The Roles of Immune Cells Derived from Clonal Hematopoiesis in Colorectal Cancer Metastasis
Bibliographic record
Abstract
[Backgrounds] Clonal hematopoiesis (CH) has been observed in over 20% of patients diagnosed with solid cancers, and it has been associated with a poor prognosis in most cases, with the exception of colorectal cancer (CRC) patients who tend to have a favorable prognosis. Among the various gene mutations detected in CH, TET2 mutations are particularly prevalent. Previous research has demonstrated that the impact of TET2-mutated CH immune cells depends on the specific types of cancer tissues involved. Specifically, studies have shown that Tet2-KO myeloid cells can inhibit the progression of melanoma while promoting the growth of hepatoma and lung cancers. However, there is a limited understanding of the roles of TET2-mutated CH immune cells on CRC progression. [ Methods] We conducted an experiment focusing on CRC and CH using CRC organoid cells transplanted into the spleens of different types of Tet2 conditional knockout mice: VAV1Cre (with Tet2 gene deletion in all hematopoietic cells), LysMCre (myeloid cells), CD19Cre (B lymphocytes), and CD4Cre (T lymphocytes). After a period of 30 days, we collected livers for analysis. The extent of liver metastasis tumor burden (LMTB) was determined by counting the number of tumor foci on 10 hematoxylin-stained slides, with an interval of 80 μm between each slide. We utilized immunohistochemistry (IHC) and flow cytometry (FC) to analyze immune cells. The number of positive cells was automatically counted in 10 fields at 20x magnification. Furthermore, we performed whole transcriptome analysis (WTA) on sorted CD4+, CD8+, CD11b+, and CD19+ cells, respectively. [Results] LMTB was significantly lower in VAV1Cre and CD4Cre mice compared to the control mice ( VAV1Cre vs. control: 55.65±35.62 vs. 89.93±34.57 foci/1000 mm², p<0.05; CD4Cre vs. control: 50.19±30.39 vs. 85.98±7.92 foci/1000 mm², p<0.05). However, the LMTB of CD19Cre and LysMCre mice was comparable to that of control mice. The differential gene expression of WTA of CD8+ cells revealed that 243 genes were up-regulated, while 189 genes were down-regulated in both of VAV1Cre and CD4Cre mice compared to the control mice. Among the down-regulated genes, a gene group consisting of Pdcd1, Tigit, Lag3 and Havcr2, which encode inhibitory molecules associated with exhausted T cells exhibited enrichment (Enrichment score =3.77) based on the analysis using DAVID. Ingenuity Pathway Analysis further indicated that these molecules were downregulated by the upstream regulator TOX. Furthermore, T cell exhaustion signaling pathways were downregulated in both VAV1Cre and CD4Cre mice using gene set enrichment analysis. The immunofluorescence results demonstrated that the number of CD8-T cells expressing PDCD1 and HAVCR2 was decreased in VAV1Cre mice and CD4Cre compared to the control mice ( VAV1Cre and CD4Cre vs control; 5.91±2.50 and 12.86±5.3 vs. 35.15±8.21 cells/100 CD8-T cells, p<0.01 for PDCD1; 4.51±4.06 and 13.65±7.84 vs. 24.51±9.94 cells/100 CD8-T cells, p<0.01 for HAVCR2). Moreover, the number of CD8-T cells expressing TOX was also significantly decreased in VAV1Cre mice and CD4Cre compared to the control mice ( VAV1Cre and CD4Cre vs control; 5.19±7.48 and 11.31±14.43 vs. 35.15±16.50 cells/100 CD8-T cells; p<0.01). [ Conclusions] The depletion of the Tet2 gene in hematopoietic cells resulted in a reduction of exhausted CD8+ T cells and suppressed the liver metastasis of CRC organoid cells. These findings provide insights into the favorable prognosis observed in CRC patients with CH. Considering the high prevalence of CH in cancer patients, our results suggest that studying the roles of CH-immune cells could shed new light on understanding the cancer microenvironment from a novel perspective.
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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) | 0.001 | 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".