Cancer Cell International最新文献

Purpose: We tested whether the PARP inhibitor, Olaparib, can effectively enhance radiosensitivity while inhibiting OSCC growth and metastasis in vitro and in vivo. Patient samples were used for survival validation.

Methods: The present study investigated the effect of Olaparib and ionizing radiation (IR) on clonogenic, migratory, and invasive ability in human IR-sensitive (OML1) and IR-resistant (OML1-R) OSCC cell lines. We next explored the underlying mechanism with ELISA and a Western blotting assay. Two in vivo mouse models were established to investigate the efficacy of Olaparib combined with radiotherapy (RT) on local tumor growth and lung metastasis. IL-17 A expression was confirmed in tissue specimens of OSCC patients by immunohistochemistry.

Results: We found that Olaparib, in combination with IR, substantially inhibited cell growth, migration, and invasion in vitro. Mechanistically, the Olaparib treatment significantly reduced the secretion of IL-17 A in irradiated OSCC cells by attenuating NF-κB and p38 activity. Consistently, Olaparib enhanced the radiosensitivity and, with RT, synergistically reduced both tumor growth and lung metastasis in mice. In addition, OSCC patients with high IL-17 A expression were substantially associated with an increased risk of lymph node involvement and worse survival.

Conclusions: This study has highlighted that Olaparib displays radiosensitizing and antimetastatic effects by inhibiting the IL-17 A-dependent signal. Remarkably, Olaparib could provide a remarkable anticancer efficacy to improve treatment response in OSCC patients with recurrent/metastatic disease after RT.

Ubiquitination is a prevalent post-translational modification that plays a crucial role in a wide range of pathophysiological processes, including cell proliferation, apoptosis, autophagy, immune response, and DNA damage repair. Among the enzymes involved in ubiquitination, E3 ubiquitin ligases are particularly significant, serving as key regulators of numerous diseases, including tumours. This review focuses on HECW2 (HECT, C2, and WW domain-containing E3 ubiquitin protein ligase 2, also known as NEDL2), providing a comprehensive overview of its interactors and its pathological roles in tumorous cancer and other diseases. The insights gained from this review may contribute to the development of novel treatment strategies for various diseases, particularly tumours.

Background: Breast cancer (BC) is the most common cancer in women and the leading cause of cancer-related death worldwide. This heterogeneous disease has been historically considered a non-immunogenic type of cancer. However, recent advances in immunotherapy have increased the interest in knowing the role of the immune checkpoints (IC) and other immune regulation pathways in this neoplasia.

Methods: In this retrospective study, we evaluated the correlation of mRNA expression of CTLA-4, PDCD1 (PD1), CD274 (PD-L1), PDCD1LG2 (PD-L2), CD276 (B7-H3), JAK2, and FOXO1 with clinicopathological factors and BC patient's outcome by real-time quantitative polymerase chain reaction (qPCR).

Results: Our results showed that immunoregulatory gene expression depends on BC immunophenotype being CTLA-4 and PDCD1 (PD1) overexpressed on triple-negative/basal-like (TN/BL) and luminal B/HER2-positive phenotypes, respectively, and CD276 (B7-H3), JAK2 and FOXO1 associated with both luminal A and luminal B/HER2-negative tumors. In addition, we found that these genes can also be related to aggressive and non-aggressive clinicopathological characteristics in BC. Finally, survival analysis showed that CTLA-4 expression levels emerge as a significant independent factor of good prognosis in BC patients, especially in the HER2-enriched subtype.

Conclusion: Considering all these data, we can conclude that the expression of immunoregulatory genes depends on tumor phenotype and has potential clinical implications in BC patients.

Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of gene expression through diverse mechanisms, including regulation of protein localization, sequestration of miRNAs, recruitment of chromatin modifiers, and modulation of signaling pathways. Accumulating evidence highlights their pivotal roles in tumor initiation, progression, and the development of therapeutic resistance. In this review, we comprehensively summarized the existing literature to identify lncRNAs associated with treatment responses in non-small cell lung cancer (NSCLC). Specifically, we categorized these lncRNAs based on their mechanisms of action in mediating resistance to chemotherapy, targeted therapy, and radiotherapy. Our analysis revealed that aberrant expression of various lncRNAs contributes to the development, metastasis, and therapeutic resistance in NSCLC, ultimately leading to poor clinical outcomes. By elucidating the intricate mechanisms through which lncRNAs modulate therapeutic responses, this review aims to provide mechanistic insights into the heterogeneous treatment outcomes observed in NSCLC patients and unveil potential therapeutic targets for overcoming drug resistance.

Background: Breast cancer remains a leading cause of mortality among women worldwide, necessitating innovative prognostic models to enhance treatment strategies.

Methods: Our study retrospectively enrolled 9,439 breast cancer patients from 12 independent datasets and single-cell data from 12 patients (64,308 cells). Moverover, 30 in-house clinical cohort were collected for validation. We employed a comprehensive approach by combining ten distinct machine learning algorithms across 108 different combinations to scrutinize 88 pre-existing signatures of breast cancer. To affirm the efficacy of our developed model, immunohistochemistry assays were performed. Additionally, we investigated various potential immunotherapeutic and chemotherapeutic interventions.

Results: This study introduces an Artificial Intelligence-aided Redox Signature (AIARS) as a novel prognostic tool, leveraging machine learning to identify critical redox-related gene signatures in breast cancer. Our results demonstrate that AIARS significantly outperforms existing prognostic models in predicting breast cancer outcomes, offering a robust tool for personalized treatment planning. Validation through immunohistochemistry assays on samples from 30 patients corroborated our results, underscoring the model's applicability on a wider scale. Furthermore, the analysis revealed that patients with low AIARS expression levels are more responsive to immunotherapy. Conversely, those exhibiting high AIARS were found to be more susceptible to certain chemotherapeutic agents, including vincristine.

Conclusions: Our study underscores the importance of redox biology in breast cancer prognosis and introduces a powerful machine learning-based tool, the AIARS, for personalized treatment strategies. By providing a more nuanced understanding of the redox landscape in breast cancer, the AIARS paves the way for the development of redox-targeted therapies, promising to enhance patient outcomes significantly. Future work will focus on clinical validation and exploring the mechanistic roles of identified genes in cancer biology.

Glioblastoma (GBM) is the most lethal and common primary tumor of central nervous system with a poor prognosis. Glioma stem cells (GSCs) are particularly significant in GBM proliferation, invasion, self-renewal and recurrence. Circular RNAs (circRNAs) play important roles in various physiological and pathological processes, including regulating the biological behavior of GBM. Therefore, discovering novel circRNAs related to GSCs may contribute to a promising approach for treatment of GBM. Herein, we find out a novel circRNA termed circZEB1 with a high expression in glioma. Limb-bud and heart (LBH) is a transcription cofactor and promotes glioma stem cell tumorigenicity in our study. Mechanistically, circZEB1 can upregulate the expression of transcription cofactor LBH via sponging miR-128-3p in GSCs. LBH can facilitate the expression of tumor necrosis factor-α (TNF-α), thus activating the NF-κB signaling pathway to promote the glioma progression. Meanwhile, LBH can also upregulate the RNA binding protein Fused in Sarcoma (FUS) expression, which can bind to and maintain the stability of circZEB1. A positive feedback loop is formed among FUS, circZEB1, miR-128-3p and LBH in GSCs. Our study uncovers a critical role of circZEB1 and provides a novel biomarker for treating GBM.