Abstract 2255: The impact of primary immunodeficiency informed molecular landscape on the biology and prognosis of refractory malignancies
Bibliographic record
Abstract
Abstract Introduction: Cancer is one of the most common causes of death in patients with primary immunodeficiencies (PIDs). The immune surveillance concept postulates that PIDs are an important contributor to cancer growth and outcomes. Although several immunodeficiency syndromes are known to be associated with malignancies in children and adults, currently, the molecular mechanisms that link immune functions to cancers are poorly understood. Here we describe distinct molecular characteristics in adult cancers with respect to PID-associated genes that impact survival outcomes in affected patients. Methods: In this study, we integrated transcriptome data of 28 adult cancers from the public database The Cancer Genome Atlas (TCGA) with respective healthy tissues as control from the Genotype-Tissue Expression (GTEx) project. Unified datasets integrating GTEx healthy samples and TCGA cancer data were provided by the Recount2 protocol and differential expression analyses (DEA) were carried out using the integrated limma-voom and edgeR pipelines in the TCGAbiolinks R package. Gene ontology (GO) enrichment analyses were performed using the pathfindR R package. Mutational and clinical data of adult cancer patient samples in TCGA and the AACR Project GENIE were consolidated using cBioPortal and the maftools R package. PID-associated genes were curated from the latest registry by the European Society for Immunodeficiencies (ESID). Results: Of 307 PID-associated genes, 151 (32.0%) up-regulated and 88 (18.6%) down-regulated genes were identified across the 28 unified TCGA-GTEx datasets. From the identified differentially expressed gene sets, GO analysis revealed enrichment in immunological pathways related to complement and coagulation cascades (27/28 datasets), systemic lupus erythematosus (25/28), in addition to Fanconi anemia (22/28). The greatest frequency of mutations in PID-associated genes from the consolidated TCGA and GENIE datasets were KRAS (14.83%), KMT2D (10.03%), TERT (8.99%), PRKDC (7.59%) and PTEN (6.18%) across all cancer types, with a total of 259 affected PID-associated genes. Survival analyses using Cox proportional-hazards and Kaplan-Meier models will assess the clinical implications of the identified molecular alterations in affected patients. Conclusion: Our integrative approach aids in the elucidation of molecular mechanisms that bridge PIDs to tumour biology. These data may help identify important biomarkers and potential future targeted therapeutics. Citation Format: Son Tran, Luis Murguia-Favela, Aru Narendran. The impact of primary immunodeficiency informed molecular landscape on the biology and prognosis of refractory malignancies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2255.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".