Enzymatically inactive chitinase-like protein CHI3L1 drives inflammatory response and promotes tumor progression. However, its role in gastric cancer (GC) tumorigenesis and metastasis has not yet been fully elucidated. We determined the significance of CHI3L1 expression in patients with GC. We also explored an as-yet unknown receptor of CHI3L1 and investigated the involved signaling in GC metastasis. CHI3L1 expression was evaluated by immunoblotting, tissue microarray-based immunohistochemistry analysis (n = 100), and enzyme linked immunosorbent assay (ELISA) (n = 150). The interactions between CD44 and CHI3L1 or Interleukin-13 receptor alpha 2 (IL-13Rα2) were analyzed by co-immunoprecipitation, immunofluorescence co-localization assay, ELISA, and bio-layer interferometry. The roles of CHI3L1/CD44 axis in GC metastasis were investigated in GC cell lines and experimental animal model by gain and loss of function. CHI3L1 upregulation occurred during GC development, and positively correlated with GC invasion depth, lymph node status, and tumor staging. Mechanically, CHI3L1 binding to CD44 activated Erk and Akt, along with β-catenin signaling by phosphorylating β-catenin at Ser552 and Ser675. CD44 also interacted with IL-13Rα2 to form a complex. Notably, CD44v3 peptide and protein, but not CD44v6 peptide or CD44s protein, bound to both CHI3L1 and IL-13Rα2. Our in vivo and in vitro data further demonstrated that CHI3L1 promoted GC cell proliferation, migration, and metastasis. CHI3L1 binding to CD44v3 activates Erk, Akt, and β-catenin signaling, therefore enhances GC metastasis. CHI3L1 expression is a novel biomarker for the prognosis of GC, and these findings have thus identified CHI3L1/CD44 axis as a vital pathway and potential therapeutic target in GC.

Background: In colorectal cancer (CRC), tumor deposits (TD) have been used to guide the N staging only in node-negative patients. It remains unknown about the prognostic value of TD in combination with positive lymph node ratio (LNR) in stage III CRC. Patients and methods: The authors analyzed data from 31 139 eligible patients diagnosed with stage III CRC, including 30 230 from the Surveillance, Epidemiology, and End Results (SEER) database as a training set and 909 from two Chinese hospitals as a validation set. The associations of TD and LNR with cancer-specific survival (CSS) and overall survival (OS) were evaluated using the Kaplan–Meier method and Cox regression models. Results: Both TD-positive and high LNR (value ≥0.4) were associated with worse CSS in the training [multivariable hazard ratio (HR), 1.50; 95% CI: 1.43–1.58 and HR, 1.74; 95% CI: 1.62–1.86, respectively] and validation sets (HR, 1.90; 95% CI: 1.41–2.54 and HR, 2.01; 95% CI: 1.29–3.15, respectively). Compared to patients with TD-negative and low LNR (value<0.4), those with TD-positive and high LNR had a 4.09-fold risk of CRC-specific death in the training set (HR, 4.09; 95% CI: 3.54–4.72) and 4.60-fold risk in the validation set (HR, 4.60; 95% CI: 2.88–7.35). Patients with TD-positive/H-LNR CRC on the right side had the worst prognosis (P<0.001). The combined variable of TD and LNR contributed the most to CSS prediction in the training (24.26%) and validation (32.31%) sets. A nomogram including TD and LNR showed satisfactory discriminative ability, and calibration curves indicated favorable consistency in both the training and validation sets. Conclusions: TD and LNR represent independent prognostic predictors for stage III CRC. A combination of TD and LNR could be used to identify those at high-risk of CRC deaths.

Human epidermal growth factor receptor 2 (HER2) -positive breast cancer exhibits aggressive clinical progression and unfavorable outcomes. While HER2-directed agents and immune checkpoint inhibitors have transformed clinical management, persistent challenges include suboptimal response rates and acquired resistance. These limitations underscore the critical need for alternative therapeutic approaches. Our investigation, leveraging single-cell transcriptomic data derived from both healthy and neoplastic breast tissues, sought to elucidate the specific cellular subsets and regulatory pathways that contribute to the aggressive characteristics of HER2 + breast cancer. Subsequent validation of these findings was achieved through the incorporation of bulk transcriptomic datasets from various breast cancer cohorts, alongside spatial transcriptomics data pertaining to HER2 + breast malignancies, and comprehensive multiplex immunohistochemistry examinations. We identified a marked elevation of SPP1 + macrophages, displaying an M2-like immune-suppressive phenotype, within the tumor microenvironment. These particular macrophage populations were deeply implicated in modulating T cell activities and consistently correlated with adverse patient outcomes. At a mechanistic level, we ascertained that SPP1 + macrophages bolster the immune-suppressive capacity of Tregs via engagement of the CD86-CTLA4 axis, thereby facilitating the advancement of the tumor. Furthermore, the strong association between SPP1 + macrophages and both unfavorable prognosis and advanced disease stages was corroborated in an independent, in-house HER2 + breast cancer patient group. Our work uncovered the pro-tumorigenic capabilities and underlying molecular mechanisms of SPP1 + macrophages in HER2 + breast cancer, suggesting these cells represent a promising new therapeutic target.

Background and aims. Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related deaths worldwide. The role of leucine-rich repeats containing G protein-coupled receptor 4 (LGR4) in HCC remains unclear. Metformin can prevent and control the development of a variety of cancers, especially in HCC. Alternative splicing (AS) can produce many cancer-driving genes. We aim to uncover that metformin regulates HCC development through alternative splicing of LGR4. Methods. First, the expression of LGR4 in HCC tumor tissues and cell lines was detected by western blotting and immunofluorescence. The ability of cell proliferation, migration, and invasion was detected with CCK8, wound-healing, and transwell assays when overexpressing LGR4 or treating with metformin. The β-catenin expression was detected by immunofluorescence. In order to investigate novel AS-associated LGR4, we discarded LGR4 isoforms from GSO databases. We used siRNA to knock down the specific isoform to check the cell proliferation, migration, and invasion when treated with metformin. Results. The level of LGR4 expression was higher in HCC cell lines and tumor tissues. The HCC cell proliferation, migration, and invasion were increased when overexpressing LGR4, which could be reduced by metformin treatment. The GEO database (GSE190076) showed that LGR4 had switching properties in HCC cell lines treated with metformin. We used siRNA to knock down the specific isoform, and the result showed that the specific isoform siRNA could promote the inhibition of cell invasion caused by metformin treatment. Conclusions. LGR4 could promote the ability of cell proliferation, migration, and invasion in HCC, which could be reduced by metformin through alternative splicing.

Breast cancer (BRCA) is the most fatal malignancy of women. Immunotherapy has greatly improved the prognosis of advanced BRCA. Cellular senescence contributes to tumorigenesis and suppresses anti-cancer immunity. Identification of senescence-relevant long noncoding RNAs (SRlncRNAs) signature may benefit the predictions of prognosis and response to immunotherapy of BRCA. RNA-seq, mutation, and clinical data of BRCA were acquired from public databases. SRlncRNAs were screened using univariate Cox regression analysis. Consensus clustering classified BRCA patients into 2 clusters, and the differences of overall survival (OS) and immune status between the 2 clusters were analyzed by survival analysis, CIBERSORT, and ESITIMATE. The SRlncRNAs signature was constructed by least absolute shrinkage and selection operator (LASSO) regression analysis, and BRCA patients were divided into 2 risk groups. Enrichment analyses were performed to explore the cancer- and immunotherapy-relevant pathways. Transcriptome analysis was performed to investigate the differences of OS, immune infiltration, and ESITIMATE score of the 2 groups. Genome analysis was applied to investigate the differences of somatic mutation, tumor mutation burden (TMB) and microsatellite instability (MSI) between the 2 risk groups. A nomogram combined with calibration curves and decision curve analysis (DCA) was established for better clinical decision. Tumor Immune Dysfunction and Exclusion (TIDE) score and IMvigor-210 were applied for the predicting of response to immunotherapy. Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) and the Cancer Therapeutics Response Portal resource (CTRP) databases were used for drug susceptibility analysis. Ten prognostic SRlncRNAs were identified and BRCA patients were divided into 2 clusters. Cluster 1 had better OS with anti-tumor immune microenvironment. The high-risk BRCA had poorer OS in the Cancer Genome Atlas (TCGA) training cohort, which was also verified by TCGA validation cohort and GSE20685 validation cohort. Low-risk patients also had anti-tumor immune microenvironment. Genome analysis demonstrated that the high-risk group had significant higher TMB. High-risk BRCA were more susceptive to immunotherapy according to the TIDE score and IMvigor-210. Finally, drug susceptibility analysis showed that 6 compounds were sensitive to high-risk BRCA patients. We developed and verified an original SRlncRNAs signature by multi-omics analysis, which could serve as a prognosis and immunotherapy predictor for BRCA.