Advanced Biology

Tumor‐Infiltrating Nociceptor Neurons in Ovarian Cancer Treatment Resistance

ABSTRACT Patients with densely innervated tumors suffer with poor outcomes, thus identifying them could define a cohort that could benefit from aggressive treatments. Most cases and deaths from ovarian cancer are associated with high‐grade serous ovarian carcinoma (HGSOC). We immunohistochemically analyzed the histological subtypes of ovarian cancer (high‐grade serous, low‐grade serous, clear cell, mucinous, and endometrioid) for nerves; only HGSOCs were densely innervated. We previously defined that tumor‐released small extracellular vesicles (sEVs) recruit nerves to the tumor bed and thus tested whether the difference in nerve infiltration amongst ovarian cancers was associated with sEVs. Using an in vitro neurite outgrowth assay, we found that HGSOC sEVs harbored robust neurite outgrowth activity. Importantly, sEVs from fallopian tube cell lines (the primary cell of origin of HGSOC) predominantly lacked this activity. Implantation of a syngeneic mouse model of HGSOC into transgenic mice lacking tumor‐infiltrating nerves slowed tumor growth, sensitized disease to carboplatin, and improved survival. Consistent with this, we show that recurrent, treatment‐resistant disease in patients is significantly more innervated than its matched naïve (untreated) malignancy. Taken together, these data identify dense nerve infiltration of HGSOCs and show that innervation contributes to treatment resistance.

Accurate Identification of Cancer Cells in Complex Pre‐Clinical Models Using a Deep‐Learning Neural Network: A Transfection‐Free Approach

Abstract3D co‐cultures are key tools for in vitro biomedical research as they recapitulate more closely the in vivo environment while allowing a tighter control on the culture's composition and experimental conditions. The limited technologies available for the analysis of these models, however, hamper their widespread application. The separation of the contribution of the different cell types, in particular, is a fundamental challenge. In this work, ORACLE (OvaRiAn Cancer ceLl rEcognition) is presented, a deep neural network trained to distinguish between ovarian cancer and healthy cells based on the shape of their nucleus. The extensive validation that are conducted includes multiple cell lines and patient‐derived cultures to characterize the effect of all the major potential confounding factors. High accuracy and reliability are maintained throughout the analysis (F1score> 0.9 and Area under the ROC curve ‐ROC‐AUC‐ score = 0.99) demonstrating ORACLE's effectiveness with this detection and classification task. ORACLE is freely available (https://github.com/MarilisaCortesi/ORACLE/tree/main) and can be used to recognize both ovarian cancer cell lines and primary patient‐derived cells. This feature is unique to ORACLE and thus enables for the first time the analysis of in vitro co‐cultures comprised solely of patient‐derived cells.

FOXP3 Polymorphism and Upregulation of the CXCL12‐CXCR4‐SNAIL Axis with High Infiltration of M2TAM by STAT3/NFKB Pathways Influence the Survival of Cervical Cancer Patients

Abstract This study explores the interaction between immune and cancer cells in the tumor microenvironment (TME) of cervical carcinoma (CC), with emphasis on tumor‐associated macrophages (M2‐TAMs) and the STAT3‐NF‐κB signaling pathway. It investigates how Treg cell polymorphisms and TAM infiltration through these pathways influence overall survival (OS) in CC patients. This prospective study follows 100 CC patients from 2018 to 2023 using qRT‐PCR and immunohistochemistry on tumor samples, and flow cytometry on blood samples to evaluate immunosuppressive cytokines and Treg cell polymorphisms. High stromal CD163+204+ TAM density, mediated by STAT3/NF‐κB, correlates with biomarkers such as Ki‐67, VEGFα, and FOXP3 ( p < 0.001). XPO5 expression is associated with increased STAT3, SNAIL, and HPV 16/18 levels. FOXP3 T allele deletion and HLA‐G polymorphism in the blood of patients correlate with higher STAT3 tumor expression and elevated IL‐4 and IL‐17 blood cytokines. The CXCL12‐CXCR4 axis shows a strong association with STAT3, SNAIL in TME and blood cytokines, including IL‐6 and IL‐12. Elevated CXCL12, CXCR4, and SNAIL expression in TME significantly increases mortality risk. These findings underscore the role of M2TAM infiltration and immune modulation in tumor progression and clinical outcomes in CC.

Unraveling the Transcriptomic Signatures of Homologous Recombination Deficiency in Ovarian Cancers

AbstractHomologous recombination deficiency (HRD) is a crucial driver of tumorigenesis by inducing impaired repair of double‐stranded DNA breaks. Although HRD possibly triggers the production of numerous tumor neoantigens that sufficiently stimulate and activate various tumor‐immune responses, a comprehensive understanding of the HRD‐associated tumor microenvironment is elusive. To investigate the effect of HRD on the selective enrichment of transcriptomic signatures, 294 cases from The Cancer Genome Atlas‐Ovarian Cancer project with both RNA‐sequencing and SNP array data are analyzed. Differentially expressed gene analysis and network analysis are performed to identify HRD‐specific signatures. Gene‐sets associated with mitochondrial activation, including enhanced oxidative phosphorylation (OxPhos), are significantly enriched in the HRD‐high group. Furthermore, a wide range of immune cell activation signatures is enriched in HRD‐high cases of high‐grade serous ovarian cancer (HGSOC). On further cell‐type‐specific analysis, M1‐like macrophage genes are significantly enriched in HRD‐high HGSOC cases, whereas M2‐macrophage‐related genes are not. The immune‐response‐associated genomic features, including tumor mutation rate, neoantigens, and tumor mutation burdens, correlated with HRD scores. In conclusion, the results of this study highlight the biological properties of HRD, including enhanced energy metabolism, increased tumor neoantigens and tumor mutation burdens, and consequent exacerbation of immune responses, particularly the enrichment of M1‐like macrophages in HGSOC cases.

Extracellular Matrix Modulates Outgrowth Dynamics in Ovarian Cancer

Abstract Ovarian carcinoma (OC) forms outgrowths that extend from the outer surface of an afflicted organ into the peritoneum. OC outgrowth formation is poorly understood due to the limited availability of cell culture models examining the behavior of cells that form outgrowths. Prompted by immunochemical evaluation of extracellular matrix (ECM) components in human tissues, laminin and collagen‐rich ECM‐reconstituted cell culture models amenable to studies of cell clusters that can form outgrowths are developed. It is demonstrated that ECM promotes outgrowth formation in fallopian tube non‐ciliated epithelial cells (FNE) expressing mutant p53 and various OC cell lines. Outgrowths are initiated by cells that underwent outward translocation and retained the ability to intercalate into mesothelial cell monolayers. Electron microscopy, optical coherence tomography, and small amplitude oscillatory shear experiments reveal that increased ECM levels led to increased fibrous network thickness and high shear elasticity of the microenvironment. These physical characteristics are associated with outgrowth suppression. The low ECM microenvironment mimicks the viscoelasticity of malignant peritoneal fluid (ascites) and supports cell proliferation, cell translocation, and outgrowth formation. These results highlight the importance of the ECM microenvironment in modulating OC growth and can provide additional insights into the mode of dissemination of primary and recurrent ovarian tumors.

ACSM3 Suppresses Ovarian Cancer Progression by Inactivating the IFN‐γ/JAK/STAT3 Signaling Pathway

AbstractThis study aimed to investigate the role of Acyl‐CoA medium‐chain synthetase 3 (ACSM3) in ovarian cancer (OC) progression. ACSM3 expression in OC tissues and cells is detected by real‐time quantitative polymerase chain reaction, immunohistochemistry, or western blot. The influences of ACSM3 on OC progression are assessed in vitro and in vivo experiments. Gene set enrichment analysis is performed to find significantly enriched pathways related to ACSM3. In this study, ACSM3 expression in OC tissues and cells is downregulated. ACSM3 inhibited tumor growth in vivo. Knockdown of ACSM3 promoted cell proliferation, migration, and invasion, inhibited cell apoptosis, and activated JAK/STAT3 signaling pathway in SKOV3 cells, while overexpression of ACSM3 in A2780 cells led to the opposite results. Moreover, treatment with interferon‐gamma (IFN‐γ) in A2780 cells reversed the effects of ACSM3 on cell proliferation, migration, invasion, and apoptosis, but IFN‐γ further enhanced the effects of ACSM3 knockdown on SKOV3 cell proliferation, migration, invasion, and apoptosis. In conclusion, ACSM3 inhibited OC cell proliferation, migration, and invasion, and promoted cell apoptosis by suppressing the IFN‐γ/JAK/STAT3 signaling pathway, which might provide a promising therapeutic target for OC treatment.

In Vivo Ultrasound Molecular Imaging in the Evaluation of Complex Ovarian Masses: A Practical Guide to Correlation with Ex Vivo Immunohistochemistry

AbstractOvarian cancer is the fifth leading cause of cancer‐related deaths in women and the most lethal gynecologic cancer. It is curable when discovered at an early stage, but usually remains asymptomatic until advanced stages. It is crucial to diagnose the disease before it metastasizes to distant organs for optimal patient management. Conventional transvaginal ultrasound imaging offers limited sensitivity and specificity in the ovarian cancer detection. With molecularly targeted ligands addressing targets, such as kinase insert domain receptor (KDR), attached to contrast microbubbles, ultrasound molecular imaging (USMI) can be used to detect, characterize and monitor ovarian cancer at a molecular level. In this article, the authors propose a standardized protocol is proposed for the accurate correlation between in‐ vivo transvaginal KDR‐targeted USMI and ex vivo histology and immunohistochemistry in clinical translational studies. The detailed procedures of in vivo USMI and ex vivo immunohistochemistry are described for four molecular markers, CD31 and KDR with a focus on how to enable the accurate correlation between in vivo imaging findings and ex vivo expression of the molecular markers, even if not the entire tumor could can be imaged by USMI, which is not an uncommon scenario in clinical translational studies. This work aims to enhance the workflow and the accuracy of characterization of ovarian masses on transvaginal USMI using histology and immunohistochemistry as reference standards, which involves sonographers, radiologists, surgeons, and pathologists in a highly collaborative research effort of USMI in cancer.