Transcriptomic profiling classifies pancreatic ductal adenocarcinoma (PDAC) into several molecular subtypes with distinctive histological and clinical characteristics. However, little is known about the molecular mechanisms that define each subtype and their correlation with clinical outcome. Mutant KRAS is the most prominent driver in PDAC, present in over 90% of tumors, but the dependence of tumors on oncogenic KRAS signaling varies between subtypes. In particular, the squamous subtype is relatively independent of oncogenic KRAS signaling and typically displays much more aggressive clinical behavior versus the progenitor subtype. Here, we identified that yes-associated protein 1 (YAP1) activation is enriched in the squamous subtype and associated with poor prognosis. Activation of YAP1 in progenitor subtype cancer cells profoundly enhanced malignant phenotypes and transformed progenitor subtype cells into squamous subtype. Conversely, depletion of YAP1 specifically suppressed tumorigenicity of squamous subtype PDAC cells. Mechanistically, we uncovered a significant positive correlation between WNT5A expression and YAP1 activity in human PDAC and demonstrated that WNT5A overexpression led to YAP1 activation and recapitulated a YAP1-dependent but Kras-independent phenotype of tumor progression and maintenance. Thus, our study identifies YAP1 oncogene as a major driver of squamous subtype PDAC and uncovers the role of WNT5A in driving PDAC malignancy through activation of the YAP pathway.

Fat mass and obesity-associated protein (FTO) regulates critical pathways in various diseases, including malignant tumours. However, the functional link between FTO and its target genes in epithelial ovarian cancer (EOC) development remains to be elucidated. In this study, the biological functions of FTO were verified in vitro and in vivo. The m6A modification and the binding sites of SNAI1 mRNA were confirmed by m6A RNA immunoprecipitation (MeRIP) and RIP experiments. The actinomycin D assay was used to test the stability of RNA. We found that FTO was downregulated with increased m6A levels in EOC. Reduced expression of FTO was associated with a higher FIGO stage in patients with EOC. Mechanistically, FTO decreased the m6A level and stability of SNAI1 mRNA, causing downregulation of SNAI1 and inhibiting epithelial–mesenchymal transition (EMT). Furthermore, FTO-mediated downregulation of SNAI1 expression depended on IGF2BP2, which acted as an m6A reader binding to the 3′ UTR region of SNAI1 mRNA to promote its stability. In conclusion, FTO inhibits SNAI1 expression to attenuate the growth and metastasis of EOC cells in an m6A-IGF2BP2-dependent manner. Our findings suggest that the FTO-IGF2BP2-SNAI1 axis is a potential therapeutic target in EOC.

Background: The prognostic factors for efficacy of poly(ADP-ribose) polymerase (PARP) inhibitors in ovarian cancer remain unknown. The purpose of this study is to evaluate the efficacy of PARP inhibitors and to explore their prognostic factors in ovarian cancer. Methods: PubMed, Embase, and conference databases were searched for relevant prospective clinical trials. The primary outcomes included overall survival (OS), progression-free survival (PFS), and their prognostic factors. Secondary outcomes included PFS2, time to first subsequent therapy (TFST), time to second subsequent therapy (TSST), chemotherapy-free interval (CFI), and their prognostic factors. Hazard ratio (HR) with a 95% confidence interval (CI) was used as an effect measure. Results: PARP inhibitors significantly prolonged PFS in patients with ovarian cancer regardless of their BRCA and HRD status (HR = 0.44, 95% CI = 0.36–0.55). BRCA mutation, HRD-positive status, and sensitivity to platinum represented effective prognostic factors for PFS (P_interaction < 0.01 and within-trial interaction HR < 1). Other clinicopathological factors did not predict the benefit of PFS (P_interaction > 0.10). Moreover, PARP inhibitors significantly increased PFS2, TFST, TSST, and CFI, with significant BRCA-related differences. However, HRD-related differences could not be evaluated due to the lack of eligible studies. Furthermore, PARP inhibitors did not translate into prolonged OS, although there was a benefit associated with OS (HR = 0.84, 95% CI = 0.70–1.02). PARP inhibitors used as maintenance therapy after first or subsequent line therapy improved OS (HR = 0.77, 95% CI = 0.63–0.93). Conclusions: PARP inhibitors can significantly prolong PFS, PFS2, TFST, TSST, and CFI in ovarian cancer patients. BRCA mutation, HRD-positive status, and sensitivity to platinum are effective prognostic factors for the efficacy of PARP inhibitors. However, despite the PFS improvement, this does not translate into prolonged OS for patients.

With the emergence of deep learning techniques based on convolutional neural networks, artificial intelligence (AI) has driven transformative developments in the field of medical image analysis. Recently, large language models (LLMs) such as ChatGPT have also started to achieve distinction in this domain. Increasing research shows the undeniable role of AI in reshaping various aspects of medical image analysis, including processes such as image enhancement, segmentation, detection in image preprocessing, and postprocessing related to medical diagnosis and prognosis in clinical settings. However, despite the significant progress in AI research, studies investigating the recent advances in AI technology in the aforementioned aspects, the changes in research hotspot trajectories, and the performance of studies in addressing key clinical challenges in this field are limited. This article provides an overview of recent advances in AI for medical image analysis and discusses the methodological profiles, advantages, disadvantages, and future trends of AI technologies.

BACKGROUND:Ovarian cancer is the most lethal malignant tumor of the female reproductive system, and the metastasis is one of the major factors that contribute to the poor outcome of patients with OC. Accumulating evidence indicates that lncRNAs are e...

Our study aims to explore the effects of neoadjuvant chemotherapy (NACT) on tumour cells and immune cells in the immune microenvironment of patients with high-grade serous ovarian cancer (HGSOC). Single-cell RNA sequencing data of paired ovarian cancer tissues were analysed before and after NACT in 11 patients with HGSOC. The effect of NACT on two major cell components of the tumour microenvironment, epithelial cells and CD8+T cells, was investigated. The mechanisms of epithelial cell evasion by NACT and immune killing were explored from the perspectives of gene expression, functional characteristics, transcriptional regulation, and cell communication. Key targets for reversing NACT resistance were identified and possible therapeutic strategies proposed. While NACT improved the de novo differentiation of anti-tumour CD8+T cells, enhancing their anti-tumour function, it increased the proportion of cancer cells with high HSP90B1 expression. Thus, the potential reasons for NACT resistance were identified as: 1) high levels of endoplasmic reticulum stress (ERS) characteristics, 2) high expression of the MDK-NCL ligand-receptor pair between them and exhausted CD8+T cells before NACT, and 3) high expression of the NECTIN2-TIGIT immune ligand-receptor pair between them and exhausted CD8+T cells after NACT. Thus, our study reveals the mechanisms underlying NACT resistance in patients with HGSOC from the perspective of the independent and interactive roles of cancer cells and CD8+T cells. We propose therapeutic strategies targeting the ERS marker HSP90B1 and the immune escape marker MDK before or during NACT, while targeting NECTIN2 blockade after NACT. This approach may offer new insights into combination treatments for patients with HGSOC displaying NACT resistance.