Cervical cancer remains a leading cause of cancer death in women, seriously threatening their physical and mental health. It is an easily preventable cancer with early screening and diagnosis. Although technical advancements have significantly improved the early diagnosis of cervical cancer, accurate diagnosis remains difficult owing to various factors. In recent years, artificial intelligence (AI)-based medical diagnostic applications have been on the rise and have excellent applicability in the screening and diagnosis of cervical cancer. Their benefits include reduced time consumption, reduced need for professional and technical personnel, and no bias owing to subjective factors. We, thus, aimed to discuss how AI can be used in cervical cancer screening and diagnosis, particularly to improve the accuracy of early diagnosis. The application and challenges of using AI in the diagnosis and treatment of cervical cancer are also discussed.

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Endometrial cancer (EC) is increasingly undermining female health worldwide, with poor survival rates for advanced or recurrent/metastatic diseases. The application of immune checkpoint inhibitors (ICIs) has opened a window of opportunity for patients with first-line therapy failure. However, there is a subset of patients with endometrial cancer who remain insensitive to immunotherapy alone. Therefore, it is necessary to develop new therapeutic agents and further explore reliable combinational strategies to optimize the efficacy of immunotherapy. DNA damage repair (DDR) inhibitors as novel targeted drugs are able to generate genomic toxicity and induce cell death in solid tumors, including EC. Recently, growing evidence has demonstrated the DDR pathway modulates innate and adaptive immunity in tumors. In this review, we concentrate on the exploration of the intrinsic correlation between DDR pathways, especially the ATM-CHK2-P53 pathway and the ATR-CHK1-WEE1 pathway, and oncologic immune response, as well as the feasibility of adding DDR inhibitors to ICIs for the treatment of patients with advanced or recurrent/metastatic EC. We hope that this review will offer some beneficial references to the investigation of immunotherapy and provide a reasonable basis for “double-checkpoint inhibition” in EC.

Cervical cancer ranks as the fourth leading cause of cancer-related deaths among women, with low response rates to immune-checkpoint blockade (ICB). Here we conducted a multidimensional analysis encompassing single-cell RNA-seq (scRNA-seq), spatial transcriptomics, and spatial proteomics, combined with genetic and pharmacological perturbations to systematically develop a high-resolution and spatially-resolved map of intra-tumoral expression heterogeneity in cervical squamous cell carcinoma (CSCC). Three context-specific tumor states (Epithelial-cytokeratin (Epi-Krt), epithelial-immune (Epi-imm) and epithelial senescence (Epi-Sen)) that recapitulate squamous differentiation substantially alter the tumor immune microenvironment (TIME). Bidirectional interactions between Epi-Krt malignant epithelial cells and MMP11+ CAF form an immune exclusionary microenvironment through TGFβ pathway signaling mediated by FABP5. Epi-Imm malignant epithelial cells and NK/T cells interact bidirectionally through interferon signaling. Notably, preliminary analysis of the NACI clinical trial (NCT04516616) demonstrated neoadjuvant chemotherapy (NACT) induce a state transition to Epi-Imm with the extent of this transition being associated with pathological complete remission (pCR) to subsequent ICB treatment. These findings provide a comprehensive and nuanced understanding of cellular state diversity and have significant implications for developing novel therapeutic strategies in CSCC and potentially other squamous cancers.