Immune signature of patients with cardiovascular disease predicts increased risk for a severe course of COVID-19.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. So far, however, there are hardly any strategies for predicting the course of SARS-CoV-2 infection in CVD patients at hospital admission. Thus, we investigated whether this prediction is achievable by prospectively analysing the blood immunophenotype of 94 nonvaccinated participants, including uninfected and acutely SARS-CoV-2-infected CVD patients and healthy donors, using a 36-colour spectral flow cytometry panel. Unsupervised data analysis revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts but fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T-cell subsets. Moreover, we identified an immune signature characterised by CD161+ T cells, intermediate effector CD8+ T cells, and natural killer T (NKT) cells that is predictive for CVD patients with a severe course of COVID-19. Thus, intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.

Immune signatures predict response to house dust mite subcutaneous immunotherapy in patients with allergic rhinitis.

BACKGROUND: Identifying predictive biomarkers for allergen immunotherapy response is crucial for enhancing clinical efficacy. This study aims to identify such biomarkers in patients with allergic rhinitis (AR) undergoing subcutaneous immunotherapy (SCIT) for house dust mite allergy. METHODS: The Tongji (discovery) cohort comprised 72 AR patients who completed 1-year SCIT follow-up. Circulating T and B cell subsets were characterized using multiplexed flow cytometry before SCIT. Serum immunoglobulin levels and combined symptom and medication score (CSMS) were assessed before and after 12-month SCIT. Responders, exhibiting ≥30% CSMS improvement, were identified. The random forest algorithm and logistic regression analysis were used to select biomarkers and establish predictive models for SCIT efficacy in the Tongji cohort, which was validated in another Wisco cohort with 43 AR patients. RESULTS: Positive SCIT response correlated with higher baseline CSMS, allergen-specific IgE (sIgE)/total IgE (tIgE) ratio, and frequencies of Type 2 helper T cells, Type 2 follicular helper T (TFH2) cells, and CD23+ nonswitched memory B (BNSM) and switched memory B (BSM) cells, as well as lower follicular regulatory T (TFR) cell frequency and TFR/TFH2 cell ratio. The random forest algorithm identified sIgE/tIgE ratio, TFR/TFH2 cell ratio, and BNSM frequency as the key biomarkers discriminating responders from nonresponders in the Tongji cohort. Logistic regression analysis confirmed the predictive value of a combination model, including sIgE/tIgE ratio, TFR/TFH2 cell ratio, and CD23+ BSM frequency (AUC = 0.899 in Tongji; validated AUC = 0.893 in Wisco). CONCLUSIONS: A T- and B-cell signature combination efficiently identified SCIT responders before treatment, enabling personalized approaches for AR patients.

Exploration of the molecular characteristics and potential clinical significance of shared immune-related genes between preterm preeclampsia and term preeclampsia.

BACKGROUND: Preeclampsia is a severe obstetric disorder that significantly affects the maternal and neonatal peri-partum safety and long-term quality of life. However, there is limited research exploring the common mechanisms and potential clinical significance between early-onset preeclampsia and full-term preeclampsia from an immunological perspective. METHODS: In this study, data analysis was conducted. Initially, immune-related co-expressed genes involving both subtypes of preeclampsia were identified through Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were further employed to investigate the shared pathways regulated by immune-related genes. Binary logistic regression identified co-expressed genes with diagnostic value for preeclampsia, and a diagnostic model was constructed. Gene Set Enrichment Analysis (GSEA) predicted the potential biological functions of the selected genes. Lasso and Cox regression analyses identified genes closely associated with gestational duration, and a risk score model was established. A 4-gene feature, immune-related gene model for predicting the risk of preterm birth in preeclamptic pregnant women, was developed and validated through qPCR experiments. Immune cell infiltration analysis determined differences in immune cell infiltration between the two subtypes of preeclampsia. RESULTS: This study identified 4 immune-related co-expressed genes (CXCR6, PIK3CB, IL1RAP, and OSMR). Additionally, diagnostic and preterm birth risk prediction models for preeclampsia were constructed based on these genes. GSEA analysis suggested the involvement of these genes in the regulation of galactose metabolism, notch signaling pathway, and RIG-I like receptor signaling pathway. Immune pathway analysis indicated that the activation of T cell co-inhibition could be a potential intervention target for immunotherapy in early-onset preeclampsia. CONCLUSION: Our study provides promising insights into immunotherapy and mechanistic research for preeclampsia, discovering novel diagnostic and intervention biomarkers, and offering personalized diagnostic tools for preeclampsia.

Azathioprine therapy induces selective NK cell depletion and IFN-γ deficiency predisposing to herpesvirus reactivation.

BACKGROUND: Azathioprine is a widely prescribed drug for patients with chronic inflammatory diseases such as myasthenia gravis or organ transplant recipients. Azathioprine exerts immunosuppressive effects by inhibiting intracellular purine synthesis and reducing the numbers of circulating B and T lymphocytes. Case reports indicate increased risk for serious infections that can occur despite regular measurements of lymphocyte counts during azathioprine therapy. OBJECTIVE: We sought to comprehensively investigate therapy-associated patient risks and the underlying immune dysfunction of azathioprine use. METHODS: Peripheral blood leukocytes were analyzed using single-cell mass and spectral flow cytometry to detect specific effects of azathioprine use on the systemic immune signature. Therapy-associated clinical features were analyzed in 2 independent cohorts of myasthenia gravis patients. RESULTS: Azathioprine therapy selectively induced pronounced CD56dimCD16+ natural killer cell depletion and concomitant IFN-γ deficiency. Cytokine profiling revealed a specific contraction of classical TH1 cells during azathioprine treatment. We further observed an increased occurrence of reactivation of endogenous latent herpesviruses in the azathioprine-treated group versus in patients with myasthenia gravis who were not receiving immunomodulatory treatment; this increased occurrence was validated in an independent cohort. CONCLUSION: Our study highlights the risk of development of adverse events during azathioprine therapy and suggests that natural killer cell monitoring could be valuable in clinical practice.

The Mutational, Prognostic, and Therapeutic Landscape of Neuroendocrine Neoplasms.

BACKGROUND: Neuroendocrine neoplasms (NENs) represent clinically and genetically heterogeneous malignancies, thus a comprehensive understanding of underlying molecular characteristics, prognostic signatures, and potential therapeutic targets is urgently needed. METHODS: Next-generation sequencing (NGS) and immunohistochemistry were applied to acquire genomic and immune profiles of NENs from 47 patients. RESULTS: Difference was distinguished based on differentiation grade and primary localization. Poorly differentiated neuroendocrine carcinomas (NECs) and well-differentiated neuroendocrine tumors (NETs) harbored distinct molecular features; we observed that tumor mutational burden (TMB) and tumor neoantigen burden (TNB) were significantly higher in NECs versus NETs. Notably, we identified a 7-gene panel (MLH3, NACA, NOTCH1, NPAP1, RANBP17, TSC2, and ZFHX4) as a novel prognostic signature in NENs; patients who carried mutations in any of the 7 genes exhibited significantly poorer survival. Furthermore, loss of heterozygosity (LOH) and germline homogeneity in human leukocyte antigen (HLA) are common in NENs, accounting for 39% and 36%, respectively. Notably, HLA LOH was an important prognostic biomarker for a subgroup of NEN patients. Finally, we analyzed clinically actionable targets in NENs, revealing that TMB high (TMB-H) or gene mutations in TP53, KRAS, and HRAS were the most frequently observed therapeutic indicators, which granted eligibility to immune checkpoint blockade (ICB) and targeted therapy. CONCLUSION: Our study revealed heterogeneity of NENs, and identified novel prognostic signatures and potential therapeutic targets, which directing improvements of clinical management for NEN patients in the foreseeable future.

Cross-platform comparison of immune signatures in immunotherapy-treated patients with advanced melanoma using a rank-based scoring approach.

BACKGROUND: Gene expression profiling is increasingly being utilised as a diagnostic, prognostic and predictive tool for managing cancer patients. Single-sample scoring approach has been developed to alleviate instability of signature scores due to variations from sample composition. However, it is a challenge to achieve comparable signature scores across different expressional platforms. METHODS: The pre-treatment biopsies from a total of 158 patients, who have received single-agent anti-PD-1 (n = 84) or anti-PD-1 + anti-CTLA-4 therapy (n = 74), were performed using NanoString PanCancer IO360 Panel. Multiple immune-related signature scores were measured from a single-sample rank-based scoring approach, singscore. We assessed the reproducibility and the performance in reporting immune profile of singscore based on NanoString assay in advance melanoma. To conduct cross-platform analyses, singscores between the immune profiles of NanoString assay and the previous orthogonal whole transcriptome sequencing (WTS) data were compared through linear regression and cross-platform prediction. RESULTS: singscore-derived signature scores reported significantly high scores in responders in multiple PD-1, MHC-1-, CD8 T-cell-, antigen presentation-, cytokine- and chemokine-related signatures. We found that singscore provided stable and reproducible signature scores among the repeats in different batches and cross-sample normalisations. The cross-platform comparisons confirmed that singscores derived via NanoString and WTS were comparable. When singscore of WTS generated by the overlapping genes to the NanoString gene set, the signatures generated highly correlated cross-platform scores (Spearman correlation interquartile range (IQR) [0.88, 0.92] and r2 IQR [0.77, 0.81]) and better prediction on cross-platform response (AUC = 86.3%). The model suggested that Tumour Inflammation Signature (TIS) and Personalised Immunotherapy Platform (PIP) PD-1 are informative signatures for predicting immunotherapy-response outcomes in advanced melanoma patients treated with anti-PD-1-based therapies. CONCLUSIONS: Overall, the outcome of this study confirms that singscore based on NanoString data is a feasible approach to produce reliable signature scores for determining patients' immune profiles and the potential clinical utility in biomarker implementation, as well as to conduct cross-platform comparisons, such as WTS.

Immune-related gene expression signatures: a step forward in the stratification of patients with ovarian clear cell carcinoma†.

Clear cell carcinoma of the ovary (CCC) is one of the five major histological types of ovarian cancer and presents specific clinicopathological features, such as a higher prevalence in the Asian population and a poor response to conventional chemotherapy. In a recent publication in The Journal of Pathology, Heong, Tan, Miwa et al demonstrated the heterogeneity of the immune landscape of CCC. They reported the immune signatures observed in a large cohort of CCC, including tumours from both Asian and Caucasian women. The authors analysed three cohorts from Europe, Japan, and Singapore, with a total of 246 tumours, and evaluated 730 immune-related genes using NanoString technology. The study revealed four main transcriptional subtypes characterised by the expression of specific sets of genes: PD1-high (11%), CTLA4-high (29%), antigen-presentation (42%), and a pro-angiogenic subtype (18%). The two main conclusions of the study were: (1) that CCCs in women of Asian and Caucasian descent share significant molecular similarities, since all four molecular signatures are present in all the cohorts analysed, without any evident differences in frequency; and (2) that the PD1-high and CTLA4-high subtypes were associated with worse clinical outcomes and may be useful when stratifying treatment in early-stage tumours. The immune signature could represent a promising biomarker of immunotherapy response if future prospective studies confirm it. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Plasma Proteomics Unveil Novel Immune Signatures and Biomarkers upon SARS-CoV-2 Infection.

Several elements have an impact on COVID-19, including comorbidities, age and sex. To determine the protein profile changes in peripheral blood caused by a SARS-CoV-2 infection, a proximity extension assay was used to quantify 1387 proteins in plasma samples among 28 Finnish patients with COVID-19 with and without comorbidities and their controls. Key immune signatures, including CD4 and CD28, were changed in patients with comorbidities. Importantly, several unreported elevated proteins in patients with COVID-19, such as RBP2 and BST2, which show anti-microbial activity, along with proteins involved in extracellular matrix remodeling, including MATN2 and COL6A3, were identified. RNF41 was downregulated in patients compared to healthy controls. Our study demonstrates that SARS-CoV-2 infection causes distinct plasma protein changes in the presence of comorbidities despite the interpatient heterogeneity, and several novel potential biomarkers associated with a SARS-CoV-2 infection alone and in the presence of comorbidities were identified. Protein changes linked to the generation of SARS-CoV-2-specific antibodies, long-term effects and potential association with post-COVID-19 condition were revealed. Further study to characterize the identified plasma protein changes from larger cohorts with more diverse ethnicities of patients with COVID-19 combined with functional studies will facilitate the identification of novel diagnostic, prognostic biomarkers and potential therapeutic targets for patients with COVID-19.

Identification and validation of an immune-relevant risk signature predicting survival outcome and immune infiltration in uveal melanoma.

PURPOSE: The current study aimed to reveal a novel immune-related signature to evaluate immune infiltration status and the survival outcome for patients with uveal melanoma (UM). METHODS: Based on 80 UM samples from the Cancer Genome Atlas, the transcriptome gene expression and clinical characteristics were analyzed to identify immune-related genes that contributed most to prognosis based on LASSO Cox regression. By combining the gene expression level with the corresponding regression coefficient, a risk score was calculated and all patients were divided into high- and low-risk groups. Survival, tumor-infiltrating immune cell abundance, dysregulated signaling pathways, immunophenoscore and tumor mutation burden were compared between two groups. Validation of the risk signature was performed in GSE22138 and GSE44295 cohort. For evaluating the immunotherapy efficacy, 348 advanced urothelial cancer patients treated with immune checkpoint inhibitor (ICI) were used for external validation. RESULTS: Nine immune-related prognostic genes were identified under the LASSO Cox regression in the TCGA cohort; they are ACKR2, AREG, CCL5, CLEC11A, IGKV1-33, IL36B, NROB1, TRAV8-4 and TRBV28. Better prognosis, elevated immune cell infiltration, decreased immune-suppressive cell infiltration, immune response-related pathways and higher immunophenoscore were found in low-risk patients, with better ICI treatment response rate. CONCLUSION: The identified immune risk signature was demonstrated to be associated with the favorable immune infiltration, prognosis and immunotherapeutic efficacy, which may provide clues for survival evaluation and immune treatment.

An immune-related prognostic signature for thyroid carcinoma to predict survival and response to immune checkpoint inhibitors.

Thyroid carcinoma (THCA) is the most common endocrine malignancy, and its incidence is increasing worldwide. Several studies have explored whether the tumor immune microenvironment and immune-related genes (IRGs) influence the prognosis of patients with THCA and can be used to predict the response to immune checkpoint inhibitors (ICIs). We developed an IRG prognostic/risk signature using a bioinformatics method, and its predictive capacity was validated in patients in the test set and the total set. Subsequently, we analyzed the correlation between this IRG prognostic signature and tumor-infiltrating immune cells, tumor mutation burden (TMB), and immune checkpoint protein expression in patients with THCA. With a multivariate analysis, the IRG prognostic signature, which comprised eight IRGs, was identified as an independent prognostic factor. High-risk patients had poor overall survival compared with low-risk patients. Plasma cells, monocytes, and dendritic cells infiltrated differently according to the IRG prognostic signature. The low-risk group had a higher TMB and immunophenoscore (IPS), which indicated a better response to ICIs. The qRT-PCR validated eight IRGs with differential expression in thyroid cancer and normal tissues. We conclude that the IRG prognostic signature may be a useful tool to predict survival and response to ICIs. However, further testing is required to assess the predictive capacity of this IRG prognostic signature.

Genomic correlates of programmed cell death ligand 1 (PD-L1) expression in Chinese lung adenocarcinoma patients.

BACKGROUND: Although PD-L1 expression is a crucial predictive biomarker for immunotherapy, it can be influenced by many factors. METHODS: A total of 248 Chinese patients with lung adenocarcinoma was retrospectively identified. Data for clinical features, gene alternations, signaling pathways and immune signatures was analyzed among negative expression group (TPS < 1%, n = 124), intermediate expression group (1% ≤ TPS < 50%, n = 93), and high expression group (TPS ≥ 50%, n = 38). Clinical outcomes among different expression groups were also evaluated from public database. RESULTS: Firstly, high tumor mutation burden was significantly associated with high PD-L1 expression in these Chinese patients with lung adenocarcinoma. In addition, gene alternations including TP53, PRKDC, KMT2D, TET1 and SETD2 apparently occurred in high PD-L1 expression group. Moreover, pathway analysis showed that mutations involving in DDR pathway, TP53 pathway, cell-cycle pathway and NOTCH pathway were obviously varied among three PD-L1 expression groups. Besides, most of patients in high PD-L1 expression group from TCGA database were determined as high-grade immune subtypes (C2-C4), showing significant higher proportions of IFN-gamma, CD8+ T-cells, NK cells, NK CD56 dim cells, Th1 cells, Th2 cells (P < 0.0001). Moreover, SETD2 mutation slightly correlated with overall survival from MSKCC cohort (HR 1.92 [95%CI 0.90-4.10], P = 0.085), and the percentage of IFN-gamma was significantly higher in SETD2 mutant group than in wild-type group (P < 0.01). CONCLUSIONS: This study illustrated in-depth genomic correlates of PD-L1 expression in Chinese lung adenocarcinoma patients and relevant immune signatures from public database, which might interpret more potential molecular mechanisms for immunotherapy in NSCLC.

Immune signature as a potential marker for predicting response to immunotherapy in obesity-associated colorectal cancer.

BACKGROUND AND AIM: It remains unclear whether immunotherapy, which is not generally considered for microsatellite stable (MSS) colorectal cancer (CRC), can be used to effectively treat select CRC patients. We investigated the feasibility of obesity-associated MSS CRC patients for immunotherapy based on genomic alterations. METHODS: We evaluated differences in genomic alteration types and immune signatures between obese and non-obese patients with MSS CRC. We performed genomic analyses using 434 CRC patients from The Cancer Genome Atlas (TCGA). Patients with MSS CRC were stratified into subgroups based on their BMI and numbers of nonsynonymous single nucleotide variants (nsSNVs) and frameshift insertions and deletions (fs INDELs) using machine learning. RESULTS: The obese subgroup showed higher incidences of single nucleotide variants (SNV) and insertions and deletions (INDELs) in comparison with healthy weight patients with MSS CRC. The subgroup, who had higher numbers of nsSNVs and fs INDLEs, exhibited increased immune signatures, increased number of SNV-derived neoantigens, and had up-regulated two immune checkpoint genes in comparison with healthy weight patients with MSS CRC, reflecting interactions between the cancer genome and immune system. CONCLUSIONS: This study suggests that immunotherapy may be suitable for some obesity-associated CRC patients.

Screening potential immune signatures for early-stage basal-like/triple-negative breast cancer.

BACKGROUND: Breast cancer (BC) is a highly heterogeneous disease. Among the BC molecular subtypes, basal-like/triple-negative BC (TNBC) is characterized by a high propensity for relatively early metastases and a lack of available endocrine and targeted therapies. Therefore, this study aimed to discover potential signatures for predicting the immune response in early-stage basal-like/triple-negative BC. METHOD: A total of 86 cases of early-stage TNBC from the TCGA and 459 cases of normal breast tissue from GTEx were enrolled and analyzed to screen out differentially expressed genes (DEGs). Then, the prognostic effect and tumor immune cell infiltration relationship with the basal-like-specific DEGs were also evaluated. RESULTS: A total of 1556 DEGs, including 929 upregulated genes and 627 downregulated genes, were screened in early-stage basal-like BC. Two prognosis-associated DEGs, GAL and TTC36, were finally found to be basal-like BC specific. However, only GAL was significantly correlated with tumor immune-infiltrating cells, especially CD8+ T cells. The expressions of GAL and TTC36 were revalidated by using the GEO dataset. CONCLUSION: GAL might be an immune signature for the response to immune checkpoint therapy in early basal-like/triple-negative BC.

Exploration of the molecular characteristics of the tumor-immune interaction and the development of an individualized immune prognostic signature for neuroblastoma.

Neuroblastoma (NBL) exists in a complex tumor-immune microenvironment. Immune cell infiltration and tumor-immune molecules play a critical role in tumor development and significantly impact the prognosis of patients. However, the molecular characteristics describing the NBL-immune interaction and their prognostic potential have yet to be investigated systematically. We first employed multiple machine learning algorithms, such as Gene Sets Enrichment Analysis and cell type identification by estimating relative subsets of RNA transcripts, to identify immunophenotypes and immunological characteristics in NBL patient data from public databases and then investigated the prognostic potential and regulatory networks of identified immune-related genes involved in the NBL-immune interaction. The immunity signature combining nine immunity genes was confirmed as more effective for individual risk stratification and survival outcome prediction in NBL patients than common clinical characteristics (area under the curve [AUC] = 0.819, C-index = 0.718, p < .001). A mechanistic exploration revealed the regulatory network of molecules involved in the NBL-immune interaction. These immune molecules were also discovered to possess a significant correlation with plasma cell infiltration, MYCN status, and the level of chemokines and macrophage-related molecules (p < .001). A nomogram was constructed based on the immune signature and clinical characteristics, which showed high potential for prognosis prediction (AUC = 0.856, C-index = 0.755, p < .001). We systematically elucidated the complex regulatory mechanisms and characteristics of the molecules involved in the NBL-immune interaction and their prognostic potential, which may have important implications for further understanding the molecular mechanism of the NBL-immune interaction and identifying high-risk NBL patients to guide clinical treatment.

Immune signature-based hepatocellular carcinoma subtypes may provide novel insights into therapy and prognosis predictions.

BACKGROUND: Hepatocellular carcinoma (HCC) has a poor prognosis and has become the sixth most common malignancy worldwide due to its high incidence. Advanced approaches to therapy, including immunotherapeutic strategies, have played crucial roles in decreasing recurrence rates and improving clinical outcomes. The HCC microenvironment is important for both tumour carcinogenesis and immunogenicity, but a classification system based on immune signatures has not yet been comprehensively described. METHODS: HCC datasets from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Cancer Genome Consortium (ICGC) were used in this study. Gene set enrichment analysis (GSEA) and the ConsensusClusterPlus algorithm were used for clustering assessments. We scored immune cell infiltration and used linear discriminant analysis (LDA) to improve HCC classification accuracy. Pearson's correlation analyses were performed to assess relationships between immune signature indices and immunotherapies. In addition, weighted gene co-expression network analysis (WGCNA) was applied to identify candidate modules closely associated with immune signature indices. RESULTS: Based on 152 immune signatures from HCC samples, we identified four distinct immune subtypes (IS1, IS2, IS3, and IS4). Subtypes IS1 and IS4 had more favourable prognoses than subtypes IS2 and IS3. These four subtypes also had different immune system characteristics. The IS1 subtype had the highest scores for IFNγ, cytolysis, angiogenesis, and immune cell infiltration among all subtypes. We also identified 11 potential genes, namely, TSPAN15, TSPO, METTL9, CD276, TP53I11, SPINT1, TSPO, TRABD2B, WARS2, C9ORF116, and LBH, that may represent potential immunological biomarkers for HCC. Furthermore, real-time PCR revealed that SPINT1, CD276, TSPO, TSPAN15, METTL9, and WARS2 expression was increased in HCC cells. CONCLUSIONS: The present gene-based immune signature classification and indexing may provide novel perspectives for both HCC immunotherapy management and prognosis prediction.

Conjoint analysis of circulating tumor cells and solid tumors for exploring potential prognostic markers and constructing a robust novel predictive signature for breast cancer.

BACKGROUND: Distance metastasis is the leading cause of death for breast cancer patients, and circulating tumor cells (CTCs) play a key role in cancer metastasis. There have been few studies on CTCs at the molecular level due to their rarity, and the heterogeneity of CTCs may provide special information for solid tumor analysis. METHODS: In this study, we used the gene expression and clinical information of single-cell RNA-seq data of CTCs of breast cancer and discovered a cluster of epithelial cells that had more aggressive characteristics. The differentially expressed genes (DEGs) between the identified epithelial cells cluster and others from single-CTCs were selected for further analysis in bulk sequence data of solid breast cancers. RESULTS: Eighteen genes closely related to the specific CTC epithelial phenotype and breast cancer patient prognosis were identified. Among these 18 genes, we selected the GARS gene, which has not been studied in breast cancer, for functional research and confirmed that it may be a potential oncogene in breast cancer. A risk score was established by the 18 genes, and a high-risk score was strongly associated with a high metastasis rate and poor survival prognosis in breast cancer. The high-risk score group was related to a defective immune infiltration environment in breast cancer, and the immune checkpoint therapy response rate was lower in this group. The drug-sensitive analysis shows that the high-risk score patients may be more sensitive to AKT-mTOR and the cyclin-dependent kinase (CDK) pathways drugs than low-risk score patients. CONCLUSIONS: Our 18-gene risk score shows good prognostic and predictive values and might be a personalized prognostic marker or therapy guide marker in breast cancer patients.

The inflammation in cutaneous lichen planus is dominated by IFN-ϒ and IL-21-A basis for therapeutic JAK1 inhibition.

Cutaneous lichen planus (CLP) and psoriasis (PSO) are both common chronic inflammatory skin diseases for which development of new treatments requires the identification of key targets. While PSO is a typical Th17/IL-17-disorder, there is some evidence that Th1/IFN-É£ dominate the inflammatory process in CLP. Nonetheless, the immunopathogenesis of CLP is not fully explained and key immunological factors still have to be recognized. In this study, we compared the immune signature of CLP lesions with the well-characterized inflammation present in PSO skin. First, we analysed the histological and immunohistological characteristics of CLP and PSO. Second, we assessed the cytokine expression (IL1A, IL1B, IL4, IL6, IL8, IL10, IL17A, IL19, IL21, IL22, IL23A, IL13, IFNG, TNF, IL12A, IL12B and IL36G) of lesional skin of CLP with PSO by qPCR. Histology revealed a similar epidermal thickness in CLP and PSO. Immunohistochemically, both diseases presented with an inflammatory infiltrate mainly composed by CD3+ CD4+ T cells rather than CD3+ CD8+ . Importantly, mRNA analysis showed a distinct cytokine signature: while levels of IL12B, IL1A, IL6 and IL23 were similar between the two groups, the characteristic PSO-associated cytokines IL8, IL17A, IL22, IL19 and IL36G were expressed at very low levels in CLP. In contrast, CLP lesional skin was dominated by the expression of IFNG, IL21, IL4, IL12A and TNF. Immunohistochemistry confirmed the dominance of IL-21, IFN-É£ and also pSTAT1 in the dermal infiltrate of CLP, while IL-17A was more present in PSO. Collectively, this study improves our understanding of the immunological factors dominating CLP. The dominating cytokines and signalling proteins identified suggest that anti-cytokine therapeutics like JAK inhibitors may be beneficial in CLP.

Molecular subtyping reveals immune alterations in IDH wild-type lower-grade diffuse glioma.

Isocitrate dehydrogenase (IDH) wild-type diffuse lower-grade glioma (LGG) is usually associated with poor outcome, but there have been disputes over its clinical outcome and classification. We present here a robust gene expression-based molecular classification of IDH wild-type diffuse LGG into two subtypes with distinct biological and clinical features. A discovery cohort of 49 IDH wild-type diffuse LGGs from the Chinese Glioma Genome Atlas (CGGA) was subjected to clustering and function analysis. Seventy-three tumors from The Cancer Genome Atlas (TCGA) were used to validate our findings. Consensus clustering of transcriptional data uncovered concordant classification of two robust and prognostically significant subtypes of IDH wild-type LGG. Subtype 1, associated with poorer outcomes, was characterized by significantly higher immune and cytolytic scores, M2 macrophages, and up-regulation of immune exhaustion markers, while Subtype 2, which had elevated lymphocytes and plasma cells, showed relatively favorable survival. Somatic alteration analysis revealed that Subtype 1 showed more frequently deleted regions, such as the locus of CDKN2A/CDKN2B, DMRTA1, C9orf53, and MTAP. Furthermore, we developed and validated a five-gene signature for better application of this acquired stratification. Our data demonstrate the biological and prognostic heterogeneity within IDH wild-type diffuse LGGs and deepen our molecular understandi-g of this tumor entity. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Exploration of the relationship between tumor mutation burden and immune infiltrates in colon adenocarcinoma.

Background: Tumor mutation burden (TMB) was correlated with the immunotherapeutic response in various malignancies. We aimed to evaluate the TMB immune signature in colon adenocarcinoma (COAD). Methods: Gene expression profile, mutation and clinical data of COAD patients were obtained from The Cancer Genome Atlas (TCGA) database. The samples were divided into high and low TMB level groups to identify differentially expressed genes (DEGs). Functional enrichments analyzes were performed to identify the biological functions of the DEGs. Then, immune cell infiltration signatures were calculated by the CIBERSORT algorithm. Finally, Cox proportional hazard model was constructed to estimate the prognostic value of the identified immune-related genes. Results: Gene set enrichment analysis in the high-TMB level group showed that DEGS were enriched in immune-related pathways, such as antigen processing and presentation, Toll-like receptor signaling and natural killer cell-mediated cytotoxicity. A higher infiltration level of CD8+ T cells, CD4+ T cells, activated NK cells , M1 Macrophages and T follicular helper cells was observed in the high-TMB level group. Furthermore, a Cox regression model combined with survival analysis based on the expression level of four identified prognostic genes was constructed, validated anf revealed that higher risk-score levels conferred poor survival outcomes in COAD patients. Conclusions: Our data demonstrate that the high TMB levels are associated with an immune signature in COAD and deepen the molecular understanding of TMB function in tumor immunotherapy.

Identification of a prognostic signature of epithelial ovarian cancer based on tumor immune microenvironment exploration.

This study aims to develop an immune-related genes (IRGs) prognostic signature to stratify the epithelial ovarian cancer (EOC) patients. We identified 332 up- and 154 down-regulated EOC-specific IRGs. As a result, candidate IRGs were idendified to construct prognostic models respectivy for overall survial and progression-free survival. The risk score was validated as a risk factor for prognosis and was used to built a combined nomogram. According to the IRG-related prognostic model, EOC patients were divided into high- and low- risk group and were further explored their association with tumor immune microenvironment (TME). CIBERSORT algorithm showed higher macrophages M1 cell, T cells follicular helper cell and plasma cells infiltrating levels in the low-risk group. In addition, the low-risk group was found with higher immunophenoscore and distinct mutation signatures compared with the high-risk group. These findings may shed light on the development of novel immune biomarkers and target therapy of EOC.