KIF18B as a regulator in tumor microenvironment accelerates tumor progression and triggers poor outcome in hepatocellular carcinoma

Kinesin family member 18B activates mTORC1 signaling via actin gamma 1 to promote the recurrence of human hepatocellular carcinoma

The mechanistic target of rapamycin complex 1 (mTORC1) signaling pathway is frequently reported to be hyperactivated in hepatocellular carcinoma (HCC) and contributes to HCC recurrence. However, the underlying regulatory mechanisms of mTORC1 signaling in HCC are not fully understood. In the present study, we found that the expression of kinesin family member 18B (KIF18B) was positively correlated with mTORC1 signaling in HCC, and the upregulation of KIF18B and p-mTOR was associated with a poor prognosis and HCC recurrence. Utilizing in vitro and in vivo assays, we showed that KIF18B promoted HCC cell proliferation and migration through activating mTORC1 signaling. Mechanistically, we identified Actin gamma 1 (γ-Actin) as a binding partner of KIF18B. KIF18B and γ-Actin synergistically modulated lysosome positioning, promoted mTORC1 translocation to lysosome membrane, and prohibited p70 S6K from entering lysosomes for degradation, which finally led to the enhancement of mTORC1 signaling transduction. Moreover, we found that KIF18B was a direct target of Forkhead box M1, which explains the potential mechanism of KIF18B overexpression in HCC. Our study highlights the potential of KIF18B as a therapeutic target for the treatment of HCC.

Multi-omics analysis reveals the association between elevated KIF18B expression and unfavorable prognosis, immune evasion, and regulatory T cell activation in nasopharyngeal carcinoma

Background

Nasopharyngeal carcinoma (NPC) is prevalent in Southern China. The expression profile and functions of kinesin family member 18B (KIF18B) remain unclear in NPC.

Methods

Bulk and single-cell transcriptome data for NPC were downloaded. KIF18B expression differences in NPC and normal tissues and its prognostic value were validated by immunohistochemistry and Cox model. We performed multi-faceted functional enrichment analysis on KIF18B. Immune infiltration was analyzed comprehensively by the CIBERSORT, EPIC, and quanTIseq algorithms and the BisqueRNA package and confirmed by immunofluorescence assay. The intercellular communication were investigated by the CellChat package. We explored the dynamics of KIF18B expression by pseudotime trajectory. M6A modification analysis rely on SRAMP platform. The treatment response were evaluated by Tumor Immune Dysfunction and Exclusion (TIDE) score, immunophenoscore and IC50 value.

Results

KIF18B overexpression in NPC led to unfavorable prognosis, and significantly associated with advanced T, N, and stage classifications. Functional analysis demonstrated that KIF18B was involved in immune suppression, epithelial-mesenchymal transition (EMT), N6-methyladenosine (m6A) modification and therapeutic responses. The deconvolution algorithm indicated that activated regulatory T cells (Tregs) had the strongest positive correlation with KIF18B among immune cells (R = 0.631). Validated by immunofluorescence assay, the high KIF18B expression group displayed a notable rise in Tregs infiltration, accompanied by a substantial decrease in the infiltration of CD8+ T cells and macrophages. In the intercellular communication network, malignant cells with high KIF18B expression implicated in more interactions, and activated and recruited Tregs by modulating cytokines, chemokines, and immune checkpoints. KIF18B was upregulated in more advanced malignant cells and influenced EMT by regulating ITGA6, VIM, and ZEB1/2. KIF18B expression was positively related to m6A "writer" and "reader" genes, and negatively related to "eraser" genes. The KIF18B high expression group exhibited a higher TIDE score and elevated IC50 values for the commonly used chemotherapy drugs, gemcitabine, oxaliplatin, and 5-fluorouracil.

Conclusion

KIF18B is a significant prognostic marker in NPC, and may modulate immune evasion and EMT. M6A modification may account for the aberrant overexpression of KIF18B in NPC. Furthermore, KIF18B may predict response to immunotherapy and chemotherapy.

Integrative Histology-Genomic Analysis Predicts Hepatocellular Carcinoma Prognosis Using Deep Learning

Cancer prognosis analysis is of essential interest in clinical practice. In order to explore the prognostic power of computational histopathology and genomics, this paper constructs a multi-modality prognostic model for survival prediction. We collected 346 patients diagnosed with hepatocellular carcinoma (HCC) from The Cancer Genome Atlas (TCGA), each patient has 1-3 whole slide images (WSIs) and an mRNA expression file. WSIs were processed by a multi-instance deep learning model to obtain the patient-level survival risk scores; mRNA expression data were processed by weighted gene co-expression network analysis (WGCNA), and the top hub genes of each module were extracted as risk factors. Information from two modalities was integrated by Cox proportional hazard model to predict patient outcomes. The overall survival predictions of the multi-modality model (Concordance index (C-index): 0.746, 95% confidence interval (CI): ±0.077) outperformed these based on histopathology risk score or hub genes, respectively. Furthermore, in the prediction of 1-year and 3-year survival, the area under curve of the model achieved 0.816 and 0.810. In conclusion, this paper provides an effective workflow for multi-modality prognosis of HCC, the integration of histopathology and genomic information has the potential to assist clinical prognosis management.