Pro-inflammatory TNF-α and IFN-γ Promote Tumor Growth and Metastasis via Induction of MACC1
Bibliographic record
Abstract
Colorectal cancer (CRC) is one of the most common malignancies worldwide. Early stage CRC patients have a good prognosis. If distant metastasis occurs, the 5-year survival drops below 10%. Despite treatment success over the last decades, treatment options for metastatic disease are still limited. Therefore, novel targets are needed to foster therapy of advanced stage CRC patients and hinder progression of early stage patients into metastasis. A novel target is the crucial oncogene Metastasis-Associated in Colon Cancer 1 (MACC1) involved in molecular pathogenesis of CRC metastasis. MACC1 induces cell proliferation and motility, supports cellular survival and rewires metabolism resulting in increased metastasis in vivo. MACC1 is a prognostic biomarker for CRC and more than 20 solid cancer entities. Inflammation plays a pivotal role in tumorigenesis, tumor progression and metastasis. For CRC, inflammatory bowel disease and ulcerative colitis are important inflammation associated risk factors. Certain cytokines, such as TNF- and IFN-, are key factors of the inflammatory process to CRC. Knowledge of the connection between inflammation and MACC1-driven tumors remains unclear. Gene expression analysis of CRC cells after cytokine stimulation was analyzed by qRT-PCR and Western blot. Cellular motility was assessed by Boyden chamber assays. MACC1 promoter activity after stimulation with pro-inflammatory cytokines was measured using promoter-luciferase constructs. To investigate signal transduction from receptor to effector molecules, blocking experiments using neutralizing antibodies and knockdown experiments were performed. Following TNF- stimulation, MACC1 and c-Jun expression were significantly increased at the mRNA and protein level. Knockdown of c-Jun reduced MACC1 inducibility following TNF- stimulation. TNF promoted MACC1-induced cell migration that was reverted following MACC1 knockdown. Moreover, MACC1 and c-Jun expression were downregulated by blocking TNFR1, but not TNFR2. Knock down of the NF-B subunit, p65, reduced basal MACC1 and c-Jun mRNA expression levels. Adalimumab, a clinically approved monoclonal anti-TNF- antibody, hindered MACC1 induction. The present study highlights that TNF- regulates the induction of MACC1 via the NF-B subunit p65 and the transcription factor c-Jun in CRC cells. This finding unravels a novel signaling pathway upstream of MACC1 and provides a potential therapeutic target for treatment of CRC patients with an associated inflammation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".