Hypoxia Molecular Characterization in Hepatocellular Carcinoma Identifies One Risk Signature and Two Nomograms for Clinical Management

Hypoxia is a universal feature in the tumor microenvironment (TME). Nonetheless, the heterogeneous hypoxia patterns of TME have still not been elucidated in hepatocellular carcinoma (HCC). Using consensus clustering algorithm and public datasets, we identified heterogeneous hypoxia subtypes. We also revealed the specific biological and clinical characteristics via bioinformatic methods. The principal component analysis algorithm was employed to develop a hypoxia-associated risk score (HARS). We identified the two hypoxia subtypes: low hypoxia pattern (C1) and high hypoxia pattern (C2). C1 was less sensitive to immunotherapy compared to C2, consistent with the lack of immune cells and immune checkpoints (ICPs) in C1, whereas C2 was the opposite. C2 displayed worse prognosis and higher sensitivity to obatoclax relative to C1, while C1 was more sensitive to sorafenib. The two subtypes also demonstrated subtype-specific genomic variations including mutation, copy number alteration, and methylation. Moreover, we developed and validated a risk signature: HARS, which had excellent performance for predicting prognosis and immunotherapy. We revealed two hypoxia subtypes with distinct biological and clinical characteristics in HCC, which enhanced the understanding of hypoxia pattern. The risk signature was a promising biomarker for predicting prognosis and immunotherapy.

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Significance of Tumor Infiltrating Immune Cells (TIICs) in Endometrial carcinoma: A Bioinformatics Analysis

10.21203/rs.3.rs-251650/v1 ◽

2021 ◽

Author(s):

Qing Hu ◽

Jun Wang ◽

Lina Ge ◽

Ying Wu

Keyword(s):

Principal Component Analysis ◽

Immune Cells ◽

Immune Activation ◽

Immune Checkpoint ◽

Clustering Algorithm ◽

Immune Cell ◽

Principal Component ◽

Immune Cell Infiltration ◽

Consensus Clustering ◽

Immune Related Genes

Abstract Background: Increasing evidence has revealed that tumor-infiltrating immune cells (TIICs) are involved in the development of endometrial carcinoma (EC). In this study, we aimed to reveal the significance of 28 TIIC types in the classification and prognosis of EC. Methods: Single-sample gene set enrichment analysis (ssGSEA) was used to calculate the abundance of the 28 TIIC types in EC patients from TCGA database. A consensus clustering algorithm was used to group the EC patients. Principal component analysis (PCA) algorithms were performed to calculate an ICI score for each sample to predict the sensitivity to ICIs therapy based on the 28 TIIC types.Results: The EC patients from The Cancer Genome Atlas (TCGA) database were classified into two groups (cluster.A and cluster.B) based on the 28 types of TIIC using a consensus clustering algorithm. The patients in the cluster.B group had increased immune cell infiltration, and higher expression of human leucocyte antigen (HLA) genes, immune checkpoint molecules, and immune activation-related genes, suggesting that they may be more sensitive to immune checkpoint inhibitors (ICIs) therapy. Differential analysis between cluster.A and cluster.B identified 591 immune-related genes. We validated the immune regulation mechanism based on the 591 immune-related genes using another consensus clustering algorithm. The EC patients were divided into two groups (gene.cluster.A and gene.cluster.B) based on the 591 immune-related genes. The patients in the gene.cluster.B group had increased immune cell infiltration, and higher expression of HLA genes, immune checkpoint molecules, and immune activation-related genes. In addition, we also calculated an ICI score for each patient with EC to predict the sensitivity to ICIs therapy based on the 28 TIIC types using principal component analysis algorithms. Conclusions: In summary, the 28 types of TIIC play non-negligible roles in the development of EC. Our investigation of the 28 types of TIIC may help to guide ICIs treatment strategies for patients with EC.

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Immune checkpoint and checkpoint inhibitors in hepatocellular carcinoma

Thai Journal of Hepatology ◽

10.30856/th.jhep2018vol1iss1_07 ◽

2018 ◽

Vol 1 (1) ◽

pp. 28-32

Author(s):

Piyawat Komolmit

Keyword(s):

Hepatocellular Carcinoma ◽

T Cells ◽

Major Histocompatibility Complex ◽

T Cell Receptor ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitors ◽

Checkpoint Inhibitors ◽

Cell Receptor ◽

Immune Checkpoints ◽

Histocompatibility Complex

การรักษามะเร็งด้วยแนวความคิดของการกระตุ้นให้ภูมิต้านทานของร่างกายไปทำลายเซลล์มะเร็งนั้น ปัจจุบันได้รับการพิสูจน์ชัดว่าวิธีการนี้สามารถหยุดยั้งการแพร่กระจายของเซลล์มะเร็ง โดยไม่ก่อให้เกิดภาวะแทรกซ้อนทางปฏิกิริยาภูมิต้านทานต่ออวัยวะส่วนอื่นที่รุนแรง สามารถนำมาใช้ทางคลินิกได้ ยุคของการรักษามะเร็งกำลังเปลี่ยนจากยุคของยาเคมีบำบัดเข้าสู่การรักษาด้วยภูมิต้านทาน หรือ immunotherapy ยากลุ่ม Immune checkpoint inhibitors โดยเฉพาะ PD-1 กับ CTLA-4 inhibitors จะเข้ามามีบทบาทในการรักษามะเร็งตับในระยะเวลาอันใกล้ จำเป็นแพทย์จะต้องมีความรู้ความเข้าใจในพื้นฐานของ immune checkpoints และยาที่ไปยับยั้งโมเลกุลเหล่านี้ Figure 1 เมื่อ T cells รับรู้แอนทิเจนผ่านทาง TCR/MHC จะมีปฏิกิริยาระหว่าง co-receptors หรือ immune checkpoints กับ ligands บน APCs หรือ เซลล์มะเร็ง ทั้งแบบกระตุ้น (co-stimulation) หรือยับยั้ง (co-inhibition) TCR = T cell receptor, MHC = major histocompatibility complex

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Immune Checkpoint Inhibitors in Patients with Recurrent Hepatocellular Carcinoma after Liver Transplantation: A Case Report and Literature Review

Current Cancer Drug Targets ◽

10.2174/1568009620666200520084415 ◽

2020 ◽

Vol 20 (9) ◽

pp. 720-727

Author(s):

Jianguo Qiu ◽

Wei Tang ◽

Chengyou Du

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Transplantation ◽

Immune Checkpoint ◽

Graft Rejection ◽

Checkpoint Inhibitors ◽

Liver Graft ◽

Immune Checkpoints ◽

Term Survival ◽

Liver Preservation ◽

Programmed Death

Background: Immune checkpoint modulators, such as the programmed death protein-1 (PD-1)/programmed death ligand-1 (PD-L1) inhibitor, cytotoxic T-Lymphocyte-associated antigen 4 (CTLA-4) inhibitor have been investigated with encouraging results for hepatocellular carcinoma (HCC). However, the safety of this strategy in patients with previous liver transplantation (LT) is not well studied. Objective: To explore the safety and feasibility of immune checkpoints inhibitors in recurrent and metastatic HCC patients on a background of LT. Methods: A case of recurrent, refractory, metastatic HCC after LT, where PD-1 inhibitor was initiated, was described and related literature was reviewed. Results: There was complete remission in lung metastases and the partial radiological response of metastatic retroperitoneal lymph node to the drug with no liver graft rejection after 13 cycles of PD- 1 inhibitor injection. PD-1inhibitor, at least in this patient, was verified to play an important role in controlling tumor progression and prolonging patient survival. Conclusions: This novel drug might be a useful method to allow doctors to guarantee a better chance for long-term survival in recurrent, metastatic HCC patients with the previous LT. However, it should be used with caution in allograft recipients due to the risk of acute graft rejection, further larger, prospective studies are needed to determine optimal immunomodulatory therapy to achieve optimal anti-tumor efficacy with transplant liver preservation.

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Application of Machine Learning in Animal Disease Analysis and Prediction

Current Bioinformatics ◽

10.2174/1574893615999200728195613 ◽

2020 ◽

Vol 15 ◽

Author(s):

Shuwen Zhang ◽

Qiang Su ◽

Qin Chen

Keyword(s):

Machine Learning ◽

Unsupervised Learning ◽

Supervised Learning ◽

Clustering Algorithm ◽

Principal Component ◽

Support Vector ◽

Animal Disease ◽

Human Beings ◽

Animal Diseases ◽

Disease Analysis

Abstract: Major animal diseases pose a great threat to animal husbandry and human beings. With the deepening of globalization and the abundance of data resources, the prediction and analysis of animal diseases by using big data are becoming more and more important. The focus of machine learning is to make computers learn how to learn from data and use the learned experience to analyze and predict. Firstly, this paper introduces the animal epidemic situation and machine learning. Then it briefly introduces the application of machine learning in animal disease analysis and prediction. Machine learning is mainly divided into supervised learning and unsupervised learning. Supervised learning includes support vector machines, naive bayes, decision trees, random forests, logistic regression, artificial neural networks, deep learning, and AdaBoost. Unsupervised learning has maximum expectation algorithm, principal component analysis hierarchical clustering algorithm and maxent. Through the discussion of this paper, people have a clearer concept of machine learning and understand its application prospect in animal diseases.

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A highly stable multifunctional aptamer for enhancing antitumor immunity against hepatocellular carcinoma by blocking dual immune checkpoints

Biomaterials Science ◽

10.1039/d0bm02210a ◽

2021 ◽

Author(s):

Yanlin Du ◽

Da Zhang ◽

Yiru Wang ◽

Ming Wu ◽

Cuilin Zhang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Checkpoint ◽

Antitumor Immunity ◽

Immune Checkpoint Blockade ◽

Checkpoint Blockade ◽

Immune Checkpoints

A highly stable multifunctional aptamer was prepared for strengthening antitumor immunity through a dual immune checkpoint blockade of CTLA-4 and PD-L1.

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To Weight or Not to Weight, That Is the Question: The Design of a Composite Indicator of Landscape Fragmentation

Applied Sciences ◽

10.3390/app11073208 ◽

2021 ◽

Vol 11 (7) ◽

pp. 3208

Author(s):

Andrea De Montis ◽

Vittorio Serra ◽

Giovanna Calia ◽

Daniele Trogu ◽

Antonio Ledda

Keyword(s):

Principal Component Analysis ◽

Geometric Mean ◽

Composite Index ◽

Weighted Average ◽

Principal Component ◽

Expert Judgment ◽

Landscape Fragmentation ◽

Composite Indicator ◽

Per Se ◽

Higher Sensitivity

Composite indicators (CIs), i.e., combinations of many indicators in a unique synthetizing measure, are useful for disentangling multisector phenomena. Prominent questions concern indicators’ weighting, which implies time-consuming activities and should be properly justified. Landscape fragmentation (LF), the subdivision of habitats in smaller and more isolated patches, has been studied through the composite index of landscape fragmentation (CILF). It was originally proposed by us as an unweighted combination of three LF indicators for the study of the phenomenon in Sardinia, Italy. In this paper, we aim at presenting a weighted release of the CILF and at developing the Hamletian question of whether weighting is worthwhile or not. We focus on the sensitivity of the composite to different algorithms combining three weighting patterns (equalization, extraction by principal component analysis, and expert judgment) and three indicators aggregation rules (weighted average mean, weighted geometric mean, and weighted generalized geometric mean). The exercise provides the reader with meaningful results. Higher sensitivity values signal that the effort of weighting leads to more informative composites. Otherwise, high robustness does not mean that weighting was not worthwhile. Weighting per se can be beneficial for more acceptable and viable decisional processes.

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Inhibition of Kynurenine Metabolism and Its Effect in Mitochondrial Function in Hepatocellular Carcinoma

Innovation in Aging ◽

10.1093/geroni/igaa057.410 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 124-125

Author(s):

Raul Castro-Portuguez ◽

Samuel Freitas ◽

George Sutphin

Keyword(s):

Hepatocellular Carcinoma ◽

Mitochondrial Function ◽

De Novo ◽

Principal Component ◽

Kynurenine Pathway ◽

The Cancer Genome Atlas ◽

Wilcoxon Test ◽

Nad Synthesis ◽

Significant Difference ◽

Kynurenine Metabolism

Abstract Hepatocellular carcinoma (HCC) is the most prevalent cancer in the liver. The majority of ingested tryptophan is processed in the liver through the kynurenine pathway, the endpoint of which is de novo NAD+ biosynthesis. Dysregulation of tryptophan-kynurenine metabolism and NAD+ synthesis may promote mitochondrial malfunction, tumor reprogramming, and carcinogenesis. Using a publicly available gene expression dataset from liver hepatocellular carcinoma (LIHC) samples available through The Cancer Genome Atlas (TCGA; n = 371), we employed Principal Component Analysis (PCA), hierarchical clustering, gene-pattern expression profiling, and survival analysis to cluster patients and determine overall survival. Our analysis of genes encoding kynurenine pathway enzymes determined that patients with high QPRT expression had a poor prognosis with decreased median survival, with no effect on the maximum survival. There is a significant difference in the survival between patients with high QPRT expression relative to patients with high HAAO/AFMID expression (HR = 1.2, [95% CI 0.5-1.8] P = 0.0181, Gehan-Breslow-Wilcoxon Test). Patients with high QPRT expression have higher survival rates compared with low QPRT expression (HR = 1.4, [95% CI 0.9-2.2] P = 0.0344, Gehan-Breslow-Wilcoxon Test). To test the consequences of kynurenine-pathway inhibition in mitochondrial function and morphology we use 4-Cl-3HAA, an irreversible HAAO inhibitor, and observed a small increase in mitochondrial fragmentation in HepG2 cells after 24 hours of treatment. We conclude that kynurenine metabolism may be useful as a biomarker to predict patient prognosis among HCC patients. In ongoing work, we are testing QPRT inhibitors in cell culture as a potential adjuvant for chemotherapies.

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Combined Inhibition of TGF-β1-Induced EMT and PD-L1 Silencing Re-Sensitizes Hepatocellular Carcinoma to Sorafenib Treatment

Journal of Clinical Medicine ◽

10.3390/jcm10091889 ◽

2021 ◽

Vol 10 (9) ◽

pp. 1889

Author(s):

Ritu Shrestha ◽

Prashanth Prithviraj ◽

Kim R. Bridle ◽

Darrell H. G. Crawford ◽

Aparna Jayachandran

Keyword(s):

Hepatocellular Carcinoma ◽

Combination Treatment ◽

Immune Checkpoint ◽

Post Treatment ◽

Immune Checkpoints ◽

Sorafenib Treatment ◽

Mesenchymal Transition ◽

Immune Checkpoint Molecules ◽

Tgf Β1 ◽

Hcc Cells

Hepatocellular carcinoma (HCC) is the most common type of primary hepatic malignancy. HCC is one of the leading causes of cancer deaths worldwide. The oral multi-tyrosine kinase inhibitor Sorafenib is the standard first-line therapy in patients with advanced unresectable HCC. Despite the significant survival benefit in HCC patients post treatment with Sorafenib, many patients had progressive disease as a result of acquiring drug resistance. Circumventing resistance to Sorafenib by exploring and targeting possible molecular mechanisms and pathways is an area of active investigation worldwide. Epithelial-to-mesenchymal transition (EMT) is a cellular process allowing epithelial cells to assume mesenchymal traits. HCC tumour cells undergo EMT to become immune evasive and develop resistance to Sorafenib treatment. Immune checkpoint molecules control immune escape in many tumours, including HCC. The aim of this study is to investigate whether combined inhibition of EMT and immune checkpoints can re-sensitise HCC to Sorafenib treatment. Post treatment with Sorafenib, HCC cells PLC/PRF/5 and Hep3B were monitored for induction of EMT and immune checkpoint molecules using quantitative reverse transcriptase (qRT)- PCR, western blot, immunofluorescence, and motility assays. The effect of combination treatment with SB431542, a specific inhibitor of the transforming growth factor (TGF)-β receptor kinase, and siRNA mediated knockdown of programmed cell death protein ligand-1 (PD-L1) on Sorafenib resistance was examined using a cell viability assay. We found that three days of Sorafenib treatment activated EMT with overexpression of TGF-β1 in both HCC cell lines. Following Sorafenib exposure, increase in the expression of PD-L1 and other immune checkpoints was observed. SB431542 blocked the TGF-β1-mediated EMT in HCC cells and also repressed PD-L1 expression. Likewise, knockdown of PD-L1 inhibited EMT. Moreover, the sensitivity of HCC cells to Sorafenib was enhanced by combining a blockade of EMT with SB431542 and knockdown of PD-L1 expression. Sorafenib-induced motility was attenuated with the combined treatment of SB431542 and PD-L1 knockdown. Our findings indicate that treatment with Sorafenib induces EMT and expression of immune checkpoint molecules, which contributes to Sorafenib resistance in HCC cells. Thus, the combination treatment strategy of inhibiting EMT and immune checkpoint molecules can re-sensitise HCC cells to Sorafenib.

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