Correlation of genomic alterations and PD-L1 expression in thymoma

PD-L1 Expression in Neoplastic and Immune Cells of Thymic Epithelial Tumors: Correlations with Disease Characteristics and HDAC Expression

BACKGROUND

Programmed death-ligand 1 (PD-L1) expression in neoplastic and immune cells of the tumor microenvironment determines the efficacy of antitumor immunity, while it can be regulated at the epigenetic level by various factors, including HDACs. In this study, we aim to evaluate the expression patterns of PD-L1 in thymic epithelial tumors (TETs), while we attempt the first correlation analysis between PD-L1 and histone deacetylases (HDACs) expression.

METHODS

Immunohistochemistry was used to evaluate the expression of PD-L1 in tumor and immune cells of 91 TETs with SP263 and SP142 antibody clones, as well as the expressions of HDCA1, -2, -3, -4, -5, and -6.

RESULTS

The PD-L1 tumor proportion score (TPS) was higher, while the immune cell score (IC-score) was lower in the more aggressive TET subtypes and in more advanced Masaoka-Koga stages. A positive correlation between PD-L1 and HDAC-3, -4, and -5 cytoplasmic expression was identified.

CONCLUSIONS

Higher PD-L1 expression in neoplastic cells and lower PD-L1 expression in immune cells of TETs characterizes more aggressive and advanced neoplasms. Correlations between PD-L1 and HDAC expression unravel the impact of epigenetic regulation on the expression of immune checkpoint molecules in TETs, with possible future applications in combined therapeutic targeting.

The Molecular Landscape of Thymic Epithelial Tumors: A Comprehensive Review

Thymic epithelial tumors (TETs) are characterized by their extreme rarity and variable clinical presentation, with the inadequacy of the use of histological classification alone to distinguish biologically indolent from aggressive cases. The utilization of Next Generation Sequencing (NGS) to unravel the intricate genetic landscape of TETs could offer us a comprehensive understanding that is crucial for precise diagnoses, prognoses, and potential therapeutic strategies. Despite the low tumor mutational burden of TETS, NGS allows for exploration of specific genetic signatures contributing to TET onset and progression. Thymomas exhibit a limited mutational load, with prevalent GTF2I and HRAS mutations. On the other hand, thymic carcinomas (TCs) exhibit an elevated mutational burden, marked by frequent mutations in TP53 and genes associated with epigenetic regulation. Moreover, signaling pathway analyses highlight dysregulation in crucial cellular functions and pathways. Targeted therapies, and ongoing clinical trials show promising results, addressing challenges rooted in the scarcity of actionable mutations and limited genomic understanding. International collaborations and data-sharing initiatives are crucial for breakthroughs in TETs research.

Analysis of the efficacy and safety of immunotherapy in advanced thymoma patients

BACKGROUND

Immunotherapy has exhibited efficacy in thymic carcinoma patients; however, there are insufficient data to confirm this efficacy in thymoma. The toxicity of immunotherapy also remains to be determined.

METHODS

The efficacy and safety of immunotherapy were analyzed in 11 thymoma patients who received PD-1 inhibitors according to a range of relevant indexes including the objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and immunotherapy-related adverse events.

RESULTS

The PFS and OS rates for all patients were 12.8 and 56.5 months, respectively. No difference in efficacy was detected between monotherapy and combination therapy (PFS: 12.8 vs 2.2 months, P = 0.787; OS: 73.8 vs 56.5 months, P = 0.367). The ORRs and DCRs for all patients were 27.3% and 90.9%, respectively. The incidence of adverse events was 45.5% among the 11 thymoma patients, including immune-related myocarditis (36.4%), immune-related liver damage (18.2%), and myasthenia gravis (18.2%). In the whole cohort of patients, the rate of adverse events of grade 3 or higher was 36.4%. The rates of adverse events of grade 3 or 4 in B3-type and non-B3-type thymoma patients were 0% and 62.5%, respectively.

CONCLUSIONS

Immunotherapy elicited a response in thymoma patients; however, more attention should be paid to the immune-related adverse events.

Molecular profiling of rare thymoma using next-generation sequencing: meta-analysis

BACKGROUND

Thymomas belong to rare tumors giving rise to thymic epithelial tissue. There is a classification of several forms of thymoma: A, AB, B1, B2, B3, thymic carcinoma (TC) and thymic neuroendocrine thymoma. In this meta-analysis study, we have focused on thymoma using articles based on the disease's next-generation sequencing (NGS) genomic profiling.

MATERIALS AND METHODS

We conducted a systematic review and meta-analysis of the prevalence of studies that discovered the genes and variants occurring in the less aggressive forms of the thymic epithelial tumors. Studies published before 12^th December 2022 were identified through PubMed, Web of Science (WoS), and SCOPUS databases. Two reviewers have searched for the bases and selected the articles for the final analysis, based on well-defined exclusion and inclusion criteria.

RESULTS

Finally, 12 publications were included in the qualitative as well as quantitative analysis. The three genes, GTF2I, TP53, and HRAS, emerged as disease-significant in the observed studies. The Odds Ratio for all three extracted genes GTF2I (OR = 1.58, CI [1.51, 1.66] p < 0.00001), TP53 (OR = 1.36, CI [1.12, 1.65], p < 0.002), and HRAS (OR = 1.02, CI [1.00, 1.04], p < 0.001).

CONCLUSIONS

According to obtained data, we noticed that the GTF2I gene exhibits a significant prevalence in the cohort of observed thymoma patients. Moreover, analyzing published articles NGS has suggested GTF2I, TP53, and HRAS genes as the most frequently mutated genes in thymoma that have pathogenic single nucleotide variants (SNV) and Insertion/Deletion (InDel), which contribute to disease development and progression. These variants could be valuable biomarkers and target points specific to thymoma.

Association of differential expression of immunoregulatory molecules and presence of targetable mutations may inform rational design of clinical trials

Background

Immune checkpoint inhibitors (ICIs) and genomic biomarker-driven targeted therapies have revolutionized the modern oncologic treatment arsenal. The next step has been to combine targeted agents and ICIs. In doing so, some combination regimens may be more logical than others.

Patients and methods

Whole-exome and whole-transcriptome sequencing were performed on 2739 unselected later-stage clinical cases from 24 solid tumor subtypes in the NantHealth database, and data were also curated from 5746 similarly sequenced patients across 28 solid tumor subtypes in The Cancer Genome Atlas (TCGA). Significant differential expression of 10 immunoregulatory molecules [IRMs (genes)] was analyzed for association with mutant versus wild-type genes.

Results

Twenty-three significant associations between currently actionable variants and RNA-expressed checkpoint genes were identified in the TCGA cases; 10 were validated in the external cohort of 2739 clinical cases from NantHealth (P values were adjusted using Benjamini–Hochberg multiple hypothesis correction to reduce false-discovery rate). Within the same 5746 TCGA profiles, 2740 TCGA patients were identified as having one or more potentially oncogenic single-nucleotide variant (SNV) mutation within an established 50-gene hotspot panel. Of the 50 genes, SNVs within 15 were found to be significantly associated with differential expression of at least one IRM after adjusting for tissue enrichment; six were confirmed significant associations in an independent set of 2739 clinical cases from NantHealth.

Conclusions

Logically combining ICIs with targeted therapies may offer unique treatment strategies for patients with cancer. The presence of specific mutations impacts the expression of IRMs, an observation of potential importance for selecting combinations of gene- and immune-targeted therapeutics.

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Altered actionable genes correlated with specific checkpoint transcripts.

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Associations between IRMs and altered genes were validated in independent datasets.

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Combining immune- and gene-targeted drugs based on IRM/gene correlations merits study.