High Expression of Triggering Receptor Expressed on Myeloid Cells 1 Predicts Poor Prognosis in Glioblastoma

Background

Glioblastoma (GBM) is a highly malignant tumor with poor prognosis, and new treatment strategies are urgently needed. Currently, the role of triggering receptor expressed on myeloid cells 1 (TREM-1) in tumors has been studied, but the role of TREM-1 in GBM remains unclear.

Methods

Immunohistochemical staining for TREM-1 was performed in 91 patients diagnosed with GBM. Clinicopathological characteristics and survival times were recorded. TREM-1 expression and its effect on prognosis were analyzed using online Gene Expression Profiling Interactive Analysis (GEPIA), The Cancer Genome Atlas (TCGA), and Chinese Glioma Genome Atlas (CGGA) databases. The expression profile of TCGA-GBM cohort was used to perform functional enrichment analysis. The CIBERSORT method and Tumor Immune Estimation Resource (TIMER) database were used to estimate the tumor-infiltrating immune cells (TIICs). The ESTIMATE algorithm was used to estimate the immune-stromal scores. Finally, the relationships of TREM-1 with TIICs, immune-stromal score, and immune checkpoint genes (ICGs) were analyzed.

Results

The expression of TREM-1 was upregulated in GBM, and high TREM-1 expression predicted a poor prognosis. TREM-1, surgical resection, postoperative radiotherapy, and temozolomide (TMZ) chemotherapy were associated with the survival time of patients with GBM, but only surgical resection and TREM-1 expression were independent prognostic factors. GBM with high TREM-1 expression exhibited increased neutrophil and macrophage infiltration. TREM-1 was positively associated with the immune-stromal score and multiple ICGs, and most of which were involved in immunosuppressive responses.

Conclusion

The present study revealed that high expression of TREM-1 in GBM is an independent poor prognosis factor and that TREM-1 is associated with the immunosuppressive microenvironment. Thus, blocking TREM-1 may be a strategy for enhancing the GBM immune response.

LINC00426 is a potential immune phenotype-related biomarker and an overall survival predictor in PAM50 luminal B breast cancer

Background: Breast cancer (BRCA) represents the most frequent diagnosed malignancy in women worldwide. Despite treatment advances, BRCAs eventually develop resistance to targeted therapies, resulting in poor prognosis. The identification of new biomarkers, like immune-related long non-coding RNAs (lncRNAs), could contribute to the clinical management of BRCA patients. In this report, we evaluated the LINC00426 expression in PAM50 BRCA subtypes from two clinical independent cohorts (BRCA-TCGA and GEO-GSE96058 datasets). Methods and results: Using Cox regression models and Kaplan-Meier survival analyses, we identified that LINC00426 expression was a consistent overall survival (OS) predictor in luminal B (LB) BRCA patients. Subsequently, differential gene expression and gene set enrichment analyses identified that LINC00426 expression was associated with different immune-related and cancer-related pathways and processes in LB BRCA. Additionally, the LINC00426 expression was correlated with the infiltration level of diverse immune cell populations, alongside immune checkpoint and cytolytic activity-related gene expression. Conclusion: This evidence suggests that LINC00426 is a potential biomarker of immune phenotype and an OS predictor in PAM50 LB BRCA.

Immune checkpoints expression patterns in early-stage triple-negative breast cancer predict prognosis and remodel the tumor immune microenvironment

Background

Currently, targeting immune checkpoint molecules holds great promise for triple-negative breast cancer (TNBC). However, the expression landscape of immune checkpoint genes (ICGs) in TNBC remains largely unknown.

Method

Herein, we systematically investigated the ICGs expression patterns in 422 TNBC samples. We evaluated the ICGs molecular typing based on the ICGs expression profile and explored the associations between ICGs molecular subtypes and tumor immune characteristics, clinical significance, and response to immune checkpoint inhibitors (ICIs).

Results

Two ICGs clusters and two ICGs-related gene clusters were determined, which were involved in different survival outcomes, biological roles and infiltration levels of immune cells. We established a quantification system ICGs riskscore (named IRS) to assess the ICGs expression patterns for individuals. TNBC patients with lower IRS were characterized by increased immune cell infiltration, favorable clinical outcomes and high sensitivity to ICIs therapy. We also developed a nomogram model combining clinicopathological variables to predict overall survival in TNBC. Genomic feature analysis revealed that high IRS group presented an increased tumor mutation burden compared with the low IRS group.

Conclusion

Collectively, dissecting the ICGs expression patterns not only provides a new insight into TNBC subtypes but also deepens the understanding of ICGs in the tumor immune microenvironment.

Human papillomavirus infection can alter the level of tumour stemness and T cell infiltration in patients with head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) usually has a poor prognosis and is associated with a high mortality rate. Its etiology is mainly the result from long-term exposure to either alcohol, tobacco or human papillomavirus (HPV) infection or a combination of these insults. However, HNSCC patients with HPV have been found to show a survival advantage over those without the virus, but the mechanism that confers this advantage is unclear. Due to the large number of HPV-independent HNSCC cases, there is a possibility that the difference in prognosis between HPV-positive (HPV⁺) and negative (HPV^-) patients is due to different carcinogens. To clarify this, we used scRNA data and viral tracking methods in order to identify HPV⁺ and HPV^- cells in the tumour tissues of patients infected with HPV. By comparing HPV⁺ and HPV^- malignant cells, we found a higher level of tumour stemness in HPV^- tumour cells. Using tumour stemness-related genes, we established a six-gene prognostic signature that was used to divide the patients into low- and high-risk groups. It was found that HPV patients who were at low-risk of contracting HNSCC had a higher number of CD8⁺ T-cells as well as a higher expression of immune checkpoint molecules. Correspondingly, we found that HPV⁺ tumour cells expressed higher levels of CCL4, and these were highly correlated with CD8⁺ T cells infiltration and immune checkpoint molecules. These data suggest that the stemness features of tumour cells are not only associated with the prognostic risk, but that it could also affect the immune cell interactions and associated signalling pathways.

A Case Report on Longitudinal Collection of Tumour Biopsies for Gene Expression-Based Tumour Microenvironment Analysis from Pancreatic Cancer Patients Treated with Endoscopic Ultrasound Guided Radiofrequency Ablation

BACKGROUND

Most patients with pancreatic ductal adenocarcinoma (PDAC) are metastatic at presentation with dismal prognosis warranting improved systemic therapy options. Longitudinal sampling for the assessment of treatment response poses a challenge for validating novel therapies. In this case study, we evaluate the feasibility of collecting endoscopic ultrasound (EUS)-guided longitudinal fine-needle aspiration biopsies (FNABs) from two PDAC patients and conduct gene expression studies associated with tumour microenvironment changes associated with radiofrequency ablation (RFA).

METHODS

EUS-guided serial/longitudinal FNABs of tumour were collected before and after treatment from two stage III inoperable gemcitabine-treated PDAC patients treated with targeted RFA three times. Biopsies were analysed using a custom NanoString panel (144 genes) consisting of cancer and cancer-associated fibroblast (CAFs) subtypes and immune changes. CAF culture was established from one FNAB and characterised by immunofluorescence and immunoblotting.

RESULTS

Two-course RFA led to the upregulation of the CD1E gene (involved in antigen presentation) in both patients 1 and 2 (4.5 and 3.9-fold changes) compared to baseline. Patient 1 showed increased T cell genes (CD4-8.7-fold change, CD8-35.7-fold change), cytolytic function (6.4-fold change) and inflammatory response (8-fold change). A greater than 2-fold upregulation of immune checkpoint genes was observed post-second RFA in both patients. Further, two-course RFA led to increased PDGFRα (4.5-fold change) and CAF subtypes B and C genes in patient 1 and subtypes A, B and D genes in patient 2. Patient 2-derived CAFs post-first RFA showed expression of PDGFRα, POSTN and MYH11 proteins. Finally, RFA led to the downregulation of classical PDAC subtype-specific genes in both patients.

CONCLUSIONS

This case study suggests longitudinal EUS-FNAB as a potential resource to study tumour and microenvironmental changes associated with RFA treatment. A large sample size is required in the future to assess the efficacy and safety of the treatment and perform comprehensive statistical analysis of EUS-RFA-based molecular changes in PDAC.

Circulating EVs long RNA-based subtyping and deconvolution enable prediction of immunogenic signatures and clinical outcome for PDAC

Identification of clinically applicable molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) is crucial to improving patient outcomes. However, the traditional tissue-dependent transcriptional subtyping strategies are invasive and not amenable to routine clinical evaluation. In this study, we developed a circulating extracellular vesicle (cEV) long RNA (exLR)-based PDAC subtyping method and provided exLR-derived signatures for predicting immunogenic features and clinical outcomes in PDAC. We enrolled 426 individuals, among which 227 PDACs served as an internal cohort, 118 PDACs from two other medical centers served as an independent validation cohort, and 81 healthy individuals served as the control. ExLR sequencing was performed on all plasma samples. We found that PDAC could be categorized into three subtypes based on plasma exLR profiles. Each subpopulation showed its own molecular features and was associated with patient clinical prognosis. The immunocyte-derived cEV fractions were altered among PDAC subtypes and interconnected with tumor-infiltrating lymphocytes in cancerous tissue. Additionally, we found a significant concordance of immunoregulators between tissue and blood EVs, and we harvested potential PDAC therapeutic targets. Most importantly, we constructed a nine exLR-derived, tissue-applicable signature for prognostic assessment of PDAC. The circulating exLR-based features may offer an attractive platform for personalized treatment and predicting patient outcomes in multiple types of cancer.

Using Immune-Related Long Non-coding Ribonucleic Acids to Develop a Novel Prognosis Signature and Predict the Immune Landscape of Colon Cancer

Purpose: This study aimed to construct a novel signature to predict the survival of patients with colon cancer and the associated immune landscape, based on immune-related long noncoding ribonucleic acids (irlncRNAs).

Methods: Expression profiles of irlncRNAs in 457 patients with colon cancer were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed (DE) irlncRNAs were identified and irlncRNA pairs were recognized using Lasso regression and Cox regression analyses. Akaike information criterion (AIC) values of receiver operating characteristic (ROC) curve were calculated to identify the ideal cut-off point for dividing patients into two groups and constructing the prognosis signature. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate the expression of LINC02195 and SCARNA9 in colon cancer.

Results: We identified 22 irlncRNA pairs and patients were divided into high-risk and low-risk groups based on the calculated risk score using these 22 irlncRNA pairs. The irlncRNA pairs were significantly related to patient survival. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). The area under the curve of the signature to predict 5-year survival was 0.951. The risk score correlated with tumor stage, infiltration depth, lymph node metastasis, and distant metastasis. The risk score remained significant after univariate and multivariate Cox regression analyses. A nomogram model to predict patient survival was developed based on the results of Cox regression analysis. Immune cell infiltration status, expression of some immune checkpoint genes, and sensitivity to chemotherapeutics were also related to the risk score. The results of qRT-PCR revealed that LINC02195 and SCARNA9 were significantly upregulated in colon cancer tissues.

Conclusion: The constructed prognosis signature showed remarkable efficiency in predicting patient survival, immune cell infiltration status, expression of immune checkpoint genes, and sensitivity to chemotherapeutics.

The CXCL Family Contributes to Immunosuppressive Microenvironment in Gliomas and Assists in Gliomas Chemotherapy

Gliomas are a type of malignant central nervous system tumor with poor prognosis. Molecular biomarkers of gliomas can predict glioma patient's clinical outcome, but their limitations are also emerging. C-X-C motif chemokine ligand family plays a critical role in shaping tumor immune landscape and modulating tumor progression, but its role in gliomas is elusive. In this work, samples of TCGA were treated as the training cohort, and as for validation cohort, two CGGA datasets, four datasets from GEO database, and our own clinical samples were enrolled. Consensus clustering analysis was first introduced to classify samples based on CXCL expression profile, and the support vector machine was applied to construct the cluster model in validation cohort based on training cohort. Next, the elastic net analysis was applied to calculate the risk score of each sample based on CXCL expression. High-risk samples associated with more malignant clinical features, worse survival outcome, and more complicated immune landscape than low-risk samples. Besides, higher immune checkpoint gene expression was also noticed in high-risk samples, suggesting CXCL may participate in tumor evasion from immune surveillance. Notably, high-risk samples also manifested higher chemotherapy resistance than low-risk samples. Therefore, we predicted potential compounds that target high-risk samples. Two novel drugs, LCL-161 and ADZ5582, were firstly identified as gliomas' potential compounds, and five compounds from PubChem database were filtered out. Taken together, we constructed a prognostic model based on CXCL expression, and predicted that CXCL may affect tumor progression by modulating tumor immune landscape and tumor immune escape. Novel potential compounds were also proposed, which may improve malignant glioma prognosis.

Effects of 1p/19q Codeletion on Immune Phenotype in Low Grade Glioma

Background: Chromosome 1p/19q codeletion is one of the most important genetic alterations for low grade gliomas (LGGs), and patients with 1p/19q codeletion have significantly prolonged survival compared to those without the codeletion. And the tumor immune microenvironment also plays a vital role in the tumor progression and prognosis. However, the effect of 1p/19q codeletion on the tumor immune microenvironment in LGGs is unclear. Methods: Immune cell infiltration of 281 LGGs from The Cancer Genome Atlas (TCGA) and 543 LGGs from the Chinese Glioma Genome Atlas (CGGA) were analyzed for immune cell infiltration through three bioinformatics tools: ESTIMATE algorithm, TIMER, and xCell. The infiltrating level of immune cells and expression of immune checkpoint genes were compared between different groups classified by 1p/19q codeletion and IDH (isocitrate dehydrogenase) mutation status. The differential biological processes and signaling pathways were evaluated through Gene Set Enrichment Analysis (GSEA). Correlations were analyzed using Spearman correlation. Results: 1p/19q codeletion was associated with immune-related biological processes in LGGs. The infiltrating level of multiple kinds of immune cells and expression of immune checkpoint genes were significantly lower in 1p/19q codeletion LGGs compared to 1p/19q non-codeletion cohorts. There are 127 immune-related genes on chromosome 1p or 19q, such as TGFB1, JAK1, and CSF1. The mRNA expression of these genes was positively correlated with their DNA copy number. These genes are distributed in multiple immune categories, such as chemokines/cytokines, TGF-β family members, and TNF family members, regulating immune cell infiltration and expression of the immune checkpoint genes in tumors. Conclusion: Our results indicated that 1p/19q codeletion status is closely associated with the immunosuppressive microenvironment in LGGs. LGGs with 1p/19q codeletion display less immune cell infiltration and lower expression of immune checkpoint genes than 1p/19q non-codeletion cases. Mechanistically, this may be, at least in part, due to the deletion of copy number of immune-related genes in LGGs with 1p/19q codeletion. Our findings may be relevant to investigate immune evasion in LGGs and contribute to the design of immunotherapeutic strategies for patients with LGGs.

Identification of an immune checkpoint gene signature that accurately predicts prognosis and immunotherapy response in endometrial carcinoma

In this study, we performed a bioinformatics analysis to identify immune checkpoint genes (ICGs) associated with prognosis and the immunotherapeutic response in endometrial carcinoma (EC) patients. We classified 47 ICGs into high, medium, and low expression groups by performing RNA-sequencing data analysis of EC patient samples from The Cancer Genome Atlas (n = 521) and GSE77688 (n = 88) datasets. Univariate Cox regression analysis showed that seven ICGs (VTCN1, TNFRSF18, TNFRSF14, TNFRSF4, CD40LG, TMIGD2, and BTLA) were associated with prognosis in EC patients. Spearman correlation analysis showed that prognosis-related ICGs correlated positively with immunotherapy response factors, including tumor mutation burden (TMB), mismatch repair gene mutations, neoantigens, clinical stages, and adaptive immune resistance pathway genes. We identified a prognostic gene signature of four ICGs (IDO1, CD274, CTLA4, and TNFRSF14) that accurately predicted survival outcomes of EC patients. TIMER database and Kaplan-Meier survival analysis showed that OS among EC patients with low TNFRSF14 expression was significantly shorter than among those with high TNFRSF14 expression. In vitro experiments showed that TNFRSF14 silencing increased the migration and invasiveness of EC cells by promoting epithelial-mesenchymal transition (EMT). Collectively, these findings reveal an immune checkpoint gene signature that accurately predicts survival outcomes and immunotherapeutic responses in EC patients.

Comparative Analysis and in vitro Experiments of Signatures and Prognostic Value of Immune Checkpoint Genes in Colorectal Cancer

Purpose

Immune checkpoints, as pivotal regulators of immune escape in cancer, can motivate the emergence of immune checkpoint inhibitors (ICIs). The aim of this study is to identify the expression of the immune checkpoint genes (ICGs) in colorectal cancer (CRC) and to relate their individual as well as combined expression to prognosis and therapeutic effectiveness in CRC.

Methods

RNA expression of 47 ICGs and clinical information of CRC patients were collected from two public databases to elucidate the expression levels and prognostic values of these ICGs in CRC. Then, the Shapiro–Wilk normality test was used to determine the normality of variables. Overall survival (OS) rates of each subset were found by Kaplan–Meier method, and the statistical significance was determined by the Log rank test (p < 0.05).

Results

The expression of 13 and 9 ICGs was significantly associated with CRC prognosis in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts. A series of ICGs was found to be significantly associated with TMB, neoantigens and MMR in CRC indicating that the combination of immunotherapy treatment biomarkers and ICGs may achieve accurate prognostic stratification of CRC, and potentially identify CRC cases that might respond to checkpoint inhibitors (CPIs). The subsets of high or low PD1/PD-L1/IDO1 expression stratified by CD48 were accurately associated with prognosis in CRC. In addition, in vitro experiments confirmed that VTCN1(B7-H4)-KD increases anti-PD-L1-mediated NK cell cytotoxicity on CRC tumor cells.

Conclusion

Although the expression of a single immune-checkpoint molecule does not predict the efficacy of immunotherapy in CRC, our findings infer that subsets defined by ICGs are associated with prognosis and imply the possibility that VTCN1 and CD48 serve as new immunotherapeutic targets.

Identification and Validation of Immune-Related Gene Signature for Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma

Lung cancer is a serious malignancy, and lung adenocarcinoma (LUAD) is the most common pathological subtype. Immune-related factors play an important role in lymph node metastasis. In this study, we obtained gene expression profile data for LUAD and normal tissues from the TCGA database and analyzed their immune-related genes (IRGs), and observed that 459 IRGs were differentially expressed. Further analysis of the correlation between differentially expressed IRGs and lymph node metastasis revealed 18 lymph node metastasis-associated IRGs. In addition, we analyzed the mutations status, function and pathway enrichment of these IRGs, and regulatory networks established through TF genes. We then identified eight IRGs (IKBKB, LTBR, MIF, PPARD, PPIA, PSME3, S100A6, SEMA4B) as the best predictors by LASSO Logistic analysis and used these IRGs to construct a model to predict lymph node metastasis in patients with LUAD (AUC 0.75; 95% CI: 0.7064-0.7978), and survival analysis showed that the risk score independently affected patient survival. We validated the predictive effect of risk scores on lymph node metastasis and survival using the GEO database as a validation cohort and the results showed good agreement. In addition, the risk score was highly correlated with infiltration of immune cells (mast cells activated, macrophages M2, macrophages M0 and B cells naïve), immune and stromal scores, and immune checkpoint genes (LTBR, CD40LG, EDA2R, and TNFRSF19). We identified key IRGs associated with lymph node metastasis in LUAD and constructed a reliable risk score model, which may provide valuable biomarkers for LUAD patients and further reveal the mechanism of its occurrence.

Identification of an Immunologic Signature of Lung Adenocarcinomas Based on Genome-Wide Immune Expression Profiles

Background: Lung cancer is one of the most common types of cancer, and it has a poor prognosis. It is urgent to identify prognostic biomarkers to guide therapy. Methods: The immune gene expression profiles for patients with lung adenocarcinomas (LUADs) were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). The relationships between the expression of 45 immune checkpoint genes (ICGs) and prognosis were analyzed. Additionally, the correlations between the expression of 45 biomarkers and immunotherapy biomarkers, including tumor mutation burden (TMB), mismatch repair defects, neoantigens, and others, were identified. Ultimately, prognostic ICGs were combined to determine immune subgroups, and the prognostic differences between these subgroups were identified in LUAD. Results: A total of 11 and nine ICGs closely related to prognosis were obtained from the GEO and TCGA databases, respectively. CD200R1 expression had a significant negative correlation with TMB and neoantigens. CD200R1 showed a significant positive correlation with CD8A, CD68, and GZMB, indicating that it may cause the disordered expression of adaptive immune resistance pathway genes. Multivariable Cox regression was used to construct a signature composed of four prognostic ICGs (IDO1, CD274, CTLA4, and CD200R1): Risk Score = -0.002* IDO1+0.031* CD274-0.069* CTLA4-0.517* CD200R1. The median Risk Score was used to classify the samples for the high- and low-risk groups. We observed significant differences between groups in the training, testing, and external validation cohorts. Conclusion: Our research provides a method of integrating ICG expression profiles and clinical prognosis information to predict lung cancer prognosis, which will provide a unique reference for gene immunotherapy for LUAD.

Identification and Validation of Immune-Related Gene Signature for Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma

Lung cancer is a serious malignancy, and lung adenocarcinoma (LUAD) is the most common pathological subtype. Immune-related factors play an important role in lymph node metastasis. In this study, we obtained gene expression profile data for LUAD and normal tissues from the TCGA database and analyzed their immune-related genes (IRGs), and observed that 459 IRGs were differentially expressed. Further analysis of the correlation between differentially expressed IRGs and lymph node metastasis revealed 18 lymph node metastasis-associated IRGs. In addition, we analyzed the mutations status, function and pathway enrichment of these IRGs, and regulatory networks established through TF genes. We then identified eight IRGs (IKBKB, LTBR, MIF, PPARD, PPIA, PSME3, S100A6, SEMA4B) as the best predictors by LASSO Logistic analysis and used these IRGs to construct a model to predict lymph node metastasis in patients with LUAD (AUC 0.75; 95% CI: 0.7064-0.7978), and survival analysis showed that the risk score independently affected patient survival. We validated the predictive effect of risk scores on lymph node metastasis and survival using the GEO database as a validation cohort and the results showed good agreement. In addition, the risk score was highly correlated with infiltration of immune cells (mast cells activated, macrophages M2, macrophages M0 and B cells naïve), immune and stromal scores, and immune checkpoint genes (LTBR, CD40LG, EDA2R, and TNFRSF19). We identified key IRGs associated with lymph node metastasis in LUAD and constructed a reliable risk score model, which may provide valuable biomarkers for LUAD patients and further reveal the mechanism of its occurrence.

A prognostic risk model based on immune-related genes predicts overall survival of patients with hepatocellular carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is one of the most common heterogeneous tumors that occurs after chronic liver diseases and hepatitis virus infection. Immune-related genes (IRGs) and their ligands regulate the homeostasis of tumor microenvironment, which is essential for the treatment of HCC and its prognosis. This study aimed to investigate the clinical value of IRGs in predicting the prognosis of HCC.

METHODS

We downloaded RNA-seq data and clinical information from TCGA database. Samples were randomly divided into training cohort and testing cohort. The "limma" R package was performed to identify differentially expressed IRGs (DEIRGs) between HCC group and normal group. Prognostic DEIRGs (PDEIRGs) were obtained by univariate Cox analysis. LASSO and multivariate Cox analysis were used, and a prognostic risk model was constructed. In order to better demonstrate the clinical value of our model in predicting overall survival rate, a nomogram was constructed. To further investigate the molecular mechanism of our model, gene set enrichment analysis (GSEA) was performed.

RESULTS

Compared with the low-risk group, the high-risk group had a significantly worse prognosis. Moreover, our prognostic risk model can accurately stratify tumor grade and TNM stage. Importantly, in our model, not only immune checkpoint genes were well predicted, but also human leucocyte antigen-I molecules were revealed. GSEA suggested that "MAPK signaling pathway," "mTOR signaling pathway," "NOD like receptor signaling pathway," "Toll like receptor signaling pathway," "VEGF signaling pathway," "WNT signaling pathway" had significant correlations with the high-risk group.

CONCLUSION

Overall, our study showed that our prognostic risk model can be used to assess prognosis of HCC, which may provide a certain basis for the survival rate of patients with HCC.

Targeting FTO Suppresses Cancer Stem Cell Maintenance and Immune Evasion

Fat mass and obesity-associated protein (FTO), an RNA N⁶-methyladenosine (m⁶A) demethylase, plays oncogenic roles in various cancers, presenting an opportunity for the development of effective targeted therapeutics. Here, we report two potent small-molecule FTO inhibitors that exhibit strong anti-tumor effects in multiple types of cancers. We show that genetic depletion and pharmacological inhibition of FTO dramatically attenuate leukemia stem/initiating cell self-renewal and reprogram immune response by suppressing expression of immune checkpoint genes, especially LILRB4. FTO inhibition sensitizes leukemia cells to T cell cytotoxicity and overcomes hypomethylating agent-induced immune evasion. Our study demonstrates that FTO plays critical roles in cancer stem cell self-renewal and immune evasion and highlights the broad potential of targeting FTO for cancer therapy.

An individualized transcriptional signature to predict the epithelial-mesenchymal transition based on relative expression ordering

The epithelial-mesenchymal transition (EMT) process is involved in cancer cell metastasis and immune system activation. Hence, identification of gene expression signatures capable of predicting the EMT status of cancer cells is essential for development of therapeutic strategies. However, quantitative identification of EMT markers is limited by batch effects, the platform used, or normalization methods. We hypothesized that a set of EMT-related relative expression orderings are highly stable in epithelial samples yet are reversed in mesenchymal samples. To test this hypothesis, we analyzed transcriptome data for ovarian cancer cohorts from publicly available databases, to develop a qualitative 16-gene pair signature (16-GPS) that effectively distinguishes the mesenchymal from epithelial phenotype. Our method was superior to previous quantitative methods in terms of classification accuracy and applicability to individualized patients without requiring data normalization. Patients with mesenchymal-like ovarian cancer showed poorer overall survival compared to patients with epithelial-like ovarian cancer. Additionally, EMT score was positively correlated with expression of immune checkpoint genes and metastasis. We, therefore, established a robust EMT 16-GPS that is independent of detection platform, batch effects and individual variations, and which represents a qualitative signature for investigating the EMT and providing insights into immunotherapy for ovarian cancer patients.

NGS Evaluation of Colorectal Cancer Reveals Interferon Gamma Dependent Expression of Immune Checkpoint Genes and Identification of Novel IFNγ Induced Genes

To evaluate the expression of immune checkpoint genes, their concordance with expression of IFNγ, and to identify potential novel ICP related genes (ICPRG) in colorectal cancer (CRC), the biological connectivity of six well documented ("classical") ICPs (CTLA4, PD1, PDL1, Tim3, IDO1, and LAG3) with IFNγ and its co-expressed genes was examined by NGS in 79 CRC/healthy colon tissue pairs. Identification of novel IFNγ- induced molecules with potential ICP activity was also sought. In our study, the six classical ICPs were statistically upregulated and correlated with IFNγ, CD8A, CD8B, CD4, and 180 additional immunologically related genes in IFNγ positive (FPKM > 1) tumors. By ICP co-expression analysis, we also identified three IFNγ-induced genes [(IFNγ-inducible lysosomal thiol reductase (IFI30), guanylate binding protein1 (GBP1), and guanylate binding protein 4 (GBP4)] as potential novel ICPRGs. These three genes were upregulated in tumor compared to normal tissues in IFNγ positive tumors, co-expressed with CD8A and had relatively high abundance (average FPKM = 362, 51, and 25, respectively), compared to the abundance of the 5 well-defined ICPs (Tim3, LAG3, PDL1, CTLA4, PD1; average FPKM = 10, 9, 6, 6, and 2, respectively), although IDO1 is expressed at comparably high levels (FPKM = 39). We extended our evaluation by querying the TCGA database which revealed the commonality of IFNγ dependent expression of the three potential ICPRGs in 638 CRCs, 103 skin cutaneous melanomas (SKCM), 1105 breast cancers (BC), 184 esophageal cancers (ESC), 416 stomach cancers (STC), and 501 lung squamous carcinomas (LUSC). In terms of prognosis, based on Pathology Atlas data, correlation of GBP1 and GBP4, but not IFI30, with 5-year survival rate was favorable in CRC, BC, SKCM, and STC. Thus, further studies defining the role of IFI30, GBP1, and GBP4 in CRC are warranted.