[Clinical study of constructing nomogram model based on multi-dimensional clinical indicators to predict prognosis of knee osteoarthritis].

OBJECTIVE: To analyze the factors affecting the prognosis of patients with knee osteoarthritis, and to construct a nomogram prediction model in conjunction with multi-dimensional clinical indicators. METHODS: The clinical data of 234 patients with knee osteoarthritis who were treated in our hospital from January 2015 to June 2021 were retrospectively analyzed, including 126 males and 108 females；age more than 60 years old for 135 cases, age less than 60 years old for 99 cases. Lysholm knee function score was used to evaluate the prognosis of the patients, and the patients were divided into good prognosis group for 155 patients and poor prognosis group for 79 patients according to the prognosis. The clinical data of the subjects in the experimental cohort were analyzed by single factor and multiple factors. The patients were divided into experimental cohort and verification cohort, the results of the multiple factor analysis were visualized to obtain a nomogram prediction model, the receiver operating characteristic curve（ROC）, calibration curve and decision curve were used to evaluate the model's discrimination, accuracy and clinical benefit rate. RESULTS: The results of multivariate analysis showed that smoking, pre-treatment K-L grades of Ⅲ to Ⅳ, and high levels of interleukin 6 （IL-6） and matrix metallo proteinase-3 （MMP-3） were risk factors for the prognosis of patients with knee osteoarthritis. ROC test results showed that the area under the curve of the nomogram model in the experimental cohort and validation cohort was 0.806[95%CI（0.742, 0.866）] and 0.786[（95%CI（0.678, 0.893）], respectively. The results of the calibration curve showed that the Brier values of the experimental cohort and verification cohort were 0.151 points and 0.134 points, respectively. When the threshold probability value in the decision curve was set to 31%, the clinical benefit rates of the experimental cohort and validation cohort were 51% and 56%, respectively. CONCLUSION: The prognostic model of patients with knee osteoarthritis constructed based on multi-dimensional clinical data has both theoretical and practical significance, and can provide a reference for taking targeted measures to improve the prognosis of patients.

MyD88 in myofibroblasts enhances nonalcoholic fatty liver disease-related hepatocarcinogenesis via promoting macrophage M2 polarization.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is a major cause of chronic liver diseases and has emerged as the leading factor in the pathogenesis of hepatocellular carcinoma (HCC). MyD88 contributes to the development of HCC. However, the underlying mechanism by which MyD88 in myofibroblasts regulates NAFLD-associated liver cancer development remains unknown. RESULTS: Myofibroblast MyD88-deficient (SMAMyD88-/-) mice were protected from diet-induced obesity and developed fewer and smaller liver tumors. MyD88 deficiency in myofibroblasts attenuated macrophage M2 polarization and fat accumulation in HCC tissues. Mechanistically, MyD88 signaling in myofibroblasts enhanced CCL9 secretion, thereby promoting macrophage M2 polarization. This process may depend on the CCR1 receptor and STAT6/ PPARß pathway. Furthermore, liver tumor growth was attenuated in mice treated with a CCR1 inhibitor. CCLl5 (homologous protein CCL9 in humans) expression was increased in myofibroblasts of HCC and was associated with shorter survival of patients with HCC. Thus, our results indicate that MyD88 in myofibroblasts promotes NAFLD-related HCC progression and may be a promising therapeutic target for HCC treatment. CONCLUSION: This study demonstrates that MyD88 in myofibroblasts can promote nonalcoholic fatty liver disease-related hepatocarcinogenesis by enhancing macrophage M2 polarization, which might provide a potential molecular therapeutic target for HCC.

PRMT1 Inhibition Activates the Interferon Pathway to Potentiate Antitumor Immunity and Enhance Checkpoint Blockade Efficacy in Melanoma.

Despite the immense success of immune checkpoint blockade (ICB) in cancer treatment, many tumors, including melanoma, exhibit innate or adaptive resistance. Tumor-intrinsic T-cell deficiency and T-cell dysfunction have been identified as essential factors in the emergence of ICB resistance. Here, we found that protein arginine methyltransferase 1 (PRMT1) expression was inversely correlated with the number and activity of CD8+ T cells within melanoma specimen. PRMT1 deficiency or inhibition with DCPT1061 significantly restrained refractory melanoma growth and increased intratumoral CD8+ T cells in vivo. Moreover, PRMT1 deletion in melanoma cells facilitated formation of double-stranded RNA derived from endogenous retroviral elements (ERV) and stimulated an intracellular interferon response. Mechanistically, PRMT1 deficiency repressed the expression of DNA methyltransferase 1 (DNMT1) by attenuating modification of H4R3me2a and H3K27ac at enhancer regions of Dnmt1, and DNMT1 downregulation consequently activated ERV transcription and the interferon signaling. Importantly, PRMT1 inhibition with DCPT1061 synergized with PD-1 blockade to suppress tumor progression and increase the proportion of CD8+ T cells as well as IFNγ+CD8+ T cells in vivo. Together, these results reveal an unrecognized role and mechanism of PRMT1 in regulating antitumor T-cell immunity, suggesting PRMT1 inhibition as a potent strategy to increase the efficacy of ICB. SIGNIFICANCE: Targeting PRMT1 stimulates interferon signaling by increasing expression of endogenous retroviral elements and double-stranded RNA through repression of DNMT1, which induces antitumor immunity and synergizes with immunotherapy to suppress tumor progression.

Early detection of hepatocellular carcinoma via no end-repair enzymatic methylation sequencing of cell-free DNA and pre-trained neural network.

BACKGROUND: Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC. METHODS: We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth. RESULTS: NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%). CONCLUSIONS: By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace.

Comprehensive analysis of immune subtypes reveals the prognostic value of cytotoxicity and FAP+ fibroblasts in stomach adenocarcinoma.

BACKGROUND: The heterogeneity limits the effective application of immune checkpoint inhibitors for patients with stomach adenocarcinoma (STAD). Precise immunotyping can help select people who may benefit from immunotherapy and guide postoperative management by describing the characteristics of tumor microenvironment. METHODS: Gene expression profiles and clinical information of patients were collected from ACRG and TCGA-STAD datasets. The immune subtypes (ISs) were identified by consensus clustering analysis. The tumor immune microenvironments (TIME) of each IS were characterized using a series of immunogenomics methods and further confirmed by multiplex immunohistochemistry (mIHC) staining in clinical samples. Two online datasets and one in-house dataset were utilized to construct and validate a prognostic immune-related gene (IRG) signature. RESULTS: STAD patients were stratified into five reproducible ISs. IS1 (immune deserve subtype) had low immune infiltration and the highest degree of HER2 gene mutation. With abundant CD8+ T cells infiltration and activated cytotoxicity reaction, patients in the IS2 (immune-activated subtype) had the best overall survival (OS). IS3 and IS4 subtypes were both in the reactive stroma state and indicated the worst prognosis. However, IS3 (immune-inhibited subtype) was characterized by enrichment of FAP+ fibroblasts and upregulated TGF-ß signaling pathway, while IS4 (activated stroma subtype) was characterized by enrichment of ACTA2+ fibroblasts. In addition, mIHC staining confirmed that TGF-ß upregulated FAP+ fibroblasts were independent risk factor of OS. IS5 (chronic inflammation subtype) displayed moderate immune cells infiltration and had a relatively good survival. Lastly, we developed a nine-IRG signature model with a robust performance on overall survival prognostication. CONCLUSIONS: The immunotyping is indicative for characterize the TIME heterogeneity and the prediction of tumor prognosis for STADs, which may provide valuable stratification for the design of future immunotherapy.

The immune subtypes and landscape of sarcomas.

BACKGROUND: Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suitable patients from an extremely heterogeneous population. RESULTS: By performing consensus clustering analysis of the gene expression profiles of 538 patients with sarcomas in online databases, we stratified sarcomas into three IMSs characterized by different immune cell features, tumor mutational burdens (TMBs), gene mutations, and clinical outcomes. IMS1 showed an immune "hot" and immunosuppressive phenotype, the highest frequencies of CSMD3 mutation but the lowest frequencies of HMCN1 and LAMA2 mutations; these patients had the worst progression-free survival (PFS). IMS2 was defined by a high TMB and more gene mutations, but had the lowest frequency of MND1 mutations. IMS3 displayed the highest MDN1 expression level and an immune "cold" phenotype, these patients had the worst PFS. Each subtype was associated with different expression levels of immunogenic cell death modulators and immune checkpoints. Moreover, we applied graph learning-based dimensionality reduction to the immune landscape and identified significant intra-cluster heterogeneity within each IMS. Finally, we developed and validated an immune gene signature with good prognostic performance. CONCLUSIONS: Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies.

Classification of colon adenocarcinoma based on immunological characterizations: Implications for prognosis and immunotherapy.

Accurate immune molecular typing is pivotal for screening out patients with colon adenocarcinoma (COAD) who may benefit from immunotherapy and whose tumor microenvironment (TME) was needed for reprogramming to beneficial immune-mediated responses. However, little is known about the immune characteristic of COAD. Here, by calculating the enrichment score of immune characteristics in three online COAD datasets (TCGA-COAD, GSE39582, and GSE17538), we identified 17 prognostic-related immune characteristics that overlapped in at least two datasets. We determined that COADs could be stratified into three immune subtypes (IS1-IS3), based on consensus clustering of these 17 immune characteristics. Each of the three ISs was associated with distinct clinicopathological characteristics, genetic aberrations, tumor-infiltrating immune cell composition, immunophenotyping (immune "hot" and immune "cold"), and cytokine profiles, as well as different clinical outcomes and immunotherapy/therapeutic response. Patients with the IS1 tumor had high immune infiltration but immunosuppressive phenotype, IS3 tumor is an immune "hot" phenotype, whereas those with the IS2 tumor had an immune "cold" phenotype. We further verified the distinct immune phenotype of IS1 and IS3 by an in-house COAD cohort. We propose that the immune subtyping can be utilized to identify COAD patients who will be affected by the tumor immune microenvironment. Furthermore, the ISs may provide a guide for personalized cancer immunotherapy and for tumor prognosis.

LiBis: an ultrasensitive alignment augmentation for low-input bisulfite sequencing.

The cell-free DNA (cfDNA) methylation profile in liquid biopsy has been utilized to diagnose early-stage disease and estimate therapy response. However, typical clinical procedures are capable of purifying only very small amounts of cfDNA. Whole-genome bisulfite sequencing (WGBS) is the gold standard for measuring DNA methylation; however, WGBS using small amounts of fragmented DNA introduces a critical challenge for data analysis, namely a low-mapping ratio. The resulting low sequencing depth and low coverage of CpG sites genome-wide is a bottleneck for the clinical application of cfDNA-based WGBS assays. We developed LiBis (Low-input Bisulfite Sequencing), a novel method for low-input WGBS data alignment. By dynamically clipping initially unmapped reads and remapping clipped fragments, we judiciously rescued those reads and uniquely aligned them to the genome. By substantially increasing the mapping ratio by up to 88%, LiBis dramatically improved the number of informative CpGs and the precision in quantifying the methylation status of individual CpG sites. LiBis significantly improved the cost efficiency of low-input WGBS experiments by dynamically removing contamination introduced by random priming. The high sensitivity and cost effectiveness afforded by LiBis for low-input samples will allow the discovery of genetic and epigenetic features suitable for downstream analysis and biomarker identification using liquid biopsy.

PRMT6 increases cytoplasmic localization of p21CDKN1A in cancer cells through arginine methylation and makes more resistant to cytotoxic agents.

p21(CDKN1A) is known as a potent inhibitor of cyclin-dependent kinase (CDK), which regulates cell cycle in response to various stimuli, including DNA damage, on the p53-dependent manner. Here we demonstrate that protein arginine methyltransferase 6 (PRMT6) methylates p21 at arginine 156 and promotes phosphorylation of threonine 145 on p21, resulting in the increase of cytoplasmic localization of p21. The cytoplasmic presence of p21 makes cancer cells more resistant to cytotoxic agents. Our results indicate that PRMT6 appears to be one of the key proteins to dysregulate p21 functions in human cancer, and targeting this pathway may be an appropriate strategy for development of anticancer drugs.

Dysregulation of AKT Pathway by SMYD2-Mediated Lysine Methylation on PTEN.

Phosphatase and tensin homologue (PTEN), one of the well-characterized tumor suppressor proteins, counteracts the phosphatidylinositol 3-kinase-AKT pathway through its unique lipid phosphatase activity. The functions of PTEN are regulated by a variety of posttranslational modifications such as acetylation, oxidation, ubiquitylation, phosphorylation, and SUMOylation. However, methylation of PTEN has not been reported so far. In this study, we demonstrated that the oncogenic protein lysine methyltransferase SET and MYND domain containing 2 (SMYD2) methylates PTEN at lysine 313 in vitro and in vivo. Knockdown of SMYD2 suppressed the cell growth of breast cancer cells and attenuated phosphorylation levels of AKT, indicating that SMYD2-mediated methylation negatively regulates PTEN tumor suppressor activity and results in activation of the phosphatidylinositol 3-kinase-AKT pathway. Furthermore, PTEN protein with lysine 313 substitution diminished phosphorylation of PTEN at serine 380, which is known to inactivate tumor suppressor functions of PTEN. Taken together, our findings unveil a novel mechanism of PTEN dysregulation regulated by lysine methylation in human cancer.

Late Cornified Envelope Group I, a novel target of p53, regulates PRMT5 activity.

p53 is one of the most important tumor suppressor genes involved in human carcinogenesis. Although downstream targets of p53 and their biologic functions in cancer cells have been extensively investigated, it is still far from the full understanding. Here, we demonstrate that Late Cornified Envelope Group I (LCE1) genes, which are located in the LCE gene clusters encoding multiple well-conserved stratum-corneum proteins, are novel downstream targets of p53. Exogenous p53 overexpression using an adenoviral vector system significantly enhanced the expression of LCE1 cluster genes. We also observed induction of LCE1 expressions by DNA damage, which was caused by treatment with adriamycin or UV irradiation in a wild-type p53-dependent manner. Concordantly, the induction of LCE1 by DNA damage was significantly attenuated by the knockdown of p53. Among predicted p53-binding sites within the LCE1 gene cluster, we confirmed one site to be a p53-enhancer sequence by reporter assays. Furthermore, we identified LCE1 to interact with protein arginine methyltransferase 5 (PRMT5). Knockdown of LCE1 by specific small interfering RNAs significantly increased the symmetric dimethylation of histone H3 arginine 8, a substrate of PRMT5, and overexpression of LCE1F remarkably decreased its methylation level. Our data suggest that LCE1 is a novel p53 downstream target that can be directly transactivated by p53 and is likely to have tumor suppressor functions through modulation of the PRMT5 activity.

Downregulation of the tumor suppressor HSPB7, involved in the p53 pathway, in renal cell carcinoma by hypermethylation.

In order to identify genes involved in renal carcinogenesis, we analyzed the expression profile of renal cell carcinomas (RCCs) using microarrays consisting of 27,648 cDNA or ESTs, and found a small heat shock protein, HSPB7, to be significantly and commonly downregulated in RCC. Subsequent quantitative PCR (qPCR) and immunohistochemical (IHC) analyses confirmed the downregulation of HSPB7 in RCC tissues and cancer cell lines in both transcriptional and protein levels. Bisulfite sequencing of a genomic region of HSPB7 detected DNA hypermethylation of some segments of HSPB7 in RCC cells and concordantly 5-aza-2'-deoxycytidine (5-Aza-dC) treatment of cancer cells restored HSPB7 expression significantly. Ectopic introduction of HSPB7 in five RCC cell lines remarkably suppressed cancer cell growth. Interestingly, we found that HSPB7 expression could be induced by p53 in a dose-dependent manner, indicating that this gene functions in the p53 pathway. Our results imply that HSBP7 is likely to be a tumor suppressor gene regulated by p53 and its downregulation by hypermethylation may play a critical role in renal carcinogenesis.

Soluble MICA and a MICA variation as possible prognostic biomarkers for HBV-induced hepatocellular carcinoma.

MHC class I polypeptide-related chain A (MICA) molecule is induced in response to viral infection and various types of stress. We recently reported that a single nucleotide polymorphism (SNP) rs2596542 located in the MICA promoter region was significantly associated with the risk for hepatitis C virus (HCV)-induced hepatocellular carcinoma (HCC) and also with serum levels of soluble MICA (sMICA). In this study, we focused on the possible involvement of MICA in liver carcinogenesis related to hepatitis B virus (HBV) infection and examined correlation between the MICA polymorphism and the serum sMICA levels in HBV-induced HCC patients. The genetic association analysis revealed a nominal association with an SNP rs2596542; a G allele was considered to increase the risk of HBV-induced HCC (P = 0.029 with odds ratio of 1.19). We also found a significant elevation of sMICA in HBV-induced HCC cases. Moreover, a G allele of SNP rs2596542 was significantly associated with increased sMICA levels (P = 0.009). Interestingly, HCC patients with the high serum level of sMICA (>5 pg/ml) exhibited poorer prognosis than those with the low serum level of sMICA (≤5 pg/ml) (P = 0.008). Thus, our results highlight the importance of MICA genetic variations and the significance of sMICA as a predictive biomarker for HBV-induced HCC.