Impact of retrotransposon protein L1 ORF1p expression on oncogenic pathways in hepatocellular carcinoma: the role of cytoplasmic PIN1 upregulation
Bibliographic record
Abstract
BACKGROUND: Molecular characterisation of hepatocellular carcinoma (HCC) is central to the development of novel therapeutic strategies for the disease. We have previously demonstrated mutagenic consequences of Long-Interspersed Nuclear Element-1 (LINE1s/L1) retrotransposition. However, the role of L1 in HCC, besides somatic mutagenesis, is not well understood. METHODS: We analysed L1 expression in the TCGA-HCC RNAseq dataset (n = 372) and explored potential relationships between L1 expression and clinical features. The findings were confirmed by immunohistochemical (IHC) analysis of an independent human HCC cohort (n = 48) and functional mechanisms explored using in vitro and in vivo model systems. RESULTS: We observed positive associations between L1 and activated TGFβ-signalling, TP53 mutation, alpha-fetoprotein and tumour invasion. IHC confirmed a positive association between pSMAD3, a surrogate for TGFβ-signalling status, and L1 ORF1p (P < 0.0001, n = 32). Experimental modulation of L1 ORF1p levels revealed an influence of L1 ORF1p on key hepatocarcinogenesis-related pathways. Reduction in cell migration and invasive capacity was observed upon L1 ORF1 knockdown, both in vitro and in vivo. In particular, L1 ORF1p increased PIN1 cytoplasmic localisation. Blocking PIN1 activity abrogated L1 ORF1p-induced NF-κB-mediated inflammatory response genes while further activated TGFβ-signalling confirming differential alteration of PIN1 activity in cellular compartments by L1 ORF1p. DISCUSSION: Our data demonstrate a causal link between L1 ORF1p and key oncogenic pathways mediated by PIN1, presenting a novel therapeutic avenue.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".