Liver metastases represent a late-stage manifestation of numerous cancers, often associated with poor patient prognosis. Kupffer cells (KCs), resident liver macrophages, play a critical role in liver metastasis (LM). However, the mechanisms by which the polarization of KCs facilitate colorectal cancer (CRC) liver metastases remain elusive. Here, we established a CRC liver metastasis mouse model and employed a co-culture system, found that KCs were recruited and polarized to M2 phenotype. We isolated and purified highly metastatic cell lines to reveal potential changes in CRC cells during metastasis. Through bulk RNA sequencing, we identified and validated CXCL16 as a positive mediator in liver-metastatic CT26-LM cells that induced an M2-like KC phenotype. Knock down of CXCL16 reduced the M2 polarization of KCs and inhibited the formation of liver metastasis lesions. Next, this polarization process was shown to be achieved through the PI3K/AKT/FOXO3a pathway. Further investigation revealed FOXO3a transcriptionally activates CD206(MRC1) in this process. Pharmacological inhibition of the CXCL16-PI3K-FOXO3a axis to disrupt the polarization of KCs attenuated CRC liver metastasis in vivo. Our findings collectively indicate that targeting the CXCL16/PI3K/AKT/FOXO3a pathway in KCs may represent a promising therapeutic strategy for preventing CRC liver metastasis.

TGF-beta signaling is a key regulator of immunity and multiple cellular behaviors in cancer. However, the prognostic and therapeutic role of TGF-beta signaling-related genes in ovarian cancer (OV) remains unexplored. Data of OV used in the current study were sourced from TCGA and GEO databases. Consensus clustering was applied to classify OV patients into different clusters using TGF-beta signaling-related genes. Differentially expressed genes (DEGs) between different clusters were screened by the “limma” R package. Prognostic genes were screened from DEGs by univariate Cox regression, followed by the construction of the TGF-beta signaling-related score. The prognostic value of TGF-beta signaling-related score was evaluated in both training and testing OV cohorts. Moreover, the immune status, GSEA and therapeutic response between low- and high-score groups were performed to further reveal the potential mechanisms. By consensus clustering, OV patients were classified into two clusters with different tumor immune environments. After differential expression and univariate Cox regression analyses, GMPR, PIEZO1, EMP1, CXCL13, GADD45B, SORCS2, FOSL2, PODN, LYNX1 and SLC38A5 were selected as prognostic genes. Using PCA algorithm, the TGF-beta signaling-related score of OV patients was calculated based on prognostic genes. Then OV patients were divided into low- and high-TGF-beta signaling-related score groups. We observed that the two score groups had significantly different survivals, tumor immune environments and expressions of immune checkpoints. In addition, GSEA results showed that immune-related pathways and biological processes, like chemokine signaling pathway, TNF signaling pathway and T cell migration were significantly enriched in the low-score group. Moreover, patients in the low- and high-score groups had remarkably different sensitivity to chemo- and immunotherapy. For the first time, our study identified ten prognostic genes associated with TGF-beta signaling, constructed a prognostic TGF-beta signaling-related score and investigated the effect of TGF-beta signaling-related score on OV immunity and therapy. These findings may enrich our knowledge of the TGF-beta signaling in OV prognosis and help to improve the prognosis prediction and treatment strategies in OV.

Background: Transarterial chemoembolization (TACE) is the first-line treatment for patients with advanced HCC, but there are limited studies on the microenvironment alterations caused by TACE. Methods: Six fresh HBV-related HCC specimens with or without TACE intervention were used to perform single-cell RNA sequencing. The 757 bulk samples from 3 large-scale multicenter cohorts were applied for comprehensive analysis. The biological functions of the biomarkers were further validated by phenotypic experiments. Results: Using single-cell RNA sequencing analysis, we delineated the global cell atlas of post-TACE and demonstrated elevated tumor heterogeneity and an enhanced proinflammatory microenvironment induced by TACE. Cell-cell communication analysis revealed that markedly elevated interactions between NABP1+ malignant hepatocytes, neutrophils, and CD8+ T cells after TACE might accelerate the shift from CD8+ effector memory T cells to CD8+ effector T cells. This result was substantiated by the developmental trajectory between the 2 and dramatically decreased resident scores along the pseudotemporal trajectory. Integrating bulk data, we further found that the increased estimated proportion of NABP1+ malignant hepatocytes was related to poor TACE response and dismal prognosis, and its biomarker role could be replaced by NABP1. In vitro, multiple biological experiments consistently verified that NABP1 knockdown significantly inhibited the proliferation and migration of HCC cells. Conclusions: Based on our depicted global map of post-TACE, we confirmed that the enhanced interactions within the microenvironment after TACE may be the culprits for postoperative progression. NABP1 may become an attractive tool for the early identification of patients sensitive to first-line TACE in clinical practice.

We found better liver graft regeneration with hypothermic machine perfusion (HMP) compared with static cold storage (SCS) for the first time in our pilot study, but the underlying mechanisms are unknown. Upregulated heme oxygenase‐ (HO‐) 1 expression has been reported to play a pivotal role in promoting hepatocyte proliferation. Here, we evaluated the novel role of HO‐1 in liver graft protection by HMP. Rats with a heterozygous knockout of HO‐1 (HO‐1^+/−) were generated and subjected to 3 h of SCS or HMP pre‐half‐size liver transplantation (HSLT) in vivo or 6 h of SCS or HMP in vitro; control rats were subjected to the same conditions (HO‐1^+/+). We found that HSLT induced significant elevation of the HO‐1 protein level in the regenerated liver and that HO‐1 haplodeficiency resulted in decreased proliferation post‐HSLT. Compared with SCS, HMP induced significant elevation of the HO‐1 protein level along with better liver recovery, both of which were reduced by HO‐1 haplodeficiency. HO‐1 haplodeficiency‐induced decreased proliferation was responsible for the attenuated regenerative ability of HMP. Mechanistically, HO‐1 haploinsufficiency resulted in suppression of hepatocyte growth factor (HGF)/Akt activity. Our results suggest that inhibition of HO‐1 mitigates HMP‐induced liver recovery effects related to proliferation, in part, by downregulating the HGF‐Akt axis.

Identification and Validation of a Novel Tertiary Lymphoid Structures-Related Prognostic Gene Signature in Hepatocellular Carcinoma

We aimed to investigate the prognostic role of CEACAM1 and to construct a radiomic model to predict CEACAM1 expression and prognosis in ovary cancer (OC). Sequencing data and CT scans in OC were sourced from TCGA and TCIA databases. CEACAM1 expression was assessed by Cox regression analyses, Kaplan-Meier curves and GSVA enrichment analysis. Furthermore, radiomic features were extracted from CT scans and selected by LASSO and ROC. The selected radiomic features were used to construct a radiomic model to predict CEACAM1 expression. In addition, the radiomic score (RS) and its relationship with OC survival were investigated by Kaplan-Meier and ROC curves. At last, RS and clinical features were included into LASSO, using nomogram to predict OC prognosis. Cox regression analyses showed that CEACAM1 expression was an independent prognostic factor and associated with immune cell infiltration in OC. By LASSO and ROC, six radiomic features were selected and used to construct a radiomic model. The PR, calibration, DCA and ROC curves revealed the good performance and clinical utility of the radiomic model to predict CEACAM1 expression. In addition, RS based on radiomic features was found to be associated with OC survival. At last, a nomogram based on RS, age, chemotherapy and tumor residual disease was constructed and was found to have high accuracy in predicting OC prognosis. For the first time, our study constructed a radiomic model to predict CEACAM1 expression and prognosis of OC patients. Those findings may guide novel diagnosis and treatment for OC patients.