efficacy, providing directions for clinical treatments.

TNF-α and RPLP0 drive the apoptosis of endothelial cells and increase susceptibility to high-altitude pulmonary edema

High-altitude pulmonary edema (HAPE) is a fatal threat for sojourners who ascend rapidly without sufficient acclimatization. Acclimatized sojourners and adapted natives are both insensitive to HAPE but have different physiological traits and molecular bases. In this study, based on GSE52209, the gene expression profiles of HAPE patients were compared with those of acclimatized sojourners and adapted natives, with the common and divergent differentially expressed genes (DEGs) and their hub genes identified, respectively. Bioinformatic methodologies for functional enrichment analysis, immune infiltration, diagnostic model construction, competing endogenous RNA (ceRNA) analysis and drug prediction were performed to detect potential biological functions and molecular mechanisms. Next, an array of in vivo experiments in a HAPE rat model and in vitro experiments in HUVECs were conducted to verify the results of the bioinformatic analysis. The enriched pathways of DEGs and immune landscapes for HAPE were significantly different between sojourners and natives, and the common DEGs were enriched mainly in the pathways of development and immunity. Nomograms revealed that the upregulation of TNF-α and downregulation of RPLP0 exhibited high diagnostic efficiency for HAPE in both sojourners and natives, which was further validated in the HAPE rat model. The addition of TNF-α and RPLP0 knockdown activated apoptosis signaling in endothelial cells (ECs) and enhanced endothelial permeability. In conclusion, TNF-α and RPLP0 are shared biomarkers and molecular bases for HAPE susceptibility during the acclimatization/adaptation/maladaptation processes in sojourners and natives, inspiring new ideas for predicting and treating HAPE.

Children with eosinophilic esophagitis non-responsive to combination therapy have distinct esophageal transcriptomic and microbiome profile

BACKGROUND

A combination of proton-pump inhibitors (PPI) and topical steroids (TS) is used to treat children with eosinophilic esophagitis (EoE). However, a subset of children do not respond to this combination therapy. We aimed to identify the esophageal transcriptional, cell composition, and microbial differences between the non-responders (EoE-PPI-TSnr; n = 7) and responders (EoE-PPI-TSr; n = 7) to the combination therapy for EoE and controls (n = 9) using metatranscriptomics.

METHODS

Differential gene expression analysis was used to identify transcriptional differences, validated using the EoE diagnostic panel (EDP). Deconvolution analysis was performed to identify differences in their cell type composition. Microbiome analysis was conducted from esophageal biopsies RNAseq data, and microbial abundance was correlated with esophageal gene expression.

RESULTS

In all, 3164 upregulated and 3154 downregulated genes distinguished EoE-PPI-TSnr from EoE-PPI-TSr. Eosinophilic inflammatory response, cytokine signaling, and collagen formation pathways were significantly upregulated in EoE-PPI-TSnr. There was a 56% overlap in dysregulated genes between EoE-PPI-TSnr and EDP, with a perfect agreement in the directionality of modulation. Eosinophils, dendritic cells (DCs), immature DCs, megakaryocytic-erythroid progenitors, and T helper type 1 cells were significantly higher in EoE-PPI-TSnr. There was no significant difference in microbiome diversity. The relative abundance of Fusobacterium sp. and Acinetobacter sp. notably differed in EoE-PPI-TSnr and correlated with the key pathways.

CONCLUSION

Our results provide critical insights into the molecular, cellular, and microbial factors associated with the lack of response to PPI and TS combination therapy in children with EoE. This study advances our understanding of the pathobiology of EoE while guiding personalized treatment strategies.

Proteomic and phosphoproteomic landscape of localized prostate cancer unveils distinct molecular subtypes and insights into precision therapeutics

Building upon our previous investigation of genomic, epigenomic, and transcriptomic profiles of prostate cancer in China, we conducted a comprehensive analysis of proteomic and phosphoproteomic profiles of 82 tumor tissues and matched adjacent normal tissues from 41 Chinese patients with localized prostate cancer. We identified three distinct proteomic subtypes with significant difference in both molecular features and clinical prognosis. Notably, these proteomic subtypes exhibited a parallel degree of heterogeneity in the phosphoproteome, featuring unique metabolism, proliferation, and immune infiltration characteristics. We further demonstrated that a combination of proteins and phosphosites serves as the most effective biomarkers in prostate cancer to predict biochemical recurrence. Through an integrated multiomics analysis, we revealed mechanistic differences underlying different proteomic subtypes and highlighted the potential significance of Serine/arginine-rich splicing factor 1 (SRSF1) phosphorylation in promoting the malignant characteristics of prostate cancer cells. Our multiomics data provide valuable resources for understanding the molecular mechanisms of prostate cancer within the Chinese population, which have the potential to inform the development of personalized treatment strategies and enhance prognostic analyses for prostate cancer patients.

Construction and validation of a machine learning-based immune-related prognostic model for glioma

BACKGROUND

Glioma stands as the most prevalent primary brain tumor found within the central nervous system, characterized by high invasiveness and treatment resistance. Although immunotherapy has shown potential in various tumors, it still faces challenges in gliomas. This study seeks to develop and validate a prognostic model for glioma based on immune-related genes, to provide new tools for precision medicine.

METHODS

Glioma samples were obtained from a database that includes the ImmPort database. Additionally, we incorporated ten machine learning algorithms to assess the model's performance using evaluation metrics like the Harrell concordance index (C-index). The model genes were further studied using GSCA, TISCH2, and HPA databases to understand their role in glioma pathology at the genomic, molecular, and single-cell levels, and validate the biological function of IKBKE in vitro experiments.

RESULTS

In this study, a total of 199 genes associated with prognosis were identified using univariate Cox analysis. Subsequently, a consensus prognostic model was developed through the application of machine learning algorithms. In which the Lasso + plsRcox algorithm demonstrated the best predictive performance. The model showed a good ability to distinguish two groups in both the training and test sets. Additionally, the model genes were closely related to immunity (oligodendrocytes and macrophages), and mutation burden. The results of in vitro experiments showed that the expression level of the IKBKE gene had a significant effect on the apoptosis and migration of GL261 glioma cells. Western blot analysis showed that down-regulation of IKBKE resulted in increased expression of pro-apoptotic protein Bax and decreased expression of anti-apoptotic protein Bcl-2, which was consistent with increased apoptosis rate. On the contrary, IKBKE overexpression caused a decrease in Bax expression an increase in Bcl-2 expression, and a decrease in apoptosis rate. Tunel results further confirmed that down-regulation of IKBKE promoted apoptosis, while overexpression of IKBKE reduced apoptosis. In addition, cells with down-regulated IKBKE had reduced migration in scratch experiments, while cells with overexpression of IKBKE had increased migration.

CONCLUSION

This study successfully constructed a glioma prognosis model based on immune-related genes. These findings provide new perspectives for glioma prognosis assessment and immunotherapy.

Comprehensive analysis of bulk, single-cell RNA sequencing, and spatial transcriptomics revealed IER3 for predicting malignant progression and immunotherapy efficacy in glioma

BACKGROUND

As part of stress-triggered molecules, immediate early response 3 (IER3) dysregulation has been reported to sustain pro-oncogenic pathways and precede malignant transformation. However, the role of IER3 in glioma pathology is ill-defined.

METHODS

Immunohistochemistry (IHC) assay and publicly available glioma datasets were used to calculate the IER3 expression level in glioma. Wound healing, invasion and cell counting kit-8 (CCK8) assays were applied to measure the cell viability and capacities of migration and invasion of glioma cells in vitro. The immunofluorescence (IF) assay was used to assess the expression associations of IER3 with CCL2 and TGFBI. Cox regression analysis and Kaplan-Meier (K-M) curve were introduced to compute the prognosis-predicting value of IER3. Variations in copy number (CNVs), single nucleotide (SNVs), and methylation profiles were analyzed to illustrate the epigenetic modifications of IER3. Gliomas were divided into two subgroups using the restricted cubic spline (RCS) method. RESULTS IER3: was overexpressed and hypomethylated in gliomas and significantly associated with the dismal prognosis of glioma samples. Samples in the high IER3 subgroup were characterized by increased infiltration of tumor-associated monocytes/macrophages (TAMMs), as well as the elevated sensitivity to Dabrafenib, an inhibitor of BRAF. In addition, this subgroup demonstrated a low mutation rate of IDH, high gain rates of BRAF, ELTD1, and PDGFA. Gliomas with relatively low IER3 expression demonstrated a less invasive subtype and were featured by favorable prognosis, increased response to immunotherapy, and adjuvant chemotherapy plus radiotherapy. The IF assay revealed that IER3 was co-localized and co-expressed with TGFBI. The glioma cells with small interfering RNA (siRNA)-silenced IER3 displayed lower migration, invasion, proliferation, and cell viability than the control group.

CONCLUSIONS

In this study, we identified IER3 upregulation as an essential biomarker that could assist in adjuvant therapy and prognosis prediction for gliomas.

Impact of high-risk EBV strains on nasopharyngeal carcinoma gene expression

Nasopharyngeal carcinoma (NPC) is closely associated with Epstein-Barr Virus infection (EBV). Despite ubiquitous EBV infection worldwide, NPC displays a unique geographical distribution in Southern China and Southeast Asia. This observed phenomenon can be attributed to the interplay of different strains of EBV infection with host genetics and environmental factors. Polymorphisms on the EBV BALF2 gene have been shown to influence risk of nasopharyngeal carcinoma (NPC). Notably, two non-synonymous EBV polymorphisms (162476T>C, 163364C>T) account for majority of NPC risk in endemic regions. These polymorphisms confer amino acid changes (I1613V, V317M) within the BALF2 protein. However, their impact on NPC tumor biology is unknown. We evaluated the distribution of BALF2 risk polymorphisms in five independent genomic datasets comprising 351 NPC clinical samples, confirming the high prevalence of high-risk EBV strains in NPC. Importantly, we observed two biologically distinct groups of tumors based on their gene expression profiles when grouped by their EBV risk strains. NPC tumors with the V317M substitution demonstrated increased proliferation processes including cell cycle (NES = 1.71, p = 5.64x10-24) and keratinization (NES = 2.42, p = 6.95x10-17). In contrast, NPC tumors without the V317M substitution demonstrated increased immune-related processes, including cell activation (NES = 1.85, p = 8.29x10-31), myeloid leukocyte activation (NES = 2.16, p = 6.51x10-24) and leukocyte mediated immunity (NES = 1.99, p = 1.05x10-23). These findings provide further insight on the influence of BALF2 variants on NPC tumor biology. EBV risk strains may have the potential to define biologically important groups in NPC.

Advanced machine learning unveils CD8 + T cell genetic markers enhancing prognosis and immunotherapy efficacy in breast cancer

BACKGROUND

Breast cancer (BC) is the most common cancer in women and poses a significant health burden, especially in China. Despite advances in diagnosis and treatment, patient variability and limited early detection contribute to poor outcomes. This study examines the role of CD8 + T cells in the tumor microenvironment to identify new biomarkers that improve prognosis and guide treatment strategies.

METHODS

CD8 + T-cell marker genes were identified using single-cell RNA sequencing (scRNA-seq), and a CD8 + T cell-related gene prognostic signature (CTRGPS) was developed using 10 machine-learning algorithms. The model was validated across seven independent public datasets from the GEO database. Clinical features and previously published signatures were also analyzed for comparison. The clinical applications of CTRGPS in biological function, immune microenvironment, and drug selection were explored, and the role of hub genes in BC progression was further investigated.

RESULTS

We identified 71 CD8 + T cell-related genes and developed the CTRGPS, which demonstrated significant prognostic value, with higher risk scores linked to poorer overall survival (OS). The model's accuracy and robustness were confirmed through Kaplan-Meier and ROC curve analyses across multiple datasets. CTRGPS outperformed existing prognostic signatures and served as an independent prognostic factor. The role of the hub gene TTK in promoting malignant proliferation and migration of BC cells was validated.

CONCLUSION

The CTRGPS enhances early diagnosis and treatment precision in BC, improving clinical outcomes. TTK, a key gene in the signature, shows promise as a therapeutic target, supporting the CTRGPS's potential clinical utility.

Paired Transcriptional Analysis of Periodontitis and Peri-Implantitis within same host: a Pilot study

BACKGROUND

Peri-implantitis, a plaque-associated pathological condition, has been on the rise with the increasing prevalence of dental implants. Despite its similarities to periodontitis, peri-implantitis is difficult to control completely and has high relapse rates. This has sparked interest in exploring the pathogenic differences between the two conditions.

METHODS

This cross-sectional study involved 10 participants to concurrently examine periodontitis and peri-implantitis within the same patients, thereby minimizing inter-individual variation. Gingival tissue samples were collected from each participant, comprising 10 periodontitis and 10 peri-implantitis tissues, and RNAs were extracted. Using RNA sequencing and bioinformatics analysis, we investigated complex gene interactions, immune responses, and the role of the extracellular matrix in both conditions. We identified hub genes in each enhanced Protein-Protein Interaction network, providing crucial insights into these diseases' pathogenesis.

RESULTS

Our findings highlighted the potential involvement of activated fibroblasts in the pathogenesis of peri-implantitis, identifying three marker genes (ACTA2, FAP, and PDGFRβ) overexpressed in peri-implantitis, thus highlighting their potential as disease-specific biomarkers.

CONCLUSIONS

Our study uncovered a novel connection between peri-implantitis and activated fibroblasts, examining specific markers and microbial differences between periodontitis and peri-implantitis. These insights improve our understanding of peri-implantitis pathogenesis, encouraging future research for better management and prevention strategies.

CLINICAL SIGNIFICANCE

This study identifies key insights into the pathogenesis of peri-implantitis compared to periodontitis. These findings promise to advance clinical approaches for better managing and preventing peri-implantitis, addressing its complexities and high relapse rates effectively.

Spatial transcriptomic analysis deciphers adipocyte-to-fibroblast transformation in bleomycin-induced murine skin fibrosis

BACKGROUND

Scleroderma is characterized by inflammation and fibrosis, predominantly occurring in the skin and extending to various parts of the body. The pathophysiology of scleroderma is multifaceted, with the current understanding including endothelial damage, inflammatory cell infiltration, and fibroblast activation in its progression. Nonetheless, the mechanism of cellular interactions and the precise spatial distribution of these cellular events within the fibrotic tissues remain elusive, highlighting a critical gap in our comprehensive understanding of scleroderma's pathogenesis.

METHODS

In this study, we administered bleomycin intradermally to the dorsal skin of four individual murine models. Subsequently, skin tissues were harvested at predetermined intervals for comprehensive spatial transcriptomic analysis to determine the spatial dynamics influencing scleroderma pathogenesis. To validate the possible results from bioinformatic analysis, further in vitro and in vivo experiments were conducted.

RESULTS

Analysis of the spatial transcriptome revealed significant alterations in cell clusters during the progression of scleroderma. Gene Ontology analysis identified disruptions in lipid metabolism as the disease advanced. Pseudotime analysis provided evidence for a phenotypic transition from adipocytes to fibroblasts. In vitro studies demonstrated increased expression of Col1a1 and α-SMA as the disease progressed. These fibroblasts have been identified as key contributors to the increasing inflammation. Co-culturing TGF-β induced adipocytes with RAW264.7 cells resulted in overexpression of pro-inflammatory cytokines in the RAW264.7 cells. Both in vitro and in vivo experiments confirmed adipocyte loss and fibroblast formation, with transformed fibroblasts showing pronounced pro-inflammatory characteristics, highlighting their crucial role in the disease mechanism.

CONCLUSIONS

Our study showed the spatial distribution and dynamic alterations of various cell types during scleroderma progression. Crucially, we identified the transformation of adipocytes into fibroblasts as a key factor promoting disease advancement. These emergent fibroblasts intensify inflammation, indicating that research on these cell clusters could reveal key scleroderma mechanisms and guide future therapies.

Functional gene signature offers a powerful tool for characterizing clinicopathological features and depicting tumor immune microenvironment of colorectal cancer

BACKGROUND

Colorectal cancer, a prevalent malignancy worldwide, poses a significant challenge due to the lack of effective prognostic tools. In this study, we aimed to develop a functional gene signature to stratify colorectal cancer patients into different groups with distinct characteristics, which will greatly facilitate disease prediction.

RESULTS

Patients were stratified into high- and low-risk groups using a prediction model built based on the functional gene signature. This innovative approach not only predicts clinicopathological features but also reveals tumor immune microenvironment types and responses to immunotherapy. The study reveals that patients in the high-risk group exhibit poorer pathological features, including invasion depth, lymph node metastasis, and distant metastasis, as well as unfavorable survival outcomes in terms of overall survival and disease-free survival. The underlying mechanisms for these observations are attributed to upregulated tumor-related signaling pathways, increased infiltration of pro-tumor immune cells, decreased infiltration of anti-tumor immune cells, and a lower tumor mutation burden. Consequently, patients in the high-risk group exhibit a diminished response to immunotherapy. Furthermore, the high-risk group demonstrates enrichment in extracellular matrix-related functions and significant infiltration of cancer-associated fibroblasts (CAFs). Single-cell transcriptional data analysis identifies CAFs as the primary cellular type expressing hub genes, namely ACTA2, TPM2, MYL9, and TAGLN. This finding is further validated through multiple approaches, including multiplex immunohistochemistry (mIHC), polymerase chain reaction (PCR), and western blot analysis. Notably, TPM2 emerges as a potential biomarker for identifying CAFs in colorectal cancer, distinguishing them from both colorectal cancer cell lines and normal colon epithelial cell lines. Co-culture of CAFs and colorectal cancer cells revealed that CAFs could enhance the tumorigenic biofunctions of cancer cells indirectly, which could be partially inhibited by knocking down CAF original TPM2 expression.

CONCLUSIONS

This study introduces a functional gene signature that effectively and reliably predicts clinicopathological features and the tumor immune microenvironment in colorectal cancer. Moreover, the identification of TPM2 as a potential biomarker for CAFs holds promising implications for future research and clinical applications in the field of colorectal cancer.

Facilitating integrative and personalized oncology omics analysis with UCSCXenaShiny

The continuous generation of multi-omics and phenotype data is propelling advancements in precision oncology. UCSCXenaShiny was developed as an interactive tool for exploring thousands of cancer datasets available on UCSC Xena. However, its capacity for comprehensive and personalized pan-cancer data analysis is being challenged by the growing demands. Here, we introduce UCSCXenaShiny v2, a milestone update through a variety of improvements. Firstly, by integrating multidimensional data and implementing adaptable sample settings, we create a suite of robust TPC (TCGA, PCAWG, CCLE) analysis pipelines. These pipelines empower users to conduct in-depth analyses of correlation, comparison, and survival in three modes: Individual, Pan-cancer and Batch screen. Additionally, the tool includes download interfaces that enable users to access diverse data and outcomes, several features also facilitate the joint analysis of drug sensitivity and multi-omics of cancer cell lines. UCSCXenaShiny v2 is an open-source R package and a web application, freely accessible at https://github.com/openbiox/UCSCXenaShiny .

Proteogenomic characterization of skull-base chordoma

Skull-base chordoma is a rare, aggressive bone cancer with a high recurrence rate. Despite advances in genomic studies, its molecular characteristics and effective therapies remain unknown. Here, we conduct integrative genomics, transcriptomics, proteomics, and phosphoproteomics analyses of 187 skull-base chordoma tumors. In our study, chromosome instability is identified as a prognostic predictor and potential therapeutic target. Multi-omics data reveals downstream effects of chromosome instability, with RPRD1B as a putative target for radiotherapy-resistant patients. Chromosome 1q gain, associated with chromosome instability and upregulated mitochondrial functions, lead to poorer clinical outcomes. Immune subtyping identify an immune cold subtype linked to chromosome 9p/10q loss and immune evasion. Proteomics-based classification reveals subtypes (P-II and P-III) with high chromosome instability and immune cold features, with P-II tumors showing increased invasiveness. These findings, confirmed in 17 paired samples, provide insights into the biology and treatment of skull-base chordoma.

Construction of store-operated calcium entry-related gene signature for predicting prognosis and indicates immune microenvironment infiltration in stomach adenocarcinomas

Gastric adenocarcinoma (STAD) is the most prevalent malignancy of the human digestive system and the fourth leading cause of cancer-related death. Calcium pools, especially Ca2+ entry (SOCE) for storage operations, play a crucial role in maintaining intracellular and extracellular calcium balance, influencing cell activity, and facilitating tumor progression. Nevertheless, the prognostic and immunological value of SOCE in STAD has not been systematically studied. The objective of this study was to develop a risk model for SOCE signature and to explore its correlation with clinical characteristics, prognosis, tumor microenvironment (TME), as well as response to immunotherapy, chemotherapy, and targeted drugs. We used the TCGA, GEO (GSE84437 and GSE159929), cBioPortal and TIMER databases to acquire mRNA expression data for STAD, along with patient clinical indicators, single-cell sequencing data, genomic variation information, and correlations of immune cell infiltration. An analysis of SOCE genes based on tumor vs. normal tissue comparisons, pan-cancer dimension, single-cell sequencing, DNA mutation, and copy number variation revealed that SOCE genes significantly impact the survival of STAD patients and are differentially involved in the immune response. SOCE co-expressed genes were identified by Pearson analysis, and subsequently protein-protein interaction (PPI) and gene function enrichment analysis indicated that coexpressed genes were associated with multicellular pathways. Based on TCGA and GSE84437 datasets, a multifactor Cox proportional hazard regression analysis was conducted to identify SOCE co-expressed genes associated with overall survival in STAD patients. Several mRNA prognostic genes, including PTPRJ, GPR146, LTBP3, FBLN1, EFEMP2, ADAMTS7 and LBH, were identified, which could be used as effective prognostic predictors for STAD patients. In both training and test datasets, receiver operating characteristic (ROC) curves were utilized to evaluate and illustrate the predictive capability of this characteristic in forecasting overall survival of STAD patients. The qPCR and human protein atlas (HPA) were employed to assess mRNA expression and protein levels. Furthermore, the ESTIMATE, TIMER, CIBERSORT, QUANTISEQ, MCPCOUNTER, xCell and EPIC algorithms were utilized to perform immune score and analyze immune cell infiltration. It effectively revealed the difference in prognosis and immune cell infiltration in TME between high-risk and low-risk groups based on the risk signature associated with SOCE. Notably, significant differences in tumor immune dysfunction and rejection (TIDE) scores between the two groups, suggesting that patients in the low-risk group may exhibit a more favorable response to ICIS treatment. The GDSC database and R packages for predictive analysis were utilized to analyze responses to chemotherapy and targeted drugs in high-risk and low-risk groups. In summary, the 7-gene signature associated with SOCE serves as a significant biomarker for evaluating the TME and predicting the prognosis of STAD patients. In addition, it may provide valuable insights for developing effective immunotherapy and chemotherapy regiments for patients with STAD.

Unraveling the immune landscape of lung adenocarcinoma: insights for tailoring therapeutic approaches

Lung adenocarcinoma (LUAD), a prevalent type of non-small cell lung cancer (NSCLC), was known for its diversity and intricate tumor microenvironment (TME). Comprehending the interaction among human immune-related genes (IRGs) and the TME is vital in the creation of accurate predictive models and specific treatments. We created a risk score based on IRGs and designed a nomogram to predict the prognosis of LUAD accurately. This involved a thorough examination of TME and the infiltration of immune cells in both high-risk and low-risk LUAD groups. Furthermore, the examination of the association between characteristic genes (BIRC5 and BMP5) and immune cells, along with immune checkpoints in the TME, was also conducted. The findings of our research unveiled unique immune profiles and interactions among individuals in the high- and low-risk categories, which contribute to variations in prognosis. LUAD demonstrated significant associations between BIRC5, BMP5, immune cells, and checkpoints, suggesting their involvement in disease advancement and resistance to medication. Furthermore, by correlating our findings with a multidrug database, we identified specific LUAD patient subsets that might benefit from tailored treatments. Our study establishes a groundbreaking prognostic model for LUAD, which not only underscores the importance of the immune context in LUAD but also paves the way for advancing precision medicine strategies in this complex malignancy.