Macrophages are a dominant leukocyte population in the tumor microenvironment and actively promote cancer progression. However, the molecular mechanism underlying the role of macrophages remains poorly understood. Here we show that polarized M2 macrophages enhance 3-phosphoinositide-dependent protein kinase 1 (PDPK1)-mediated phosphoglycerate kinase 1 (PGK1) threonine (T) 243 phosphorylation in tumor cells by secreting interleukin-6 (IL-6). This phosphorylation facilitates a PGK1-catalyzed reaction toward glycolysis by altering substrate affinity. Inhibition of PGK1 T243 phosphorylation or PDPK1 in tumor cells or neutralization of macrophage-derived IL-6 abrogates macrophage-promoted glycolysis, proliferation, and tumorigenesis. In addition, PGK1 T243 phosphorylation correlates with PDPK1 activation, IL-6 expression, and macrophage infiltration in human glioblastoma multiforme (GBM). Moreover, PGK1 T243 phosphorylation also correlates with malignance and prognosis of human GBM. Our findings demonstrate a novel mechanism of macrophage-promoted tumor growth by regulating tumor cell metabolism, implicating the therapeutic potential to disrupt the connection between macrophages and tumor cells by inhibiting PGK1 phosphorylation.

A key feature of TGF-β signaling activation in cancer cells is the sustained activation of SMAD complexes in the nucleus; however, the drivers of SMAD activation are poorly defined. Here, using human and mouse breast cancer cell lines, we found that oncogene forkhead box M1 (FOXM1) interacts with SMAD3 to sustain activation of the SMAD3/SMAD4 complex in the nucleus. FOXM1 prevented the E3 ubiquitin-protein ligase transcriptional intermediary factor 1 γ (TIF1γ) from binding SMAD3 and monoubiquitinating SMAD4, which stabilized the SMAD3/SMAD4 complex. Loss of FOXM1 abolished TGF-β-induced SMAD3/SMAD4 formation. Moreover, the interaction of FOXM1 and SMAD3 promoted TGF-β/SMAD3-mediated transcriptional activity and target gene expression. We found that FOXM1/SMAD3 interaction was required for TGF-β-induced breast cancer invasion, which was the result of SMAD3/SMAD4-dependent upregulation of the transcription factor SLUG. Importantly, the function of FOXM1 in TGF-β-induced invasion was not dependent on FOXM1's transcriptional activity. Knockdown of SMAD3 diminished FOXM1-induced metastasis. Furthermore, FOXM1 levels correlated with activated TGF-β signaling and metastasis in human breast cancer specimens. Together, our data indicate that FOXM1 promotes breast cancer metastasis by increasing nuclear retention of SMAD3 and identify crosstalk between FOXM1 and TGF-β/SMAD3 pathways. This study highlights the critical interaction of FOXM1 and SMAD3 for controlling TGF-β signaling during metastasis.

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Purpose: We determined the expression of mammalian target of rapamycin (mTOR) and its activated form, p-mTOR, in Chinese patients with gastric cancer and its clinical effects and underlying mechanisms. Experimental Design: Tissue microarray blocks containing gastric cancer tissue and matched noncancer gastric tissue specimens obtained from 1,072 patients were constructed. Expression of total mTOR and p-mTOR in these specimens was analyzed using immunohistochemical studies and confirmed by Western blotting. Results: The overall rates of total mTOR and p-mTOR overexpression were 50.8% (545 of 1,072) and 46.5% (499 of 1,072), respectively. The p-mTOR overexpression was significantly correlated with total mTOR overexpression. Overexpression of total mTOR protein was significantly correlated with tumor differentiation, T1/T2 tumors, and stage I/II/III disease, whereas p-mTOR overexpression was significantly correlated with lymph node metastasis and all stage disease. The Cox proportional hazards model revealed that the overexpression of p-mTOR, but not total mTOR, was an independent prognostic factor for gastric cancer. The overexpression of p-mTOR also predicted the angiogenic phenotype of human gastric cancer and regulated angiogenesis of gastric cancer cells. Conclusions: Increased activation of mTOR is frequent in human gastric cancer and overexpression of p-mTOR is an independent prognostic factor, suggesting that mTOR pathway could be a potential target for therapy of this malignancy.

ObjectiveTumour pathology contains rich information, including tissue structure and cell morphology, that reflects disease progression and patient survival. However, phenotypic information is subtle and complex, making the discovery of prognostic indicators from pathological images challenging.DesignAn interpretable, weakly supervised deep learning framework incorporating prior knowledge was proposed to analyse hepatocellular carcinoma (HCC) and explore new prognostic phenotypes on pathological whole-slide images (WSIs) from the Zhongshan cohort of 1125 HCC patients (2451 WSIs) and TCGA cohort of 320 HCC patients (320 WSIs). A ‘tumour risk score (TRS)’ was established to evaluate patient outcomes, and then risk activation mapping (RAM) was applied to visualise the pathological phenotypes of TRS. The multi-omics data of The Cancer Genome Atlas(TCGA) HCC were used to assess the potential pathogenesis underlying TRS.ResultsSurvival analysis revealed that TRS was an independent prognosticator in both the Zhongshan cohort (p<0.0001) and TCGA cohort (p=0.0003). The predictive ability of TRS was superior to and independent of clinical staging systems, and TRS could evenly stratify patients into up to five groups with significantly different prognoses. Notably, sinusoidal capillarisation, prominent nucleoli and karyotheca, the nucleus/cytoplasm ratio and infiltrating inflammatory cells were identified as the main underlying features of TRS. The multi-omics data of TCGA HCC hint at the relevance of TRS to tumour immune infiltration and genetic alterations such as the FAT3 and RYR2 mutations.ConclusionOur deep learning framework is an effective and labour-saving method for decoding pathological images, providing a valuable means for HCC risk stratification and precise patient treatment.