Immune index: A gene and cell prognostic signature for immunotherapy response prediction in hepatocellular carcinoma

Deletion of 17p in cancers: Guilt by (p53) association

Monoallelic deletion of the short arm of chromosome 17 (del17p) is a recurrent abnormality in cancers with poor outcomes. Best studied in relation to haematological malignancies, associated functional outcomes are attributed mainly to loss and/or dysfunction of TP53, which is located at 17p13.1, but the wider impact of deletion of other genes located on 17p is poorly understood. 17p is one of the most gene-dense regions of the genome and includes tumour suppressor genes additional to TP53, genes essential for cell survival and proliferation, as well as small and long non-coding RNAs. In this review we utilise a data-driven approach to demarcate the extent of 17p deletion in multiple cancers and identify a common loss-of-function gene signature. We discuss how the resultant loss of heterozygosity (LOH) and haploinsufficiency may influence cell behaviour but also identify vulnerabilities that can potentially be exploited therapeutically. Finally, we highlight how emerging animal and isogenic cell line models of del17p can provide critical biological insights for cancer cell behaviour.

A pan-cancer analysis of the oncogenic role of N-acetyltransferase 8 like in human cancer

BACKGROUND

N-Acetyltransferase 8 Like (NAT8L) inhibits natural killer (NK)/T-cell cytotoxicity by impairing the formation of the immunological synapse via N-acetylaspartate (NAA). Existing research has predominantly focused on the metabolic functions of NAT8L, particularly in adipose tissues and myelination in the brain. However, in contrast to other N-acetyltransferases such as NAT1 and NAT2, the role of NAT8L in cancer has been less extensively studied. In this study, we conducted a comprehensive pan-cancer analysis to investigate the carcinogenic role of NAT8L in human cancers.

METHODS

We utilized the standardized TCGA pan-cancer dataset to analyze differential expression, clinical prognosis, gene mutation, immune infiltration, epigenetic modification, tumor stemness, and heterogeneity. Additionally, we evaluated the sensitivity of NAT8L to small molecule drugs using the GDSC and CTRP databases.

RESULTS

In this study, we identified that NAT8L expression was upregulated in 6 cancers and downregulated in 12 compared to normal tissues. We analyzed its prognostic value in 5 tumor types (KIRP, COAD, COADREAD, GBMLGG, LUSC) and found correlations with overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). Furthermore, NAT8L expression was significantly correlated with levels of most immune checkpoints, immunomodulators, and immune cell infiltration. The mutation frequencies for bladder cancer (BLCA), glioblastoma multiforme and glioma (GBMLGG), lower-grade glioma (LGG), and KIRP were 1.2%, 0.9%, 0.8%, and 0.4%, respectively.

CONCLUSION

Our findings suggest that NAT8L may serve as a potential prognostic marker and therapeutic target across a variety of cancers, particularly in KIRP, COAD, COADREAD, GBMLGG, and lung squamous cell carcinoma (LUSC).

Biomarkers and prognostic factors of PD-1/PD-L1 inhibitor-based therapy in patients with advanced hepatocellular carcinoma

Systemic therapies using programmed death-1 (PD-1) and programmed death ligand 1 (PD-L1) inhibitors have demonstrated commendable efficacy in some patients with advanced hepatocellular carcinoma (HCC); however, other individuals do not respond favorably. Hence, identifying the biomarkers, the prognostic factors, and their underlying mechanisms is crucial. In this review, we summarized the latest advancements in this field. Within the tumor microenvironment, PD-L1 expression is commonly utilized to predict response. Moreover, the characteristics of tumor-infiltrating lymphocytes are associated with the effectiveness of immunotherapy. Preclinical studies have identified stimulatory dendritic cells, conventional dendritic cells, and macrophages as potential biomarkers. The emergence of single-cell sequencing and spatial transcriptomics has provided invaluable insights into tumor heterogeneity through the lens of single-cell profiling and spatial distribution. With the widespread adoption of next-generation sequencing, certain genomic characteristics, including tumor mutational burden, copy number alterations, specific genes (TP53, CTNNB1, and GZMB), and signaling pathways (WNT/β-catenin) have been found to correlate with prognosis. Furthermore, clinical features such as tumor size, number, and metastasis status have demonstrated prognostic value. Notably, common indicators such as the Child-Pugh score and Eastern Cooperative Oncology Group score, which are used in patients with liver diseases, have shown potential. Similarly, commonly employed laboratory parameters such as baseline transforming growth factor beta, lactate dehydrogenase, dynamic changes in alpha-fetoprotein (AFP) and abnormal prothrombin, CRAFITY score (composed of C-reactive protein and AFP), and immune adverse events have been identified as predictive biomarkers. Novel imaging techniques such as EOB-MRI and PET/CT employing innovative tracers also have potential. Moreover, liquid biopsy has gained widespread use in biomarker studies owing to its non-invasive, convenient, and highly reproducible nature, as well as its dynamic monitoring capabilities. Research on the gut microbiome, including its composition, dynamic changes, and metabolomic analysis, has gained considerable attention. Efficient biomarker discovery relies on continuous updating of treatment strategies. Next, we summarized recent advancements in clinical research on HCC immunotherapy and provided an overview of ongoing clinical trials for contributing to the understanding and improvement of HCC immunotherapy.

Deciphering the immune modulation through deep transcriptomic profiling and therapeutic implications of DNA damage repair pattern in hepatocellular carcinoma

AIMS

DNA damage repair (DDR) plays a pivotal role in hepatocellular carcinoma (HCC), driving oncogenesis, progression, and therapeutic response. However, the mechanisms of DDR mediated immune cells and immuno-modulatory pathways in HCC are yet ill-defined.

METHODS

Our study introduces an innovative deep machine learning framework for precise DDR assessment, utilizing single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data. Single-cell RNA sequencing data were obtained and in total 85,628 cells of primary or post-immunotherapy cases were analyzed. Large-scale HCC datasets, including 1027 patients in house together with public datasets, were used for 101 machine-learning models and a novel DDR feature was derived at single-cell resolution (DDRscore). Druggable targets were predicted using the reverse phase protein array (RPPA) proteomic profiling of 169 HCC patients and RNA-seq data from 22 liver cancer cell lines.

RESULTS

Our investigation reveals a dynamic interplay of DDR with natural killer cells and B cells in the primary HCC microenvironment, shaping a tumor-promoting immune milieu through metabolic programming. Analysis of HCC post-immunotherapy demonstrates elevated DDR levels that induces epithelial-mesenchymal transition and fibroblast-like transformation, reshaping the fibrotic tumor microenvironment. Conversely, attenuated DDR promotes antigen cross-presentation by dendritic cells and CD8+ T cells, modulating the inflammatory tumor microenvironment. Regulatory network analysis identifies the CXCL10-CXCR3 axis as a key determinant of immunotherapeutic response in low DDR HCC, potentially regulated by transcription factors GATA3, REL, and TBX21. Using machine learning techniques by combining bulk RNA-seq data in house together with public datasets, we introduce DDRscore, a robust consensus DDR scoring system to predict overall survival and resistance to PD-1 therapy in HCC patients. Finally, we identify BRAF as a potential therapeutic target for high DDRscore patients.

CONCLUSION

Our comprehensive findings advance our understanding of DDR and the tumor microenvironment in HCC, providing insights into immune regulatory mechanisms mediated via DDR pathways.