Lymph Node Metastasis In Cervical Cancer Research Articles

Clinical Controversies and Research Progress in Lymph Node Dissection for Cervical Cancer

Regional lymph node metastasis (LNM) is the main metastatic route of cervical cancer, whose rate of LNM increases in the cancer progression. LNM of cervical cancer is closely related to the cervical cancer staging, treatment method and prognosis. Lymph node dissection (LND) is an important part of standard cervical cancer staging surgeries. In recent years, Sentinel Lymph Node Biopsy (SLNB) has been used in treatments of some tumors, being considered as an alternative to Pelvic Lymph Node Dissection (PLND) in early-stage cervical cancer. However, validation regarding the feasibility of using SLNB alone as an alternative to PLND is still needed. Some scholars support PLND for patients with suspicious lymph nodes detected preoperatively due to reasons such as lower diagnostic sensitivity and specificity of preoperative imaging and potentially better prognosis for surgical staging of advanced stage of cervical cancer. However, recent basic research suggests that lymph nodes are important organs for providing tumor-specific immunity, the preservation of which facilitates immunotherapy. In this way, controversies about whether to use PLND still exist. This paper presents a brief review of the relevant research progress and discusses the new clinical definition and value of lymph nodes in the era of immunotherapy, with a view to providing new directions and ideas for the rational application of LND.

Tumor-to-stroma cd8+ t cells ratio combined with cancer-associated fibroblasts: an innovative approach to predicting lymph node metastases of cervical cancer

PurposePrecise identification of lymph node metastases is vital for the management of cervical cancer. However, the existing diagnostic methods for lymph node metastases have certain drawbacks. In this study, we aim to explore the expression of cancer-associated fibroblasts (CAFs) and tumor-to-stroma CD8+ T cells ratio (CD8+ T cells T:S ratio) and its association with lymph node metastases of cervical cancer.MethodsHundred and ten cervical cancer tissues and 39 biopsy tissues from patients were investigated immunocytochemically for the expression of CAFs and CD8+ T cells. The statistical correlation analysis was carried out using the SPSS system.ResultsA strong and statistically significant negative correlation (r= − 0.690; P < 0.001) was observed between CAF density and CD8+ T cells T:S ratio. Not only were CAFs density and CD8+ T cells T:S ratio correlated with lymph node metastases respectively (P < 0.001), but the combination of them also significantly correlated with lymph node metastases (P < 0.001). Then, we constructed the combined diagnosis model (Logit (P) = − 4.446 + 0.300 × CAFs + 0.752 × CD8+ T cells T:S Ratio) of cervical cancer lymph node metastases. ROC curves analysis showed that the ROC curves areas for CAFs, CD8+ T cells T:S ratio, and a combination of both are 0.879, 0.747, and 0.951. Then, the prediction model was verified by biopsy specimens and consistent results were obtained.ConclusionsThe combination of CAF density and CD8+ T cells T:S ratio has a significant predictive value for lymph node metastases in patients with cervical cancer.

Prediction models for lymph node metastasis in cervical cancer based on preoperative heart rate variability.

The occurrence of lymph node metastasis (LNM) is one of the critical factors in determining the staging, treatment and prognosis of cervical cancer (CC). Heart rate variability (HRV) is associated with LNM in patients with CC. The purpose of this study was to validate the feasibility of machine learning (ML) models constructed with preoperative HRV as a feature of CC patients in predicting CC LNM. A total of 292 patients with pathologically confirmed CC admitted to the Department of Gynecological Oncology of the First Affiliated Hospital of Bengbu Medical University from November 2020 to September 2023 were included in the study. The patient' preoperative 5-min electrocardiogram data were collected, and HRV time-domain, frequency-domain and non-linear analyses were subsequently performed, and six ML models were constructed based on 32 parameters. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. Among the 6 ML models, the random forest (RF) model showed the best predictive performance, as specified by the following metrics on the test set: AUC (0.852), accuracy (0.744), sensitivity (0.783), and specificity (0.785). The RF model built with preoperative HRV parameters showed superior performance in CC LNM prediction, but multicenter studies with larger datasets are needed to validate our findings, and the physiopathological mechanisms between HRV and CC LNM need to be further explored.

CircMAST1 inhibits cervical cancer progression by hindering the N4-acetylcytidine modification of YAP mRNA

BackgroundCervical cancer (CCa) is the fourth most common cancer among females, with high incidence and mortality rates. Circular RNAs (circRNAs) are key regulators of various biological processes in cancer. However, the biological role of circRNAs in cervical cancer (CCa) remains largely unknown. This study aimed to elucidate the role of circMAST1 in CCa.MethodsCircRNAs related to CCa progression were identified via a circRNA microarray. The relationship between circMAST1 levels and clinicopathological features of CCa was evaluated using the clinical specimens and data of 131 patients with CCa. In vivo and in vitro experiments, including xenograft animal models, cell proliferation assay, transwell assay, RNA pull-down assay, whole-transcriptome sequencing, RIP assay, and RNA-FISH, were performed to investigate the effects of circMAST1 on the malignant behavior of CCa.ResultsCircMAST1 was significantly downregulated in CCa tissues, and low expression of CircMAST1 was correlated with a poor prognosis. Moreover, our results demonstrated that circMAST1 inhibited tumor growth and lymph node metastasis of CCa. Mechanistically, circMAST1 competitively sequestered N-acetyltransferase 10 (NAT10) and hindered Yes-associated protein (YAP) mRNA ac4C modification to promote its degradation and inhibit tumor progression in CCa.ConclusionsCircMAST1 plays a major suppressive role in the tumor growth and metastasis of CCa. In particular, circMAST1 can serve as a potential biomarker and novel target for CCa.

Negative Instance Guided Self-Distillation Framework for Whole Slide Image Analysis.

Histopathology image classification is an important clinical task, and current deep learning-based whole-slide image (WSI) classification methods typically cut WSIs into small patches and cast the problem as multi-instance learning. The mainstream approach is to train a bag-level classifier, but their performance on both slide classification and positive patch localization is limited because the instance-level information is not fully explored. In this article, we propose a negative instance-guided, self-distillation framework to directly train an instance-level classifier end-to-end. Instead of depending only on the self-supervised training of the teacher and the student classifiers in a typical self-distillation framework, we input the true negative instances into the student classifier to guide the classifier to better distinguish positive and negative instances. In addition, we propose a prediction bank to constrain the distribution of pseudo instance labels generated by the teacher classifier to prevent the self-distillation from falling into the degeneration of classifying all instances as negative. We conduct extensive experiments and analysis on three publicly available pathological datasets: CAMELYON16, PANDA, and TCGA, as well as an in-house pathological dataset for cervical cancer lymph node metastasis prediction. The results show that our method outperforms existing methods by a large margin. Code will be publicly available.

DHCR7 promotes lymph node metastasis in cervical cancer through cholesterol reprogramming-mediated activation of the KANK4/PI3K/AKT axis and VEGF-C secretion

Cervical cancer (CC) patients with lymph node metastasis (LNM) have a poor prognosis. However, the molecular mechanism of LNM in CC is unclear, and there is no effective clinical treatment. Here, we found that 7-dehydrocholesterol reductase (DHCR7), an enzyme that catalyzes the last step of cholesterol synthesis, was upregulated in CC and closely related to LNM. Gain-of-function and loss-of-function experiments proved that DHCR7 promoted the invasion ability of CC cells and lymphangiogenesis in vitro and induced LNM in vivo. The LNM-promoting effect of DHCR7 was partly mediated by upregulating KN motif and ankyrin repeat domains 4 (KANK4) expression and subsequently activating the PI3K/AKT signaling pathway. Alternatively, DHCR7 promoted the secretion of vascular endothelial growth factor-C (VEGF-C), and thereby lymphangiogenesis. Interestingly, cholesterol reprogramming was needed for the DHCR7-mediated promotion of activation of the KANK4/PI3K/AKT axis, VEGF-C secretion, and subsequent LNM. Importantly, treatment with the DHCR7 inhibitors AY9944 and tamoxifen (TAM) significantly inhibited LNM of CC, suggesting the clinical application potential of DHCR7 inhibitors in CC. Collectively, our results uncover a novel molecular mechanism of LNM in CC and identify DHCR7 as a new potential therapeutic target.

SNHG3/WISP2 Axis Promotes Hela Cell Migration and Invasion via Activating Wnt/β-Catenin Signaling.

Cervical cancer (CC) poses a significant threat to women's health and has a relatively poor prognosis due to local invasion and metastasis. It is, therefore, crucial to elucidate the molecular mechanisms of CC metastasis. SNHG3 has been implicated in various tumor metastasis processes, but its involvement in CC has not been thoroughly studied. Our study aimed to investigate the role of SNHG3 in metastasis and elucidate its underlying mechanisms in CC. LncRNA SNHG3 expression in CC tissues was analyzed using TCGA and GSE27469 databases. Normal cervical epithelial cells and CC cell lines were used to detect mRNA expression of SNHG3 via quantitative reverse transcription polymerase chain reaction (qRT-PCR). With RNA interference (RNAi) technology, antisense oligonucleotides (ASO) can act on HeLa cells to knockdown target gene expression. The influence of SNHG3 on cell migration and invasion were determined by wound healing and transwell assays. Transcriptome sequencing (RNA-seq) was used to seek abnormally expressed genes between SNHG3 knockdown cells and control cells. The expressions of epithelial-mesenchymal transition (EMT) and Wnt/β-catenin signaling related proteins were detected using western blot. SNHG3 was obviously up-regulated in CC tissues and cell lines, and ectopic expression of SNHG3 was associated with lymph node metastasis of CC. Knockdown of SNHG3 significantly inhibited cell migration and invasion in CC. Further molecular mechanism studies showed that SNHG3 knockdown could down-regulate the expression of WNT1 Inducible Signaling Pathway Protein 2 (WISP2) so as to inhibit the activation of the Wnt/β-catenin signaling pathway, and regulated the expression of EMT-related markers, that promoted the protein expression of E-cadherin, as well as decreased the expression of N-cadherin and vimentin. SNHG3 appears to exert a pro-metastatic effect in CC, as evidenced by inhibition of cell migration and invasion upon SNHG3 knockdown. EMT also appears to be attenuated. Of interest is the down-regulation of WISP2 following SNHG3 knockdown leads to the inactivation of the Wnt/β-catenin signaling pathway.

Developing a nomogram for preoperative prediction of cervical cancer lymph node metastasis by multiplex immunofluorescence

BackgroundMost traditional procedures can destroy tissue natural structure, and the information on spatial distribution and temporal distribution of immune milieu in situ would be lost. We aimed to explore the potential mechanism of pelvic lymph node (pLN) metastasis of cervical cancer (CC) by multiplex immunofluorescence (mIF) and construct a nomogram for preoperative prediction of pLN metastasis in patients with CC.MethodsPatients (180 IB1-IIA2 CC patients of 2009 FIGO (International Federation of Gynecology and Obstetrics)) were divided into two groups based on pLN status. Tissue microarray (TMA) was prepared and tumor-infiltrating immune markers were assessed by mIF. Multivariable logistic regression analysis and nomogram were used to develop the predicting model.ResultsMultivariable logistic regression analysis constructs a predictive model and the area under the curve (AUC) can reach 0.843. By internal validation with the remaining 40% of cases, a new ROC curve has emerged and the AUC reached 0.888.ConclusionsThis study presents an immune nomogram, which can be conveniently used to facilitate the preoperative individualized prediction of LN metastasis in patients with CC.

Whole-Lesion Apparent Diffusion Coefficient Histogram Analysis for Assessing Normal-Sized Lymph Node Metastasis in Cervical Cancer: Comparison Between Readout-Segmented and Single-Shot Echo-Planar Diffusion-Weighted Imaging.

To compare the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis derived from readout-segmented echo-planar imaging (RS-EPI) and single-shot echo-planar imaging (SS-EPI) diffusion-weighted imaging (DWI) in evaluating normal-sized lymph node metastasis (LNM) in cervical cancer. Seventy-six pathologically confirmed cervical cancer patients (stages IB and IIA) were enrolled, including 61 patients with non-LNM (group A) and 15 patients with normal-sized LNM (group B). The recorded tumor volume on T2-weighted imaging was the reference against which both DWIs were evaluated. Each ADC histogram parameter (including ADC max , ADC 90 , ADC median , ADC mean , ADC 10 , ADC min , ADC skewness , ADC kurtosis , and ADC entropy ) was compared between SS-EPI and RS-EPI and between the 2 groups. There was no significant difference in tumor volume between the 2 DWIs and T2-weighted imaging (both P > 0.05). Higher ADC max and ADC entropy but lower ADC 10 , ADC min and ADC skewness were found in SS-EPI than those in RS-EPI (all P < 0.05). For SS-EPI, lower ADC 90 and higher ADC kurtosis were found in group B than those in group A (both P < 0.05). For RS-EPI, lower ADC 90 and higher ADC kurtosis and ADC entropy were found in group B than those in group A (all P < 0.05). Readout-segmented echo-planar imaging ADC kurtosis showed the highest area under the curve of 0.792 in the differentiation of the 2 groups (sensitivity, 80%; specificity, 73.77%). Compared with SS-EPI, the ADC histogram parameters derived from RS-EPI were more accurate, and ADC kurtosis held great potential in differentiating normal-sized LNM in cervical cancer.

Amide Proton Transfer-Weighted Imaging Combined with ZOOMit Diffusion Kurtosis Imaging in Predicting Lymph Node Metastasis of Cervical Cancer

The aim of this study is to investigate the feasibility of amide proton transfer-weighted (APTw) imaging combined with ZOOMit diffusion kurtosis imaging (DKI) in predicting lymph node metastasis (LNM) in cervical cancer (CC). Sixty-one participants with pathologically confirmed CC were included in this retrospective study. The APTw MRI and ZOOMit diffusion-weighted imaging (DWI) were acquired. The mean values of APTw and DKI parameters including mean kurtosis (MK) and mean diffusivity (MD) of the primary tumors were calculated. The parameters were compared between the LNM and non-LNM groups using the Student's t-test or Mann-Whitney U test. Binary logistic regression analysis was performed to determine the association between the LNM status and the risk factors. The diagnostic performance of these quantitative parameters and their combinations for predicting the LNM was assessed with receiver operating characteristic (ROC) curve analysis. Patients were divided into the LNM group (n = 17) and the non-LNM group (n = 44). The LNM group presented significantly higher APTw (3.7 ± 1.1% vs. 2.4 ± 1.0%, p < 0.001), MK (1.065 ± 0.185 vs. 0.909 ± 0.189, p = 0.005) and lower MD (0.989 ± 0.195 × 10-3 mm2/s vs. 1.193 ± 0.337 ×10-3 mm2/s, p = 0.035) than the non-LNM group. APTw was an independent predictor (OR = 3.115, p = 0.039) for evaluating the lymph node status through multivariate analysis. The area under the curve (AUC) of APTw (0.807) was higher than those of MK (AUC, 0.715) and MD (AUC, 0.675) for discriminating LNM from non-LNM, but the differences were not significant (all p > 0.05). Moreover, the combination of APTw, MK, and MD yielded the highest AUC (0.864), with the corresponding sensitivity of 76.5% and specificity of 88.6%. APTw and ZOOMit DKI parameters may serve as potential noninvasive biomarkers in predicting LNM of CC.

CircVPRBP inhibits nodal metastasis of cervical cancer by impeding RACK1 O-GlcNAcylation and stability

Lymph node (LN) metastasis is one of the most malignant clinical features in patients with cervical cancer (CCa). Understanding the mechanism of lymph node metastasis will provide treatment strategies for patients with CCa. Circular RNAs (circRNA) play a critical role in the development of human cancers. However, the role and mechanism of circRNAs in lymph node metastasis remain largely unknown. Here, it is reported that loss expression of circRNA circVPRBP was closely associated with LN metastasis and poor survival of CCa patients. In vitro and in vivo assays showed that circVPRBP overexpression notably inhibited lymphangiogenesis and LN metastasis, whereas RfxCas13d mediated silencing of circVPRBP promoted lymphangiogenesis and the ability of the cervical cancer cells to metastasize to the LNs. Mechanistically, circVPRBP could bind to RACK1 and shield the S122 O-GlcNAcylation site to promote RACK1 degradation, resulting in inhibition of Galectin-1 mediated lymphangiogenesis and LN metastasis in CCa. Taken together, the results demonstrate that circVPRBP is a potential prognostic biomarker and a novel therapeutic target for LN metastasis in CCa patients.

Integrated single-cell transcriptome analysis of the tumor ecosystems underlying cervical cancer metastasis.

Cervical cancer (CC) is one of the most frequent female malignancies worldwide. However, the molecular mechanism of lymph node metastasis in CC remains unclear. In this study, we investigated the transcriptome profile of 51,507 single cells from primary tumors, positive lymph nodes (P-LN), and negative lymph nodes (N-LN) using single-cell sequencing. Validation experiments were performed using bulk transcriptomic datasets and immunohistochemical assays. Our results indicated that epithelial cells in metastatic LN were associated with cell- cycle-related signaling pathways, such as E2F targets, and mitotic spindle, and immune response-related signaling pathways, such as allograft rejection, IL2_STAT5_signaling, and inflammatory response. However, epithelial cells in primary tumors exhibited high enrichment of epithelial-mesenchymal translation (EMT), oxidative phosphorylation, and interferon alpha response. Our analysis then indicated that metastasis LN exhibited an early activated tumor microenvironment (TME) characterized by the decrease of naive T cells and an increase of cytotoxicity CD8 T cells, NK cells, FOXP3+ Treg cells compared with normal LN. By comparing the differently expressed gene of macrophages between tumor and metastatic LN, we discovered that C1QA+ MRC1low macrophages were enriched in a tumor, whereas C1QA+ MRC1high macrophages were enriched in metastatic LN. Finally, we demonstrated that cancer-associated fibroblasts (CAFs) in P-LN were associated with immune regulation, while CAFs in tumor underwent EMT. Our findings offered novel insights into the mechanisms of research, diagnosis, and therapy of CC metastasis.

Clinical application of laparoscopic sentinel lymph node mapping in early staged cervical cancer

Objective: To investigate the application of sentinel lymph node biopsy (SLNB) in early-staged cervical cancer by laparoscopy. Methods: It was a prospective, single-arm, single-center clinical study. Seventy-eight cases of cervical cancer patients were collected from July 2015 to December 2018 at the Fourth Hospital of Hebei Medical University. All the patients were injected with tracer into the disease-free block of cervical tissue after anesthesia by the same surgeon who learned sentinel lymph node (SLN) mapping technique in Memorial Sloan-Kettering Cancer Center, and underwent SLN mapping followed by complete pelvic lymphadenectomy. Moreover, all the dissected lymph nodes were stained with hematoxylin eosin staining (HE) pathological examination. Besides, the negative SLN on hematoxylin-eosin staining were detected by immunohistochemistry cytokeratin staining micro-metastasis. To analyze the distribution, detection rate, false negative rate the sensitivity and negative predictive value of the SLN in early-staged cervical cancer by laparoscopy, and explore the value of SLN mapping in predicting the lymph nodes metastasis in early-staged cervical cancer. Results: The overall detection rate of SLN in cervical cancer was 99% (77/78), bilateral detection rate was 87% (68/78). The average of 12.4 lymph node (LN) and 3.6 SLN were dissected for each patients each side. SLN of cervical cancer were mainly distributed in the obturator space (61.5%, 343/558), followed by external iliac (23.5%, 131/558), common iliac (7.3%, 41/558), para-uterine (3.8%, 21/558), internal iliac (2.2%, 12/558), para abdominal aorta (1.1%, 6/558), and anterior sacral lymphatic drainage area (0.7%, 4/558). Fourteen cases of LN metastasis were found among all 78 cases. There were a total of 38 positive LN, including 26 SLN metastasis and 12 none sentinel LN metastasis. Through immunohistochemical staining and pathological ultra-staging, 1 SLN was found to be isolated tumor cells (ITC), and 5 SLNs were found to be micro-metastases (MIC), accounting for 23% (6/26) of positive SLN. SLN mapping with pathological ultra-staging improved the prediction of LN metastasis in cervical cancer (2/14). Metastatic SLN mainly distributed in the obturator space (65%, 17/26), peri-uterine region (12%, 3/26), common iliac region (15%, 4/26), and external iliac region (8%, 2/26). The consistency of the diagnosis of lymph node metastasis by SLN biopsy and postoperative retroperitoneal lymph node metastasis showed that the Kappa value was 1.000 (P<0.001), indicated that the metastasis status of SLN and retroperitoneal lymph node were completely consistent. The sensitivity, specificity, accuracy, false-negative rate, and negative predictive value of SLN biopsy in the diagnosis of lymph node metastasis were 100%, 100%, 100%, 0, and 100%, respectively. Conclusions: SLN in early-staged cervical cancer patients were mainly distributed in the obturator and external iliac space, pathalogical ultra-staging of SLN could improve the prediction of LN metastasis. Intraoperative SLN mapping is safe, feasible and could predict the state of retroperitoneal LN metastasis in early-staged cervical cancer. SLNB may replace systemic pelvic lymphadenectomy.

Expression of GMFB in High-Grade Cervical Intraepithelial Neoplasia and Its Role in Cervical Cancer.

Cervical intraepithelial neoplasia (CIN) is a collective term for specific precancerous lesions associated with cervical cancer (CC). Although it has been affirmed with slow development of several levels of cellular changes, the existing poor prognosis calls for an urgent need to diagnose CIN at early stage and be aware of markers related to its pathogenesis and prognosis. We explored the expression level of a newly marker GMFB and its regulatory effect on CIN and CC. Patient samples and cell models were included. Bioinformatic studies were taken to predict its binding to miR-143-3p, miR-26b-5p, miR-191-5p, and miR-223-3p. Luciferase reporter and RNA pull-down assays were used to validate the prediction. Edu assay and flow cytometry were used to measure the regulation of GMFB on proliferation and apoptosis of CC cells. qRT-PCR was used for mRNA expression level detection. The results showed that GMFB was targeted by miR-143-3p, miR-26b-5p, miR-191-5p, and miR-223-3p. It had elevated expression in both CIN and CC samples. GMFB had highly prognostic value for CIN, and lymph node metastasis of CC was much associated with high GMFB expression level. Besides, silencing of GMFB inhibited CC cell proliferation and elevated cell apoptosis. In conclusion, we determined that GMFB has regulatory effect on high grade CIN and CC, which could lighten a novel way in exploring their pathogenesis and improving accuracy of prognosis.

Receptor for activated C kinase 1 promotes cervical cancer lymph node metastasis via the glycolysis‑dependent AKT/mTOR signaling.

Cervical cancer (CC), an aggressive form of squamous cell carcinoma, is characterized by early-stage lymph node metastasis and an extremely poor prognosis. The authors have previously demonstrated that patients with CC have aberrant glycolysis. The upregulation of receptor for activated C kinase 1 (RACK1) is associated with CC lymph node metastasis (LNM). However, its role in mediating aerobic glycolysis in CC LNM remains unclear. In the present study, 1H nuclear magnetic resonance analysis revealed a significant association between RACK1 expression and the glycolysis/gluconeogenesis pathway. Additionally, RACK1 knockdown inhibited aerobic glycolysis and lymphangiogenesis in vitro and suppressed CC LNM in vivo. Furthermore, protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling was identified as a critical RACK1-regulated pathway that increased lymphangiogenesis in CC. Co-immunoprecipitation, immunofluorescence and western blot analysis revealed that RACK1 activated AKT/mTOR signaling by interacting with insulin-like growth factor 1 receptor (IGF1R). POU class 2 homeobox 2 (POU2F2) bound to the RACK1 promoter and regulated its transcription, thereby functionally contributing to glycolysis and lymphangiogenesis in CC. Of note, the admin-istration of 2-deoxy-D-glucose, which attenuates glycolysis, inhibited RACK1-induced lymphangiogenesis in CC. The correlations between RACK1, IGF1R, POU2F2 and hexokinase 2 were further confirmed in CC tissues. Thus, RACK1 plays a crucial role in CC tumor LNM by regulating glycolysis via IGF1R/AKT/mTOR signaling. Thus, the targeting of the POU2F2/RACK1/IGF1R/AKT/mTOR signaling pathway may provide a novel treatment strategy for CC.

FASN promotes lymph node metastasis in cervical cancer via cholesterol reprogramming and lymphangiogenesis

Cervical cancer (CC) patients with lymph node metastasis (LNM) have a poor prognosis. Clarification of the detailed mechanisms underlying LNM may provide potential clinical therapeutic targets for CC patients with LNM. However, the molecular mechanism of LNM in CC is unclear. In the present study, we demonstrated that fatty acid synthase (FASN), one of the key enzymes in lipid metabolism, had upregulated expression in the CC samples and was correlated with LNM. Moreover, multivariate Cox proportional hazards analysis identified FASN as an independent prognostic factor of CC patients. Furthermore, gain-of-function and loss-of-function approaches showed that FASN promoted CC cell migration, invasion, and lymphangiogenesis. Mechanistically, on the one hand, FASN could regulate cholesterol reprogramming and then activate the lipid raft-related c-Src/AKT/FAK signaling pathway, leading to enhanced cell migration and invasion. On the other hand, FASN induced lymphangiogenesis by secreting PDGF-AA/IGFBP3. More importantly, knockdown of FASN with FASN shRNA or the inhibitors C75 and Cerulenin dramatically diminished LNM in vivo, suggesting that FASN plays an essential role in LNM of CC and the clinical application potential of FASN inhibitors. Taken together, our findings uncover a novel molecular mechanism in LNM of CC and identify FASN as a novel prognostic factor and potential therapeutic target for LNM in CC.

PET-CT versus MRI in the diagnosis of lymph node metastasis of cervical cancer: A meta-analysis.

To compare the clinical application value of positron emission tomography-computed tomography (PET-CT) and magnetic resonance imaging (MRI) in the diagnosis of cervical cancer lymph node metastasis. We searched PubMed and other databases for the studies comparing the use of PET-CT and MRI for the diagnosis of cervical cancer lymph node metastasis up to January 20, 2021. We strictly followed the inclusion and exclusion criteria to screen the literature and extract the data. Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 tool was used for quality evaluation of included studies, and Revman 5.3 and Stata 15.0 software were used for evaluating heterogeneity, synthesize sensitivity (SEN), specificity (SPE), positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and the area under the curve (AUC) and comparing the pretest and posttest probabilities. Finally, 11 studies were included for meta-analysis. The synthesized results indicated that the SEN value of PET-CT was 0.65 (0.60 ~ 0.69) and SPE was 0.93 (0.91 ~ 0.94), and the SEN value of MRI was 0.58 (0.54 ~ 0.63) and SPE was 0.91 (0.90 ~ 0.92). AUC of PET-CT was 0.824, which was significantly higher than that of MRI (AUC=0.702; p < .05). The subgroup analysis showed that the AUC value of the study based on study design and use of blinding methods was not statistically significant (all p > .05). There was no obvious publication bias in the synthesized analysis of the diagnostic value of PET-CT and MRI (all p > .05). HIGHLIGHTS: To compare positron emission tomography-computed tomography (PET-CT) and magnetic resonance imaging (MRI) in diagnosis of cervical cancer lymph node metastasis. Synthesize sensitivity value of PET-CT was comparable with that of MRI. Area under the curve of PET-CT was significantly higher than that of MRI. There was no obvious publication bias in synthesized analysis.

Deep learning nomogram for predicting lymph node metastasis using computed tomography image in cervical cancer.

Deep learning (DL) has been used on medical images to grade, differentiate, and predict prognosis in many tumors. To explore the effect of computed tomography (CT)-based deep learning nomogram (DLN) for predicting cervical cancer lymph node metastasis (LNM) before surgery. In total, 418 patients with stage IB-IIB cervical cancer were retrospectively enrolled for model exploration (n = 296) and internal validation (n = 122); 62 patients from another independent institution were enrolled for external validation. A convolutional neural network (CNN) was used for DL features extracting from all lesions. The least absolute shrinkage and selection operator (Lasso) logistic regression was used to develop a deep learning signature (DLS). A DLN incorporating the DLS and clinical risk factors was proposed to predict LNM individually. The performance of the DLN was evaluated on internal and external validation cohorts. Stage, CT-reported pelvic lymph node status, and DLS were found to be independent predictors and could be used to construct the DLN. The combination showed a better performance than the clinical model and DLS. The proposed DLN had an area under the curve (AUC) of 0.925 in the training cohort, 0.771 in the internal validation cohort, and 0.790 in the external validation cohort. Decision curve analysis and stratification analysis suggested that the DLN has potential ability to generate a personalized probability of LNM in cervical cancer. The proposed CT-based DLN could be used as a personalized non-invasive tool for preoperative prediction of LNM in cervical cancer, which could facilitate the choice of clinical treatment methods.

Clinical value of MRI, serum SCCA, and CA125 levels in the diagnosis of lymph node metastasis and para-uterine infiltration in cervical cancer

BackgroundCervical cancer shows great differences in depth of invasion, metastasis, and other biological behaviors. The location of the lesion is special, so it is usually difficult to determine the clinical stage. This study aimed to explore the clinical value of magnetic resonance imaging (MRI) and tumor serum markers for the preoperative diagnosis of cervical cancer lymph node metastasis and para-uterine invasion.MethodsA total of 200 patients with cervical cancer admitted to our hospital from January 2019 to January 2020 were collected as the research subjects. Comparing the diagnosis results of preoperative MRI scan, serum tumor markers, and postoperative pathological examination using single factor comparison, we determined the MRI scan results, the comprehensive matching rate between serum tumor markers (squamous cell carcinoma antigen (SCCA), carbohydrate antigen 125 (CA125)) and postoperative pathological results, and the differences of sensitivity, specificity, and accuracy in the prediction of lymph node metastasis and para-uterine infiltration of cervical cancer.ResultsThe levels of SCCA and CA125 in patients with para-uterine invasion and lymph node metastasis were higher than those of patients without invasion and metastasis. Among them, the level of SCCA was significantly different (P<0.05). The level of CA125 was not statistically significant (P>0.05), so MRI combined with serum SCCA was selected for combined diagnosis in the later period. The sensitivity, specificity, and accuracy of MRI diagnosis of cervical cancer and para-uterine infiltrating lymph node metastasis and metastasis were 55.2, 91.6, and 89.5% and 55.2, 91.6, and 89.5%, respectively. These data in MRI combined with serum SCCA were 76.3, 95.3, and 94.3% and 63.2, 96.0, and 95.1%, respectively. The accuracy of tumor markers combined with MRI in the diagnosis of cervical cancer lymph node metastasis and para-uterine invasion was higher than that of MRI.ConclusionsMRI combined with serum SCCA can more accurately identify cervical cancer lymph node metastasis and para-uterine invasion compared with MRI alone. Tumor marker combined with MRI diagnosis is an important auxiliary method for cervical cancer treatment and can provide comprehensive and reliable clinical evidence for evaluation before cervical cancer surgery.

Heart Rate Variability is an Independent Predictor of Lymph Node Metastasis in Patients with Cervical Cancer.

PurposeHeart rate variability (HRV) has been reported as a useful biomarker for prognostic factors in a variety of cancers. The purpose of this study was to explore the predictive value of preoperative HRV for lymph node metastasis (LNM) in patients with cervical cancer (CC).Patients and MethodsA total of 77 patients with CC were included, including 18 LNM and 59 non-LNM patients. A five-minute resting electrocardiogram (ECG) was collected before surgery for the analysis of HRV time domain, frequency domain and Poincaré plot parameters (ie, SDNN, RMSSD, LF, HF, LF/HF, SD1, SD2 and SD2/SD1). Student’s t-tests and logistic regression were performed to determine the relationship between HRV and LNM.ResultsThe LNM group had significantly lower SDNN, LF, and SD2 than the non-LNM group (all p < 0.05; all Cohen’s d > 0.5). Binary logistic regression analysis indicated that SDNN, LF and SD2 were still significantly associated with LNM. Specifically, for each 1 ms decrease in SDNN and SD2 and each 1 logarithmic unit decrease in ln (LF), the odds of LNM increased by 12%, 9%, and 86%, respectively (all p < 0.05).ConclusionThese findings suggest an association between HRV and CC LNM, and HRV could be a potential noninvasive biomarker for the prediction of LNM in CC patients.