Baoxia Cui

Therapeutic Potential of IL‐37 in Cervical Cancer: Suppression of Tumour Progression and Enhancement of CD47‐Mediated Macrophage Phagocytosis

ABSTRACTAs a promising therapeutic approach, immunotherapy is being extensively investigated in cervical cancer. Although immunotherapy has been validated to improve progression‐free survival and overall survival in clinical trials, the overall response rate for cervical cancer remains inadequate, necessitating further improvement. Interleukin (IL)‐37, an emerging immunomodulator, exhibits antitumour potentials by inhibiting tumour progression and regulating tumour‐associated macrophage recognition. We found a significant downregulation of IL‐37 expression in cervical cancer, correlated with a poor prognosis. Moreover, the upregulation of IL‐37 expression exhibited a suppressive effect on various tumorigenic processes, suppressing the proliferation, invasion, migration, apoptosis and angiogenesis of tumour cells. We also found that the upregulation of IL‐37 suppressed cluster of differentiation 47 (CD47) expression in tumour cells via suppression of the signal transducer and activator of transcription 3 (STAT3) expression and phosphorylation, thereby enhancing macrophage recognition and phagocytosis to tumour cells, ultimately reducing immune evasion. Overall, our study highlighted the crucial role of IL‐37 in antitumour efficacy and downregulating the expression of CD47 in tumour cells to reduce immune evasion, suggesting the potential of IL‐37 as a prognostic biomarker in cervical cancer and offering innovative therapeutic strategies to improve cancer treatment outcomes.

Proteomics-Based Mapping of the Lymph Node Metastasis Landscape in Cervical Cancer

Lymph node metastasis (LNM) in cervical cancer is a critical determinant of the disease progression and prognosis. Elucidating its molecular mechanisms and identifying specific biomarkers are crucial for optimizing treatment. DIA-based quantitative proteomic sequencing was conducted on 49 cervical cancer patients. We screened differentially expressed proteins and performed functional enrichment, pathway scoring, time-series analysis, protein interaction studies, and integrated proteomic and TCGA transcriptomic data to identify biomarkers. 56 genes showed consistent expression trends, with 2 upregulated (SERPINB5, FABP5) and 54 downregulated (including ZNF512). Novel findings include activation of unsaturated fatty acid/steroid biosynthesis and inhibition of cell junction pathways during progression. Lymphovascular space invasion (LVSI) precedes LNM, but a subset of LNM cases lacks LVSI and exhibits a unique cholesterol metabolism activation. SERPINB5, FABP5, and ZNF512 were validated as potential prognostic and LNM-predictive biomarkers. DIA proteomics characterized cervical cancer lymph node metastasis, revealing molecular changes and potential biomarkers and offering new insights into its biological mechanisms.

Targeting tumor-associated macrophage-derived CD74 improves efficacy of neoadjuvant chemotherapy in combination with PD-1 blockade for cervical cancer

Background Cervical cancer has the second-highest mortality rate among malignant tumors of the female reproductive system. Immune checkpoint inhibitors such as programmed cell death protein 1 (PD-1) blockade are promising therapeutic agents, but their efficacy when combined with neoadjuvant chemotherapy (NACT) has not been fully tested, and how they alter the tumor microenvironment has not been comprehensively elucidated. Methods In this study, we conducted single-cell RNA sequencing using 46,950 cells from nine human cervical cancer tissues representing sequential different stages of NACT and PD-1 blockade combination therapy. We delineated the trajectory of cervical epithelial cells and identified the crucial factors involved in combination therapy. Cell–cell communication analysis was performed between tumor and immune cells. In addition, THP-1-derived and primary monocyte-derived macrophages were cocultured with cervical cancer cells and phagocytosis was detected by flow cytometry. The antitumor activity of blocking CD74 was validated in vivo using a CD74 humanized subcutaneous tumor model. Results Pathway enrichment analysis indicated that NACT activated cytokine and complement-related immune responses. Cell–cell communication analysis revealed that after NACT therapy, interaction strength between T cells and cancer cells decreased, but intensified between macrophages and cancer cells. We verified that macrophages were necessary for the PD-1 blockade to exert antitumor effects in vitro. Additionally, CD74-positive macrophages frequently interacted with the most immunoreactive epithelial subgroup 3 (Epi3) cancer subgroup during combination NACT. We found that CD74 upregulation limited phagocytosis and stimulated M2 polarization, whereas CD74 blockade enhanced macrophage phagocytosis, decreasing cervical cancer cell viability in vitro and in vivo. Conclusions Our study reveals the dynamic cell–cell interaction network in the cervical cancer microenvironment influenced by combining NACT and PD-1 blockade. Furthermore, blocking tumor-associated macrophage-derived CD74 could augment neoadjuvant therapeutic efficacy.

hsa_circ_0000745 promotes cervical cancer by increasing cell proliferation, migration, and invasion

AbstractCircular RNAs (circRNAs) participate in gene regulation and malignant tumor progression, including uterine cervical cancer (CC). In this study, the expression profile of circRNAs in CC was detected using circRNA microarrays. Then, we selected hsa_circ_0000745 for further examination from the significantly dysregulated circRNAs. Proliferation assays, Transwell assays, quantitative reverse transcription polymerase chain reaction, western blot analysis and tumorigenesis tests in vivo were used to validate the role of hsa_circ_0000745 in CC. hsa_circ_0000745 was upregulated in CC, and its level positively correlated with the level of its linear messenger RNA isoform. Patients with poorly differentiated tumors or vascular/lymphatic invasion presented higher expression of hsa_circ_0000745. The role of hsa_circ_0000745 was illuminated by knocking down hsa_circ_0000745 in CC cells, and the results revealed that reducing hsa_circ_0000745 inhibited cell proliferation, migration, and invasion in CC by upregulating E‐cadherin (E‐cad) expression. In summary, as a tumor promoter in CC, hsa_circ_0000745 enhances the cell's ability to proliferate, migrate, and invade by reducing the expression of E‐cad. hsa_circ_0000745 is a candidate target for the treatment of CC in the clinic.

Development of a Novel Deep Learning-Based Prediction Model for the Prognosis of Operable Cervical Cancer

Background. Cervical cancer ranks as the 4th most common female cancer worldwide. Early stage cervical cancer patients can be treated with operation, but clinical staging system is not a good predictor of patients’ survival. We aimed to develop a novel prognostic model to predict the prognosis for operable cervical cancer patients with better accuracy than clinical staging system. Methods. A total of 13,952 operable cervical cancer patients were retrospectively enrolled in this study. The whole dataset was randomly split into a training set ( n = 9,068 , 65%), validation set ( n = 2,442 , 17.5%), and testing set ( n = 2,442 , 17.5%). Cox proportional hazard (CPH) model and random survival forest (RSF) model were used as baseline models for the prediction of overall survival (OS). Then, a deep survival learning model (DSLM) was developed for OS prediction. Finally, a novel prognostic model was explored based on this DSLM. Results. The C-indexes for the CPH and RSF model were 0.731 and 0.753, respectively. DSLM, which had four layers that had 50 neurons in each layer, achieved a C-index of 0.782 in the validation set and a C-index of 0.758 in the testing set. The novel prognostic model based on DSLM showed better performances than the conventional clinical staging system (area under receiver operating curves were 0.826 and 0.689, respectively). Personalized survival curves for individual patient using this novel model also showed notably different survival slopes. Conclusions. Our study developed a novel, practical, personalized prognostic model for operable cervical cancer patients. This novel prognostic model may have the potential to provide a more prognostic information to oncologists.

Use of Nomogram to Predict the Risk of Lymph Node Metastasis among Patients with Cervical Adenocarcinoma

Background. The objective of this study was to develop a nomogram that can predict lymph node metastasis (LNM) in patients with cervical adenocarcinoma (cervical AC). Methods. A total of 219 patients with cervical AC who had undergone radical hysterectomy and lymphadenopathy between 2005 and 2021 were selected for this study. Both univariate and multivariate logistic regression analyses were performed to analyze the selected key clinicopathologic features and develop a nomogram and underwent internal validation to predict the probability of LNM. Results. Lymphovascular invasion (LVI), tumor   size ≥ 4  cm, and depth of cervical stromal infiltration were independent predictors of LNM in cervical AC. However, the Silva pattern was not found to be a significant predictor in the multivariate model. The Silva pattern was still included in the model based on the improved predictive performance of the model observed in the previous studies. The concordance index ( C -index) of the model increased from 0.786 to 0.794 after the inclusion of the Silva pattern. The Silva pattern was found to be the strongest predictor of LNM among all the pathological factors investigated, with an OR of 4.37 in the nomogram model. The nomogram developed by incorporation of these four predictors performed well in terms of discrimination and calibration capabilities ( C − index = 0.794 ; 95% confidence interval (CI), 0.727–0.862; Brier   score = 0.127 ). Decision curve analysis demonstrated that the nomogram was clinically effective in the prediction of LNM. Conclusion. In this study, a nomogram was developed based on the pathologic features, which helped to screen individuals with a higher risk of occult LNM. As a result, this tool may be specifically useful in the management of individuals with cervical AC and help gynecologists to guide clinical individualized treatment plan.

The roles of m6A methylation in cervical cancer: functions, molecular mechanisms, and clinical applications

AbstractCervical cancer (CC) is a gynecological neoplasm with the highest incidence rate, primarily attributed to the persistent infection of high-risk Human papillomavirus (HPV). Despite extensive research, the pathogenesis of CC remains unclear. N6-methyladenosine (m6A) methylation, the most prevalent form of epigenetic modification in RNA, is intricately linked to cell proliferation, metastasis, metabolism, and therapeutic resistance within the tumor microenvironment (TME) of CC. The involvement of the writer, reader, and eraser in m6A modification impacts the advancement of tumors through the regulation of RNA stability, nuclear export, translation efficiency, and RNA degradation. Here, we discuss the biogenesis of m6A, the atypical expressions of m6A regulators, the mechanisms of molecular interactions, and their functions in CC. Furthermore, we elucidate m6A modification of non-coding RNA. In the context of precision medicine, and with the advancements of genomics, proteomics, and high-throughput sequencing technologies, we summarize the application of m6A in the clinical diagnosis and treatment of CC. Additionally, new perspectives on detection methods, immune regulation, and nano-drug development are presented, which lay the foundation for further research of m6A and provide new ideas for the clinical treatment of CC.

Identification of lymph node metastasis in pre‐operation cervical cancer patients by weakly supervised deep learning from histopathological whole‐slide biopsy images

AbstractBackgroundLymph node metastasis (LNM) significantly impacts the prognosis of individuals diagnosed with cervical cancer, as it is closely linked to disease recurrence and mortality, thereby impacting therapeutic schedule choices for patients. However, accurately predicting LNM prior to treatment remains challenging. Consequently, this study seeks to utilize digital pathological features extracted from histopathological slides of primary cervical cancer patients to preoperatively predict the presence of LNM.MethodsA deep learning (DL) model was trained using the Vision transformer (ViT) and recurrent neural network (RNN) frameworks to predict LNM. This prediction was based on the analysis of 554 histopathological whole‐slide images (WSIs) obtained from Qilu Hospital of Shandong University. To validate the model's performance, an external test was conducted using 336 WSIs from four other hospitals. Additionally, the efficiency of the DL model was evaluated using 190 cervical biopsies WSIs in a prospective set.ResultsIn the internal test set, our DL model achieved an area under the curve (AUC) of 0.919, with sensitivity and specificity values of 0.923 and 0.905, respectively, and an accuracy (ACC) of 0.909. The performance of the DL model remained strong in the external test set. In the prospective cohort, the AUC was 0.91, and the ACC was 0.895. Additionally, the DL model exhibited higher accuracy compared to imaging examination in the evaluation of LNM. By utilizing the transformer visualization method, we generated a heatmap that illustrates the local pathological features in primary lesions relevant to LNM.ConclusionDL‐based image analysis has demonstrated efficiency in predicting LNM in early operable cervical cancer through the utilization of biopsies WSI. This approach has the potential to enhance therapeutic decision‐making for patients diagnosed with cervical cancer.

Glycolysis Induced by METTL14 Is Essential for Macrophage Phagocytosis and Phenotype in Cervical Cancer

Abstract N 6-methyladenosine (m6A) is the most abundant mRNA modification in mammals and it plays a vital role in various biological processes. However, the roles of m6A on cervical cancer tumorigenesis, especially macrophages infiltrated in the tumor microenvironment of cervical cancer, are still unclear. We analyzed the abnormal m6A methylation in cervical cancer, using CaSki and THP-1 cell lines, that might influence macrophage polarization and/or function in the tumor microenvironment. In addition, C57BL/6J and BALB/c nude mice were used for validation in vivo. In this study, m6A methylated RNA immunoprecipitation sequencing analysis revealed the m6A profiles in cervical cancer. Then, we discovered that the high expression of METTL14 (methyltransferase 14, N6-adenosine-methyltransferase subunit) in cervical cancer tissues can promote the proportion of programmed cell death protein 1 (PD-1)–positive tumor-associated macrophages, which have an obstacle to devour tumor cells. Functionally, changes of METTL14 in cervical cancer inhibit the recognition and phagocytosis of macrophages to tumor cells. Mechanistically, the abnormality of METTL14 could target the glycolysis of tumors in vivo and vitro. Moreover, lactate acid produced by tumor glycolysis has an important role in the PD-1 expression of tumor-associated macrophages as a proinflammatory and immunosuppressive mediator. In this study, we revealed the effect of glycolysis regulated by METTL14 on the expression of PD-1 and phagocytosis of macrophages, which showed that METTL14 was a potential therapeutic target for treating advanced human cancers.

Splice-switching of the oncogenic BCS1L isoform suppresses ovarian cancer progression by disrupting mitochondrial function

Abstract Increasing evidences demonstrate that mitochondrial function is essential for cancer cell survival and metastasis. However, the role of mitochondrial metabolic reprogramming in ovarian cancer progression remains largely unknown. Here, we report that mitochondrial chaperone BCS1L generates two major alternative-spliced isoforms, a full-length isoform ( BCS1L-L ) and a short isoform lacking exon 2 ( BCS1L-S ). Interestingly, BCS1L-L is elevated in several human cancers, and it significantly increased oxidative phosphorylation and ATP production in the present work, which is required for the survival of cancer cells. In contrast, BCS1L-S was unable to localize to the mitochondria as BCS1L-L did, and this led to impaired metabolic function. Mechanistically, splicing factor USP39 promoted exon 2 inclusion, thus facilitating the generation of oncogenic BCS1L-L and, thereby, maintaining mitochondrial homeostasis and survival of ovarian cancer cells. Importantly, we developed splice-switch antisense oligonucleotides (ASOs) that successfully induced exon 2 skipping and decreased BCS1L-L abundance, resulting in impaired tumor growth. These findings suggest that targeting oncogenic BCS1L-L by ASOs is a novel approach for ovarian cancer treatment.