Thirteen tumor necrosis factor receptor superfamily gene expression in malignancies and their clinical relevance to immunotherapy: a pan-cancer analysis
Bibliographic record
Abstract
Abstract Background: Although the expression of the tumor necrosis factor receptor superfamily (TNFRSF) genes and their anticancer functions in immune cells have been well described, little is known about the regulatory mechanisms and the clinical relevance of TNFRSF family gene expression in cancer cells. Recent studies indicate that the expression of CD40 (also known as TNFRSF5) is upregulated by RAS/RAF/PI3K pathway inhibition in melanoma cells, and it has the potential to be a predictive biomarker for immune checkpoint blockade (ICB) therapy responses in multiple cancer types. Therefore, we hypothesized that 13 TNFRSF genes with structural similarities to CD40 would be associated with the RAS-mediated oncogenic signaling pathways in melanoma cells and could benefit the prediction of immunotherapy responses in a range of cancers. Furthermore, there is a paucity of comparative gene expression analyses across cancer types (pan-cancer analysis) to reveal different types of cancer that share similar and distinct expression patterns of these TNFRSF genes. Methods: We performed a pan-cancer analysis of the 13 TNFRSF genes in 18,299 samples from 23 cancer types to elucidate their expression alterations in tumorigenesis and their associations with signatures of immune cell infiltration and type I anti-tumor response, as well as the expression of oncogenes and ICB-related genes. In addition, single-cell (n = 169) and bulk (n = 37) RNA-seq data in melanoma samples with different NRAS (neuroblastoma RAS viral oncogene homolog) mutational statuses were used separately to examine the regulation of these TNFRSF genes by NRAS. Ultimately, the evaluation of these TNFRSF genes as biomarkers of immunotherapy responses in seven cancer types (n = 1,257) was performed using the Tumor Immune Dysfunction and Exclusion web platform. Results and conclusions: Our findings demonstrate a comprehensive landscape of expression alterations in the 13 TNFRSF genes across a wide range of malignancies, with an emphasis on the association of these genes with type I anti-tumor T-cell responses and oncogene expression. In melanoma, oncogenic NRAS mutations downregulate the expression of multiple TNFRSF genes at bulk and single-cell levels. Moreover, our study suggests that the expression of the 13 TNFRSF genes could be used as potential biomarkers for predicting response to ICB therapy in certain cancer types with a partially complementary role. These findings will help us better understand the role of these TNFRSF genes in cancer development and treatment, and they may lead to the identification of candidate biomarkers for future clinical research and implications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".