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Summary: Accurate tumor diagnosis by pathologists relies on identifying specific morphological characteristics. However, summarizing these unique morphological features in tumor classifications can be challenging. Although deep learning models have been extensively studied for tumor classification, their indirect and subjective interpretation obstructs pathologists from comprehending the model and discerning the morphological features accountable for classifications. In this study, we introduce a new approach utilizing Style Generative Adversarial Networks, which enables a direct interpretation of deep learning models to detect significant morphological characteristics within datasets representing patients with deficient mismatch repair/microsatellite instability-high gastric cancer. Our approach effectively identifies distinct morphological features crucial for tumor classification, offering valuable insights for pathologists to enhance diagnostic accuracy and foster professional growth.

Abstract RNA-binding proteins (RBPs) are key regulators of gene expression. RBP dysregulation is reported to play essential roles in tumorigenesis. However, the role of RBPs in urothelial carcinoma of the bladder (UCB) is only starting to be unveiled. Here, we comprehensively assessed the mRNA expression landscape of 104 RBPs from two independent UCB cohorts, Sun Yat-sen University Cancer Center (SYSUCC) and The Cancer Genome Atlas (TCGA). Fragile X-related gene 1 (FXR1) was identified as a novel cancer driver gene in UCB. FXR1 overexpression was found to be related to the poor survival rate in the SYSUCC and TCGA cohorts. Functionally, FXR1 promotes UCB proliferation and tumorigenesis. Mechanistically, FXR1 serves as a platform to recruit CFIm25 and CFIm68, forming a novel 3′ processing machinery that functions in sequence-specific poly(A) site recognition. FXR1 affects the 3′ processing of Tumor necrosis factor receptor-associated factor 1 (TRAF1) mRNA, which leads to nuclear stabilization. The novel regulatory relationship between FXR1 and TRAF1 can enhance cell proliferation and suppress apoptosis. Our data collectively highlight the novel regulatory role of FXR1 in TRAF1 3′ processing as an important determinant of UCB oncogenesis. Our study provides new insight into RBP function and provides a potential therapeutic target for UCB.

Cancer stem-like cells (CSLCs) acquire enhanced immune checkpoint responses to evade immune cell killing and promote tumor progression. Here we showed that signal regulatory protein γ (SIRPγ) determined CSLC properties and immune evasiveness in a small population of lung adenocarcinoma (LUAD) cancer cells. A SIRPγhi population displayed CSLC properties and transmitted the immune escape signal through sustaining CD47 expression in both SIRPγhi and SIRPγlo/– tumor cells. SIRPγ bridged MST1 and PP2A to facilitate MST1 dephosphorylation, resulting in Hippo/YAP activation and leading to cytokine release by CSLCs, which stimulated CD47 expression in LUAD cells and consequently inhibited tumor cell phagocytosis. SIRPγ promoted tumor growth and metastasis in vivo through YAP signaling. Notably, SIRPγ targeting with genetic SIRPγ knockdown or a SIRPγ-neutralizing antibody inhibited CSLC phenotypes and elicited phagocytosis that suppressed tumor growth in vivo. SIRPG was upregulated in human LUAD and its overexpression predicted poor survival outcome. Thus, SIRPγhi cells serve as CSLCs and tumor immune checkpoint–initiating cells, propagating the immune escape signal to the entire cancer cell population. Our study identifies Hippo/YAP signaling as the first mechanism by which SIRPγ is engaged and reveals that targeting SIRPγ represents an immune- and CSLC-targeting strategy for lung cancer therapy.

Gastric cancer is a malignant tumor with high morbidity and mortality worldwide. However, increasing evidences have revealed the correlation between the glycolysis process and tumorigenesis. This study is aim to develop a list of glycolysis-related genes for risk stratification in gastric cancer patients. We included 500 patients’ sample data from GSE62254 and GSE26942 datasets, and classified patients into training (n = 350) and testing sets (n = 150) at a ratio of 7: 3. Univariate and multivariate Cox regression analysis were performed to screen genes having prognostic value. Based on HALLMARK gene sets, we identified 9 glycolysis-related genes (BPNT1, DCN, FUT8, GMPPA, GPC3, LDHC, ME2, PLOD2, and UGP2). On the basis of risk score developed by the 9 genes, patients were classified into high- and low-risk groups. The survival analysis showed that the high-risk patients had a worse prognosis ( p < 0.001). Similar finding was observed in the testing cohort and 2 independent cohorts (GSE13861 and TCGA-STAD, all p < 0.001). The multivariate Cox regression analysis showed that the risk score was an independent prognostic factor for overall survival ( p < 0.001). Furthermore, we constructed a nomogram that integrated the risk score and tumor stage, age, and adjuvant chemotherapy. Through comparing the results of the receiver operating characteristic curves and decision curve analysis, we found that the nomogram had a superior predictive accuracy than conventional TNM staging system, suggesting that the risk score combined with other clinical factors (age, tumor stage, and adjuvant chemotherapy) can develop a robust prediction for survival and improve the individualized clinical decision making of the patient. In conclusion, we identified 9 glycolysis-related genes from hallmark glycolysis pathway. Based on the 9 genes, gastric cancer patients were separated into different risk groups related to survival.

Skeletal muscle is rich in lymphatic vessels, with an abundant blood supply, and it is an infrequent site of cancer metastasis. Previous studies have demonstrated that enhanced secretion of MyoD may occur when skeletal muscle is injured or becomes cancerous. It was hypothesized that MyoD may act as an endogenous cytokine to inhibit the proliferation of cancer cells. To verify the possible effect of this protein on tumor cell proliferation, C2C12 mouse skeletal muscle cells and 4T1 mouse breast cancer cells were co-cultured using embedded Transwell plates. Following co-culture, cell cycle analysis revealed that C2C12 muscle cells were able to inhibit the proliferation of the breast cancer cells. Subsequently, MyoD was silenced in C2C12 cells to assess its effect on 4T1 cell proliferation. Following co-culture with MyoD-silenced cells, a 5-ethynyl-20-deoxyuridine assay indicated that MyoD silencing prevented the reduction in proliferation of 4T1 cells induced by untransfected C2C12 cells. In summary, the results indicated that MyoD inhibits the proliferation of breast cancer cells and may be a tumor suppressor factor. [ABSTRACT FROM AUTHOR]