Identification of a prognostic immune signature for cervical cancer to predict survival and response to immune checkpoint inhibitors.

Cervical cancer (CC) is a leading cause of cancer-related death in women. Limited studies have investigated whether immune-related genes (IRGs) or tumor immune microenvironment (TIME) could be indicators for CC prognoses. The aim of this study was to develop an improved prognostic signature for CC based on IRGs or TIME to predict survival and response to immune checkpoint inhibitors (ICIs). A prognostic signature was constructed using bioinformatics method and its predictive capability was validated. The mechanisms underlying the signature's predictive capability were explored with CIBERSORT algorithm and mutation analysis. Immunophenoscore (IPS) is validated for ICIs response, and was therefore explored in relation to the signature. A prognostic signature based on 11 IRGs was developed. A multivariate analysis revealed that the 11-IRG signature was an independent prognostic factor for overall survival (OS) and progression-free interval in CC patients. In the 11-IRG signature high-risk group, CD8 T cells and resting mast cells, which are found to associate with better OS in our study, were lower; activated mast cells, associated with poorer OS, were higher, compared with the low-risk group. An IPS analysis suggested that the 11-IRG signature low-risk group, which possessed a higher IPS, represented a more immunogenic phenotype that was more inclined to respond to ICIs. In short, an 11-IRG prognostic signature for predicting CC patients' survival and response to ICIs was firmly established. The predictive capability of this model in CC requires further testing with the goal of better prognostic stratification and treatment management.

Yang S ，Wu Y ，Deng Y ，Zhou L ，Yang P ，Zheng Y ，Zhang D ，Zhai Z ，Li N ，Hao Q ，Song D ，Kang H ，Dai Z ... -  《OncoImmunology》

Survival prediction and response to immune checkpoint inhibitors: A prognostic immune signature for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common cancers all over the world. Several studies have explored if immune-related genes and tumor immune microenvironment could play roles in HCC prognoses. This study is aimed at developing a prognostic signature of HCC based on immune-related genes or tumor immune microenvironment to predict survival and response to immune checkpoint inhibitors (ICIs). We constructed a prognostic signature using bioinformatics method and validated its predictive capability. The mechanisms of the signature prediction were explored with The Cancer Immunome Atlas (TCIA) and mutation analysis. We also explored the association between the signature and immunophenoscore (IPS), which is the marker of ICIs response. A 6 immune-related-gene (6-IRG) signature was developed. It was revealed in a multivariate analysis that the 6-IRG signature was an independent prognostic factor of overall survival and progression-free interval among HCC patients. In the high-risk group of 6-IRG signature score, macrophage M0 cells and regulatory T cells, which are observed associated with poor overall survival in our study, were higher. The low-risk group had a higher IPS, which meant a better response to ICIs. Taken together, we constructed a reliable 6-IRG signature for prediction of survival and response to ICIs. The signature needs further testing for clinical application.

Xu Y ，Wang Z ，Li F 《Translational Oncology》

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.

Wu P ，Sun W ，Zhang H 《-》

Identification of a prognostic and therapeutic immune signature associated with hepatocellular carcinoma.

Peng Y ，Liu C ，Li M ，Li W ，Zhang M ，Jiang X ，Chang Y ，Liu L ，Wang F ，Zhao Q ... -  《Cancer Cell International》

Identification of an Immune-Related LncRNA Signature in Gastric Cancer to Predict Survival and Response to Immune Checkpoint Inhibitors.

Immune microenvironment in gastric cancer is closely associated with patient's prognosis. Long non-coding RNAs (lncRNAs) are emerging as key regulators of immune responses. In this study, we aimed to construct a prognostic model based on immune-related lncRNAs (IRLs) to predict the overall survival and response to immune checkpoint inhibitors (ICIs) of gastric cancer (GC) patients. The IRL signature was constructed through a bioinformatics method, and its predictive capability was validated. A stratification analysis indicates that the IRL signature can distinguish different risk patients. A nomogram based on the IRL and other clinical variables efficiently predicted the overall survival of GC patients. The landscape of tumor microenvironment and mutation status partially explain this signature's predictive capability. We found the level of cancer-associated fibroblasts, endothelial cells, M2 macrophages, and stroma cells was high in the high-risk group, while the number of CD8+ T cells and T follicular helper cells was high in the low-risk group. Immunophenoscore (IPS) is validated for ICI response, and the IRL signature low-risk group received higher IPS, representing a more immunogenic phenotype that was more inclined to respond to ICIs. In addition, we found RNF144A-AS1 was highly expressed in GC patients and promoted the proliferation, migration, and invasive capacity of GC cells. We concluded that the IRL signature represents a novel useful model for evaluating GC survival outcomes and could be implemented to optimize the selection of patients to receive ICI treatment.

Ding Z ，Li R ，Han J ，Sun D ，Shen L ，Wu G ... -  《Frontiers in Cell and Developmental Biology》