Immunogenetic clustering of 30 cancers

Establishment of a lysosome-related prognostic signature in breast cancer to predict immune infiltration and therapy response

Background

Lysosomes are instrumental in intracellular degradation and recycling, with their functional alterations holding significance in tumor growth. Nevertheless, the precise role of lysosome-related genes (LRGs) in breast cancer (BC) remains elucidated. This study aimed to establish a prognostic model for BC based on LRGs.

Methods

Employing The Cancer Genome Atlas (TCGA) BC cohort as a training dataset, this study identified differentially expressed lysosome-related genes (DLRGs) through intersecting LRGs with differential expression genes (DEGs) between tumor and normal samples. A prognostic model of BC was subsequently developed using Cox regression analysis and validated within two Gene Expression Omnibus (GEO) external validation sets. Further analyses explored functional pathways, the immune microenvironment, immunotherapeutic responses, and sensitivity to chemotherapeutic drugs in different risk groups. Additionally, the mRNA and protein expression levels of genes within the risk model were examined by utilizing the Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases. Clinical tissue specimens obtained from patients were gathered to validate the expression of the model genes via Real-Time Polymerase Chain Reaction (RT-PCR).

Results

We developed a risk model of BC based on five specific genes (ATP6AP1, SLC7A5, EPDR1, SDC1, and PIGR). The model was validated for overall survival (OS) in two GEO validation sets (p=0.00034 for GSE20685 and p=0.0095 for GSE58812). In addition, the nomogram incorporating clinical factors showed better predictive performance. Compared to the low-risk group, the high-risk group had a higher level of certain immune cell infiltration, including regulatory T cells (Tregs) and type 2 T helper cells (Th2). The high-risk patients appeared to respond less well to general immunotherapy and chemotherapeutic drugs, according to the Tumor Immune Dysfunction and Exclusion (TIDE), Immunophenotype Score (IPS), and drug sensitivity scores. The RT-PCR results validated the expression trends of some prognostic-related genes in agreement with the previous differential expression analysis.

Conclusion

Our innovative lysosome-associated signature can predict the prognosis for BC patients, offering insights for guiding subsequent immunotherapeutic and chemotherapeutic interventions. Furthermore, it has the potential to provide a scientific foundation for identifying prospective therapeutic targets.

Association between brain cancer immunogenetic profile and in silico immunogenicities of 11 viruses

Several viruses including human herpes viruses (HHVs), human polyomavirus JCV, and human papilloma virus (HPV) have been implicated in brain cancer, albeit inconsistently. Since human leukocyte antigen (HLA) is centrally involved in the human immune response to viruses and has been implicated in brain cancer, we evaluated in silico the immunogenicity between 69 Class I HLA alleles with epitopes of proteins of 9 HHVs, JCV, and HPV with respect to a population-based HLA-brain cancer profile. We found that immunogenicity varied widely across HLA alleles with HLA-C alleles exhibiting the highest immunogenicity, and that immunogenicity scores were negatively associated with the population-based HLA-brain cancer profile, particularly for JCV, HHV6A, HHV5, HHV3, HHV8, and HHV7. Consistent with the role of HLA in foreign antigen elimination, the findings suggest that viruses with proteins of high HLA immunogenicity are eliminated more effectively and, consequently, less likely to cause brain cancer; conversely, the absence of highly immunogenic HLA may allow the viral antigens to persist, contributing to cancer.

Positive Association Between the Immunogenetic Human Leukocyte Antigen (HLA) Profiles of Multiple Sclerosis and Brain Cancer

Previous research has documented elevated risk of brain cancer in patients with multiple sclerosis (MS). Separately, human leukocyte antigen (HLA) has been implicated in protection or susceptibility for both conditions. The aim of the current study was to assess a possible role of shared immunogenetic influence on risk of MS and brain cancer. We first identified an immunogenetic profile for each condition based on the covariance between the population frequency of 127 high-resolution HLA alleles and the population prevalence of each condition in 14 Continental Western European countries and then evaluated the correspondence between MS and brain cancer immunogenetic profiles. Also, since each individual carries 12 HLA alleles (2 × 6 genes), we estimated HLA protection and susceptibility for MS and brain cancer at the individual level. We found that the immunogenetic profiles of MS and brain cancer were highly correlated overall (P < .001) and across all 6 HLA genes with the strongest association observed for DRB1, followed by DQB1 and HLA-A. These findings of immunogenetic overlap between MS and brain cancer are discussed in light of the role of HLA in the immune system response to viruses and other foreign antigens.

Scaffold-Based (Matrigel™) 3D Culture Technique of Glioblastoma Recovers a Patient-like Immunosuppressive Phenotype

Conventional 2D cultures are commonly used in cancer research though they come with limitations such as the lack of microenvironment or reduced cell heterogeneity. In this study, we investigated in what respect a scaffold-based (Matrigel™) 3D culture technique can ameliorate the limitations of 2D cultures. NGS-based bulk and single-cell sequencing of matched pairs of 2D and 3D models showed an altered transcription of key immune regulatory genes in around 36% of 3D models, indicating the reoccurrence of an immune suppressive phenotype. Changes included the presentation of different HLA surface molecules as well as cellular stressors. We also investigated the 3D tumor organoids in a co-culture setting with tumor-infiltrating lymphocytes (TILs). Of note, lymphocyte-mediated cell killing appeared less effective in clearing 3D models than their 2D counterparts. IFN-γ release, as well as live cell staining and proliferation analysis, pointed toward an elevated resistance of 3D models. In conclusion, we found that the scaffold-based (Matrigel™) 3D culture technique affects the transcriptional profile in a subset of GBM models. Thus, these models allow for depicting clinically relevant aspects of tumor-immune interaction, with the potential to explore immunotherapeutic approaches in an easily accessible in vitro system.

Immunogenetic Profiles and Associations of Breast, Cervical, Ovarian, and Uterine Cancers

It is increasingly recognized that the human immune response influences cancer risk, progression, and survival; consequently, there is growing interest in the role of human leukocyte antigen (HLA), genes that play a critical role in initiating the immune response, on cancer. Recent evidence documented clustering of cancers based on immunogenetic profiles such that breast and ovarian cancers clustered together as did uterine and cervical cancers. Here we extend that line of research to evaluate the HLA profile of those 4 cancers and their associations. Specifically, we evaluated the associations between the frequencies of 127 HLA alleles and the population prevalences of breast, ovarian, cervical, and uterine cancer in 14 countries in Continental Western Europe. Factor analysis and hierarchical clustering were used to evaluate groupings of cancers based on their immunogenetic profiles. The results documented highly similar immunogenetic profiles for breast and ovarian cancers that were characterized predominantly by protective HLA effects. In addition, highly similar immunogenetic profiles for cervical and uterine cancers were observed that were, conversely, characterized by susceptibility effects. In light of the role of HLA in host immune system protection against non-self antigens, these findings suggest that certain cancers may be associated with similar contributory factors such as viral oncoproteins or neoantigens.