A Novel Epitope Quality-Based Immune Escape Mechanism Reveals Patient's Suitability for Immune Checkpoint Inhibition

Omics-based deep learning approaches for lung cancer decision-making and therapeutics development

Lung cancer has been the most common and the leading cause of cancer deaths globally. Besides clinicopathological observations and traditional molecular tests, the advent of robust and scalable techniques for nucleic acid analysis has revolutionized biological research and medicinal practice in lung cancer treatment. In response to the demands for minimally invasive procedures and technology development over the past decade, many types of multi-omics data at various genome levels have been generated. As omics data grow, artificial intelligence models, particularly deep learning, are prominent in developing more rapid and effective methods to potentially improve lung cancer patient diagnosis, prognosis and treatment strategy. This decade has seen genome-based deep learning models thriving in various lung cancer tasks, including cancer prediction, subtype classification, prognosis estimation, cancer molecular signatures identification, treatment response prediction and biomarker development. In this study, we summarized available data sources for deep-learning-based lung cancer mining and provided an update on recent deep learning models in lung cancer genomics. Subsequently, we reviewed the current issues and discussed future research directions of deep-learning-based lung cancer genomics research.

Integrated Clinical, Molecular and Immunological Characterization of Pulmonary Sarcomatoid Carcinomas Reveals an Immune Escape Mechanism That May Influence Therapeutic Strategies

Pulmonary sarcomatoid carcinoma (PSC) has highly aggressive biological behaviour and poor clinical outcomes, raising expectations for new therapeutic strategies. We characterized 179 PSC by immunohistochemistry, next-generation sequencing and in silico analysis using a deep learning algorithm with respect to clinical, immunological and molecular features. PSC was more common in men, older ages and smokers. Surgery was an independent factor (p < 0.01) of overall survival (OS). PD-L1 expression was detected in 82.1% of all patients. PSC patients displaying altered epitopes due to processing mutations showed another PD-L1-independent immune escape mechanism, which also significantly influenced OS (p < 0.02). The effect was also maintained when only advanced tumour stages were considered (p < 0.01). These patients also showed improved survival with a significant correlation for immunotherapy (p < 0.05) when few or no processing mutations were detected, although this should be interpreted with caution due to the small number of patients studied. Genomic alterations for which there are already approved drugs were present in 35.4% of patients. Met exon 14 skipping was found more frequently (13.7%) and EGFR mutations less frequently (1.7%) than in other NSCLC. In summary, in addition to the divergent genomic landscape of PSC, the specific immunological features of this prognostically poor subtype should be considered in therapy stratification.

Engineering neoantigen vaccines to improve cancer personalized immunotherapy

Immunotherapy treatments harnessing the immune system herald a new era of personalized medicine, offering considerable benefits for cancer patients. Over the past years, tumor neoantigens emerged as a rising star in immunotherapy. Neoantigens are tumor-specific antigens arising from somatic mutations, which are proceeded and presented by the major histocompatibility complex on the cell surface. With the advancement of sequencing technology and bioinformatics engineering, the recognition of neoantigens has accelerated and is expected to be incorporated into the clinical routine. Currently, tumor vaccines against neoantigens mainly encompass peptides, DNA, RNA, and dendritic cells, which are extremely specific to individual patients. Due to the high immunogenicity of neoantigens, tumor vaccines could activate and expand antigen-specific CD4+ and CD8+ T cells to intensify anti-tumor immunity. Herein, we introduce the origin and prediction of neoantigens and compare the advantages and disadvantages of multiple types of neoantigen vaccines. Besides, we review the immunizations and the current clinical research status in neoantigen vaccines, and outline strategies for enhancing the efficacy of neoantigen vaccines. Finally, we present the challenges facing the application of neoantigens.

Proteasomal Processing Immune Escape Mechanisms in Platinum-Treated Advanced Bladder Cancer

In recent years, the number and type of treatment options in advanced bladder cancer (BC) have been rapidly evolving. To select an effective therapy and spare unnecessary side effects, predictive biomarkers are urgently needed. As the host’s anti-cancer immune response is by far the most effective system to impede malignant tumor growth, immune system-based biomarkers are promising. We have recently described altered proteasomal epitope processing as an effective immune escape mechanism to impair cytotoxic T-cell activity. By altering the neoantigens’ characteristics through different proteasomal peptide cleavage induced by non-synonymous somatic mutations, the ability for T-cell activation was decreased (“processing escapes”). In the present study, we analyzed primary chemo-naïve tissue samples of 26 adjuvant platinum-treated urothelial BC patients using a targeted next-generation sequencing panel followed by the epitope determination of affected genes, a machine-learning based prediction of epitope processing and proteasomal cleavage and of HLA-affinity as well as immune activation. Immune infiltration (immunohistochemistries for CD8, granzyme B, CD45/LCA) was digitally quantified by a pathologist and clinico-pathological and survival data were collected. We detected 145 epitopes with characteristics of a processing escape associated with a higher number of CD8-positive but lower number of granzyme B-positive cells and no association with PD-L1-expression. In addition, a high prevalence of processing escapes was associated with unfavorable overall survival. Our data indicate the presence of processing escapes in advanced BC, potentially creating a tumor-promoting pro-inflammatory environment with lowered anti-cancerous activity and independence from PD-L1-expression. The data also need to be prospectively validated in BC treated with immune therapy.

Digital gene expression analysis of NSCLC-patients reveals strong immune pressure, resulting in an immune escape under immunotherapy

BACKGROUND

Immune checkpoint inhibitors (ICIs) are currently one of the most promising therapy options in the field of oncology. Although the first pivotal ICI trial results were published in 2011, few biomarkers exist to predict their therapy outcome. PD-L1 expression and tumor mutational burden (TMB) were proven to be sometimes-unreliable biomarkers. We have previously suggested the analysis of processing escapes, a qualitative measurement of epitope structure alterations under immune system pressure, to provide predictive information on ICI response. Here, we sought to further validate this approach and characterize interactions with different forms of immune pressure.

METHODS

We identified a cohort consisting of 48 patients with advanced non-small cell lung cancer (NSCLC) treated with nivolumab as ICI monotherapy. Tumor samples were subjected to targeted amplicon-based sequencing using a panel of 22 cancer-associated genes covering 98 mutational hotspots. Altered antigen processing was predicted by NetChop, and MHC binding verified by NetMHC. The NanoString nCounter® platform was utilized to provide gene expression data of 770 immune-related genes. Patient data from 408 patients with NSCLC were retrieved from The Cancer Genome Atlas (TCGA) as a validation cohort.

RESULTS

The two immune escape mechanisms of PD-L1 expression (TPS score) (n = 18) and presence of altered antigen processing (n = 10) are mutually non-exclusive and can occur in the same patient (n = 6). Both mechanisms have exclusive influence on different genes and pathways, according to differential gene expression analysis and gene set enrichment analysis, respectively. Interestingly, gene expression patterns associated with altered processing were enriched in T cell and NK cell immune activity. Though both mechanisms influence different genes, they are similarly linked to increased immune activity.

CONCLUSION

Pressure from the immune system will lay the foundations for escape mechanisms, leading to acquisition of resistance under therapy. Both PD-L1 expression and altered antigen processing are induced similarly by pronounced immunoactivity but in different context. The present data help to deepen our understanding of the underlying mechanisms behind those immune escapes.

Digital Gene Expression Analysis of Epithelioid and Sarcomatoid Mesothelioma Reveals Differences in Immunogenicity

Malignant pleural mesothelioma (MPM) is an aggressive malignancy associated with asbestos exposure. Median survival ranges from 14 to 20 months after initial diagnosis. As of November 2020, the FDA approved a combination of immune checkpoint inhibitors after promising intermediate results. Nonetheless, responses remain unsatisfying. Adequate patient stratification to improve response rates is still lacking. This retrospective study analyzed formalin fixed paraffin embedded specimens from a cohort of 22 MPM. Twelve of those samples showed sarcomatoid, ten epithelioid differentiation. Complete follow-up, including radiological assessment of response by modRECIST and time to death, was available with reported deaths of all patients. RNA of all samples was isolated and subjected to digital gene expression pattern analysis. Our study revealed a notable difference between epithelioid and sarcomatoid mesothelioma, showing differential gene expression for 304/698 expressed genes. Whereas antigen processing and presentation to resident cytotoxic T cells as well as phagocytosis is highly affected in sarcomatoid mesothelioma, cell-cell interaction via cytokines seems to be of greater importance in epithelioid cases. Our work reveals the specific role of the immune system within the different histologic subtypes of MPM, providing a more detailed background of their immunogenic potential. This is of great interest regarding therapeutic strategies including immunotherapy in mesothelioma.