Cervical Cancer Invasion Research Articles

Radiomics based on MRI in predicting lymphovascular space invasion of cervical cancer: a meta-analysis.

The objective of this meta-analysis is to assess the efficacy of radiomics techniques utilizing magnetic resonance imaging (MRI) for predicting lymphovascular space invasion (LVSI) in patients with cervical cancer (CC). A comprehensive literature search was conducted in databases including PubMed, Embase, Cochrane Library, Medline, Scopus, CNKI, and Wanfang, with studies published up to 08/04/2024, being considered for inclusion. The meta-analysis was performed using Stata 15 and Review Manager 5.4. The quality of the included studies was evaluated using the Quality Assessment of Diagnostic Accuracy Studies 2 and Radiomics Quality Score tools. The analysis encompassed the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). Summary ROC curves were constructed, and the AUC was calculated. Heterogeneity was investigated using meta-regression. Statistical significance was set at p ≤ 0.05. There were 13 studies involving a total of 2,245 patients that were included in the meta-analysis. The overall sensitivity and specificity of the MRI-based model in the Training set were 83% (95% CI: 77%-87%) and 72% (95% CI: 74%-88%), respectively. The AUC, DOR, PLR, and NLR of the MRI-based model in the Training set were 0.89 (95% CI: 0.86-0.91), 22 (95% CI: 12-40), 4.6 (95% CI: 3.1-7.0), and 0.21 (95% CI: 0.16-0.29), respectively. Subgroup analysis revealed that the AUC of the model combining radiomics with clinical factors [0.90 (95% CI: 0.87-0.93)] was superior to models based on T2-weighted imaging (T2WI) sequence [0.78 (95% CI: 0.74-0.81)], contrast-enhanced T1-weighted imaging (T1WI-CE) sequence [0.85 (95% CI: 0.82-0.88)], and multiple sequences [0.86 (95% CI: 0.82-0.89)] in the Training set. The pooled sensitivity and specificity of the model integrating radiomics with clinical factors [83% (95% CI: 73%-89%) and 86% (95% CI: 73%-93%)] surpassed those of models based on the T2WI sequence [79% (95% CI: 71%-85%) and 72% (95% CI: 67%-76%)], T1WI-CE sequence [78% (95% CI: 67%-86%) and 78% (95% CI: 68%-86%)], and multiple sequences [78% (95% CI: 67%-87%) and 79% (95% CI: 70%-87%)], respectively. Funnel plot analysis indicated an absence of publication bias (p > 0.05). MRI-based radiomics demonstrates excellent diagnostic performance in predicting LVSI in CC patients. The diagnostic performance of models combing radiomics and clinical factors is superior to that of models utilizing radiomics alone. https://www.crd.york.ac.uk/PROSPERO/#myprospero, identifier CRD42024538007.

Inhibiting SNX10 induces autophagy to suppress invasion and EMT and inhibits the PI3K/AKT pathway in cervical cancer.

Cervical cancer (CC) is a prevalent malignancy among women with high morbidity and poor prognosis. Sorting nexin 10 (SNX10) is a newly recognized cancer regulatory factor, while its action on CC progression remains elusive. Hence, this study studied the effect of SNX10 on CC development and investigated the mechanism. The SNX10 level in CC and the overall survival of CC cases with different SNX10 expressions were determined by bioinformatics analysis in GEPIA. The SNX10 expression in tumor tissues and clinical significance were studied in 64 CC cases. The overall survival was assessed using Kaplan-Meier analysis. The formation of LC3 was evaluated using immunofluorescence. Cell invasion was measured using the Transwell assay. Epithelial-to-mesenchymal transition (EMT) was determined by observing cell morphology and assessing EMT marker levels. A xenograft tumor was constructed to evaluate tumor growth. SNX10 was elevated in CC tissues and cells, and the CC cases with high SNX10 levels exhibited poor overall survival. Besides, SNX10 correlated with the FIGO stage, lymph node invasion, and stromal invasion of CC. SNX10 silencing induced CC cell autophagy and suppressed CC cell invasion and EMT. Meanwhile, silenced SNX10 could suppress invasion and EMT via inducing autophagy. Furthermore, SNX10 inhibition suppressed the PI3K/AKT pathway. Moreover, silenced SNX10 restrained the tumor growth, autophagy, and EMT of CC in vivo. SNX10 was enhanced in CC and correlated with poor prognosis. Silenced SNX10 induced autophagy to suppress invasion and EMT and inhibited the PI3K/AKT pathway in CC, making SNX10 a valuable molecule for CC therapy.

Study on the Role of EPHB6 in Inhibiting the Malignant Progression of Cervical Cancer C33A Cells by Binding to CBX7.

Cervical cancer stands as the most frequently diagnosed malignancy affecting the female reproductive. The erythropoietin-producing hepatocyte (Eph) family tyrosine kinases play important roles in tumorigenesis and cancer aggression. However, the exact role of EPHB6 in cervical cancer remains unknown. The present study investigated the role of EPHB6 in the malignant process of cervical cancer. GEPIA, tnmplot and kmplot database was used to study the expression of EPHB6 in cervical cancer tissues. western blotting was used to detect the expression of EPHB6, CyclinD, CDK4, CDK6, CBX7, MMP2 and MMP9. CCK8 and EDU staining were used to detect cell proliferation. Wound healing and transwell were used to detect cell proliferation and migration. Flow cytometry was used to detect cell cycle level. The linkedomics database was used to predict the correlation of EPHB6 and CBX7 in cervical cancer. Subsequently, HDOCK server was used to predict the combination of EPHB6 and CBX7. Our current results suggested that the expression of EPHB6 is reduced in cervical cancer tissues and cell lines, and the lower the expression, the worse the prognosis. Moreover, overexpression of EPHB6 inhibits cell proliferation, invasion and migration and cycle acceleration of C33A cells. Furthermore, EPHB6 and CBX7 bind to each other in C33A cells, and EPHB6 inhibits cell proliferation, invasion, migration and cell cycle acceleration in cervical cancer by binding to CBX7. EPHB6 expression is reduced in cervical cancer tissues and cells. Its overexpression inhibits proliferation, invasion, migration, and cell cycle acceleration in C33A cells, exhibiting synergy when bound to CBX7.

RNF113A as a poor prognostic factor promotes metastasis and invasion of cervical cancer through miR197/PRP19/P38MAPK signaling pathway

It has been discovered that aberrant expression of RNF113A plays a significant role in various diseases, including esophageal cancer, hepatocellular carcinoma, and X-linked trichothiodystrophy syndrome. Nevertheless, its functional implications in cervical cancer (CC) remain unclear. The objective of this study was to investigate the role of RNF113A in both the development and prognosis of CC. To achieve this objective, a total of sixty cases were included in the follow-up investigation. The findings revealed a significant up-regulation of RNF113A protein in CC tissues compared to paired paracancerous tissues, and a high expression level of RNF113A was strongly associated with malignant phenotypes such as lymph node metastasis, differentiation degree, depth of invasion, and FIGO stage. Meanwhile, RNF113A was found to be an independent prognostic risk factor, with its high expression significantly correlating with a reduced overall survival period in patients. To elucidate the underlying cause and mechanism of the unfavorable prognosis associated with RNF113A, comprehensive functional investigations were conducted both in vitro and in vivo.Interestingly, it was revealed that RNF113A promoted migration and invasion while inhibiting apoptosis of CC cells, thereby contributing to a poor prognosis. Mechanistically, RNF113A regulated the progression and prognosis of CC through the miR197/Prp19/p38Mark signaling pathway. Overall, our findings underscore the potential clinical significance of RNF113A as an unfavorable prognostic factor in CC.

Fgf17: A regulator of the mid/hind brain boundary in mammals

The Fibroblast growth factor (FGFs) family consists of at least 22 members that exert their function by binding and activating fibroblast growth factor receptors (FGFRs). The Fgf8/FgfD subfamily member, Fgf17, is located on human chromosome 8p21.3 and mouse chromosome 14 D2. In humans, FGF17 can be alternatively spliced to produce two isoforms (FGF17a and b) whereas three isoforms are present in mice (Fgf17a, b, and c), however, only Fgf17a and Fgf17b produce functional proteins. Fgf17 is a secreted protein with a cleavable N-terminal signal peptide and contains two binding domains, namely a conserved core region and a heparin binding site. Fgf17 mRNA is expressed in a wide range of different tissues during development, including the rostral patterning centre, midbrain-hindbrain boundary, tailbud mesoderm, olfactory placode, mammary glands, and smooth muscle precursors of major arteries. Given its broad expression pattern during development, it is surprising that adult Fgf17−/− mice displayed a rather mild phenotype; such that mutants only exhibited morphological changes in the frontal cortex and mid/hind brain boundary and changes in certain social behaviours. In humans, FGF17 mutations are implicated in several diseases, including Congenital Hypogonadotropic Hypogonadism and Kallmann Syndrome. FGF17 mutations contribute to CHH/KS in 1.1% of affected individuals, often presenting in conjunction with mutations in other FGF pathway genes like FGFR1 and FLRT3. FGF17 mutations were also identified in patients diagnosed with Dandy-Walker malformation and Pituitary Stalk Interruption Syndrome, however, it remains unclear how FGF17 is implicated in these diseases. Altered FGF17 expression has been observed in several cancers, including prostate cancer, hematopoietic cancers (acute myeloid leukemia and acute lymphoblastic leukemia), glioblastomas, perineural invasion in cervical cancer, and renal cell carcinomas. Furthermore, FGF17 has demonstrated neuroprotective effects, particularly during ischemic stroke, and has been shown to improve cognitive function in ageing mice.

Cervical cancer-produced neuromedin-B reprograms Schwann cells to initiate perineural invasion

Perineural invasion (PNI) is a new approach of cervical cancer invasion and metastasis, involving the cross-talk between tumor and nerve. However, the initiating signals and cellular interaction mechanisms of PNI remain largely elusive. The nerve-sparing radical hysterectomy (NSRH) proposed to improve postoperative quality of life is only applicable to cervical cancer patients without PNI. Therefore, it is important to elucidate the underlying mechanisms initiating PNI, and suggest the effective biomarkers to predict PNI before NSRH surgery. Here, we found that PNI is the characteristic of advanced cervical cancer, and Schwann cells were the antecedent cells that initiating PNI. Further, neuropeptide neuromedin B (NMB) produced by cervical cancer cells was determined to induce PNI by reprogramming Schwann cells, including driving their morphological and transcriptional changes, promoting their proliferation and migration, and initiating PNI by secreting CCL2 and directing axon regeneration. Mechanistically, cervical cancer cells-produced NMB activated its receptor NMBR in Schwann cells, and opened the T-type calcium channels to stimulate Ca2+ influx through PKA signaling, which could be blocked by the inhibitor. Clinically, combined examination of serum NMB and CCL2 levels was suggested to effectively predict PNI in cervical cancer patients. Our data demonstrate that cervical cancer-produced NMB initiates the reprograming of Schwann cells, which then direct axon regeneration, thus causing PNI onset. The elevated serum NMB and CCL2 levels may be useful for the decision-making to nerve sparing during hysterectomy surgery of cervical cancer patients.

The value of amide proton transfer imaging combined with serum CA125 levels in predicting lymph vascular invasion in cervical cancer before surgery.

Preoperative prediction of lymphovascular space invasion (LVSI) is crucial for improving the prognosis of patients with cervical cancer. To evaluate the value of preoperative amide proton transfer (APT) imaging combined with serum CA125 levels for predicting LVSI in cervical cancer. This retrospective study included 80 patients with cervical cancer who underwent preoperative magnetic resonance imaging, including APT imaging. Serum CA125 levels were measured using a fully automated immunoassay analyzer and chemiluminescence method. The presence of LVSI was determined based on the pathological results after surgery. Among the 40 patients who met the requirements, 29 had postoperative pathological confirmation of LVSI, while 11 did not. The areas under the receiver operating characteristic curves (AUC) of preoperative APT and CA125 levels predicting LVSI were 0.889 and 0.687, respectively. When the APT value was 2.9%, the corresponding Youden index was the highest (0.702), with a sensitivity of 79.3% and specificity of 90.9%. When the critical value of the preoperative serum CA15 level was 25.3 u/mL, the corresponding Youden index was the highest (0.508), with a sensitivity of 69.0% and a specificity of 81.8%. The sensitivity and specificity of preoperative APT imaging combined with serum CA125 in predicting LVSI were 82.7% and 100%, respectively, with a Youden's index of 0.828 and an AUC of 0.923. The combination of preoperative APT imaging and serum CA125 levels is valuable for predicting LVSI in cervical cancer. Diagnostic efficacy is highest when the APT value is >2.9% and the serum CA125 level is >25.3 u/mL.

Based on 3D-PDU and clinical characteristics nomogram for prediction of lymph node metastasis and lymph-vascular space invasion of early cervical cancer preoperatively

PurposeTo develop and validate a nomogram based on 3D-PDU parameters and clinical characteristics to predict LNM and LVSI in early-stage cervical cancer preoperatively.Materials and methodsA total of first diagnosis 138 patients with cervical cancer who had undergone 3D-PDU examination before radical hysterectomy plus lymph dissection between 2014 and 2019 were enrolled for this study. Multivariate logistic regression analyses were performed to analyze the 3D-PDU parameters and selected clinicopathologic features and develop a nomogram to predict the probability of LNM and LVSI in the early stage. ROC curve was used to evaluate model differentiation, calibration curve and Hosmer-Lemeshow test were used to evaluate calibration, and DCA was used to evaluate clinical practicability.ResultsMenopause status, FIGO stage and VI were independent predictors of LNM. BMI and maximum tumor diameter were independent predictors of LVSI. The predicted AUC of the LNM and LSVI models were 0.845 (95%CI,0.765–0.926) and 0.714 (95%CI,0.615–0.813). Calibration curve and H-L test (LNM groups P = 0.478; LVSI P = 0.783) all showed that the predicted value of the model had a good fit with the actual observed value, and DCA indicated that the model had a good clinical net benefit.ConclusionThe proposed nomogram based on 3D-PDU parameters and clinical characteristics has been proposed to predict LNM and LVSI with high accuracy, demonstrating for the first time the potential of non-invasive prediction. The probability derived from this nomogram may have the potential to provide valuable guidance for physicians to develop clinical individualized treatment plans of FIGO patients with early cervical cancer.

Evaluating the image quality and local tumor invasion of uterine cancer by MUSE DWI with RPG

Diffusion-weighted imaging (DWI) is widely utilized for evaluating uterine diseases. However, the prevalent technique, single-shot echo planar imaging (ssEPI), is hindered by notable image distortion and low spatial resolution. Therefore, optimizing uterine DWI sequences is vital for improving image quality. To investigate the efficacy of multiplexed sensitivity encoding (MUSE) combined with reverse polarity gradient (RPG) in enhancing uterine DWI quality and assessing local invasion in endometrial and cervical cancer, we included 149 patients. Each patient underwent DWI of the uterus using ssEPI, MUSE, and RPG-MUSE techniques. We compared these three sequences regarding image quality, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), geometric distortion rate (GDR), ADC values, accuracy in determining the extent of cancer invasion, and the Area Under the Curve (AUC) for identifying endometrial cancer and benign endometrial lesions using ADC values. The results indicated that RPG-MUSE DWI had less artifacts than MUSE and ssEPI (P < 0.05). Lesions were more apparent in MUSE and RPG-MUSE sequences compared to ssEPI (P < 0.05), with RPG-MUSE providing clearer lesion edges (P < 0.05). Additionally, RPG-MUSE DWI demonstrated higher SNR and CNR than ssEPI and MUSE (P < 0.05), along with a lower GDR (P < 0.05). The ADC values did not show significant differences among the three sequences (P > 0.05). Furthermore, the AUC of the ROC for detecting endometrial cancer and benign endometrial lesions using ADC values showed no significant differences across the sequences (P = 0.7609, 0.7186, and 0.8706, respectively). When combining each DWI sequence with T2WI for FIGO staging, RPG-MUSE and MUSE exhibited better alignment with pathology findings compared to ssEPI (P < 0.05). Overall, RPG-MUSE DWI showed fewer artifacts, higher SNR and CNR, reduced geometric distortion, and clearer lesion visualization compared to ssEPI and MUSE, leading to a more precise assessment of endometrial and cervical cancer invasion extent.

Perineural Invasion in Cervical Cancer: A Hidden Trail for Metastasis.

Perineural invasion (PNI), the neoplastic invasion of nerves, is an often overlooked pathological phenomenon in cervical cancer that is associated with poor clinical outcomes. The occurrence of PNI in cervical cancer patients has limited the promotion of Type C1 surgery. Preoperative prediction of the PNI can help identify suitable patients for Type C1 surgery. However, there is a lack of appropriate preoperative diagnostic methods for PNI, and its pathogenesis remains largely unknown. Here, we dissect the neural innervation of the cervix, analyze the molecular mechanisms underlying the occurrence of PNI, and explore suitable preoperative diagnostic methods for PNI to advance the identification and treatment of this ominous cancer phenotype.

LIMK1 promotes the development of cervical cancer by up-regulating the ROS/Src-FAK/cofilin signaling pathway.

In this study, we investigated the mechanism of action of LIMK1 in cervical cancer progression. The biological role of LIMK1 in regulating the growth, invasion, and metastasis of cervical cancer was studied in SiHa, CaSki cells and nude mice tumor models. The role of LIMK1 in the growth of cervical cancer was evaluated by HE staining. The role of LIMK1 in the invasion, metastasis, and proliferation of cervical cancer was evaluated by cell scratch, Transwell, and monoclonal experiments. The interaction among LIMK1, ROS, and Src was evaluated by Western blotting. The effects of regulating ROS and p-Src expression on LIMK1 in the migration/invasion and proliferation of cervical cancer cells were evaluated through cellular functional assays. Overexpression of LIMK1 promoted tumor growth in nude mice. Cell scratch, Transwell, and monoclonal experiments suggested that LIMK1 promoted the invasion, metastasis, and proliferation of cervical cancer cells. Western blotting suggested that LIMK1 can promote the expression of ROS-related proteins NOX2, NOX4, p-Src, and downstream proteins p-FAK, p-ROCK1/2, p-Cofilin-1, F-actin and inhibit the expression of p-SHP2 protein. Correction experiments showed that LIMK1 regulated the expression of p-FAK and p-Cofilin-1 proteins by regulating ROS and p-Src. Through the detection of cervical cancer cell functions, it was found that the activation of ROS and p-Src induced by LIMK1 is an early event that promotes the migration, proliferation, and invasion of cervical cancer cells. LIMK1 promotes the expression of F-actin and promotes the development of cervical cancer by regulating the oxidative stress/Src-mediated p-FAK/p-ROCK1/2/p-Cofilin-1 pathway.

Multiparametric mri-based radiomics nomogram for predicting lymph-vascular space invasion in cervical cancer

PurposeTo develop and validate a multiparametric magnetic resonance imaging (mpMRI)-based radiomics model for predicting lymph-vascular space invasion (LVSI) of cervical cancer (CC).MethodsThe data of 177 CC patients were retrospectively collected and randomly divided into the training cohort (n=123) and testing cohort (n = 54). All patients received preoperative MRI. Feature selection and radiomics model construction were performed using max-relevance and min-redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) on the training cohort. The models were established based on the extracted features. The optimal model was selected and combined with clinical independent risk factors to establish the radiomics fusion model and the nomogram. The diagnostic performance of the model was assessed by the area under the curve.ResultsFeature selection extracted the thirteen most important features for model construction. These radiomics features and one clinical characteristic were selected showed favorable discrimination between LVSI and non-LVSI groups. The AUCs of the radiomics nomogram and the mpMRI radiomics model were 0.838 and 0.835 in the training cohort, and 0.837 and 0.817 in the testing cohort.ConclusionThe nomogram model based on mpMRI radiomics has high diagnostic performance for preoperative prediction of LVSI in patients with CC.

The activation of Piezo1 channel promotes invasion and migration via the release of extracellular ATP in cervical cancer

BackgroundThe mechanosensitive ion channel Piezo1 has emerged as a potential prognostic and therapeutic target in different types of cancers. The aim of this study was to determine the expression levels and underlying mechanisms of Piezo1 in the invasion and migration processes in cervical cancer. MethodsInitially, we employed qRT-PCR, western blot, and immunohistochemical staining techniques to assess the disparity in Piezo1 expression in cervical cancer tissues and cells. Subsequently, we conducted wound healing, transwell assays and phalloidin staining to observe the effects of stable Piezo1 silencing and Piezo1 selective agonist Yoda1 on the invasion and migration capabilities. The release of extracellular ATP was assessed using the enhanced ATP assay kit. Furthermore, we conducted rescue experiments to investigate whether the activation of Piezo1 facilitates cervical cancer invasion and migration through extracellular ATP. Finally, we constructed xenograft tumor models to determine weather the Piezo1 selective agonist Yoda1 influenced the tumor growth in vivo. ResultsIn our study, we found that Piezo1 expression was elevated in both cervical cancer tissues and cells, with the highest levels observed in patients with lymph node metastasis. Knocking down Piezo1 resulted in a significant reduction in the invasion and migration capabilities of cervical cancer cells, whereas the use of the Piezo1 selective agonist Yoda1 enhanced these capabilities. Moreover, the activation of Piezo1 channels was found to regulate the release of extracellular ATP. Mechanistically, the activation of Piezo1 might facilitate cervical cancer invasion, migration, and pseudopodium formation through the release of extracellular ATP. And Piezo1 was an important molecule for the tumor growth of cervical cancer in vivo. ConclusionOur findings revealed that Piezo1 facilitated the invasion and migration of cervical cancer by releasing extracellular ATP, which might hold potential as a valuable target for prognostic and therapeutic interventions in cervical cancer.

The value of contrast-enhanced ultrasound in cervical cancer assessed in comparison with magnetic resonance imaging.

Currently, magnetic resonance imaging (MRI) is the most commonly used imaging method in the assessment of the loco-regional extension in cervical cancer. Contrast-enhanced ultrasound (abbreviated CEUS) is being investigated as an alternative or complement to the MRI investigation. To evaluate the performance of CEUS in identifying loco-regional invasion of cervical cancer compared to MRI, considered the accepted reference standard. Sixty-one patients with histopathologically confirmed cervical cancer were investigated as part of the pre-treatment workup by CEUS and MRI. We calculated the accuracy and concordance of CEUS versus MRI for tumor invasion in the vagina, bladder, rectum, parametrium, and uterus. For the time-intensity curve associated parameters analyzed (TTPK, AUC, peak intensity, wash in and wash out gradient) we calculated sensitivity, specificity and threshold value of positivity, for tumor invasion at the above-mentioned sites, with graphical representation of the ROC (receiver operating characteristic) curve. CEUS was highly accurate in detecting bladder (93.4%, 95% CI: 87.2-99.6) and uterine invasion (88.5%, 95% CI: 80.5-96.5). Substantial agreement between CEUS and MRI was observed for invasion in the uterine body (k=0.77, 95% CI: 0.56-0.98) and bladder (k=0.56, 95% CI: 0.35-0.77). ROC curve analysis for loco-regional invasions showed that the wash in gradient at a cut-off value of 2.23 had a sensitivity of 76% and a specificity of 67% in predicting uterine invasion. Our results demonstrate high accuracy and good agreement between CEUS and MRI regarding especially uterine and bladder invasion. This imaging method could help select patients in early stages for fertility sparing surgery, and also be of use in cases in which early bladder invasion is suspected.

Intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI for predicting parametrial invasion in cervical cancer.

This study aimed to assess the predictive efficacy of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in parametrial invasion (PMI) in cervical cancer patients. A total of 83 cervical cancer patients (32 PMI-positive and 51 PMI-negative) retrospectively underwent pretreatment IVIM-DWI and DCE-MRI scans. IVIM-DWI parameters included apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D*), and perfusion fraction (f). DCE-MRI parameters included volume transfer constant (Ktrans), flux rate constant (Kep), and fractional extravascular extracellular space volume (Ve). Logistic regression analyses were conducted to identify independent variables associated with PMI. Receiver operating characteristic curves were generated to assess the predictive performance of significant parameters. Multivariable analysis revealed that the MRI parameters D (odds ratio [OR]: 7.05; 95% CI 1.78-27.88; P = 0.005), D* (OR 6.58; 95% CI 1.49-29.10; P = 0.01), f (OR 5.12; 95% CI 1.23-21.37; P = 0.03), Ktrans (OR 4.60; 95% CI 1.19-17.81; P = 0.03), and Kep (OR 4.90; 95% CI 1.25-19.18; P = 0.02) were independent predictors of PMI in cervical cancer patients. The combined parameter incorporating these parameters demonstrated the highest performance in predicting PMI, yielding an area under the curve of 0.906, sensitivity of 84.4%, and specificity of 86.3%. The proposed combined parameter exhibited favorable performance in identifying PMI in cervical cancer patients.

Retracted] MicroRNA‑329‑3p targets MAPK1 to suppress cell proliferation, migration and invasion in cervical cancer.

Following the publication of the above article, a concerned reader drew to the Editor's attention that certain of the Transwell cell migration and invasion assay data featured in Figs. 5C and 6C were strikingly similar to data appearing in different form in other articles written by different authors at different research institutes that had already been published elsewhere prior to the submission of this paper to Oncology Reports, or were submitted for consideration for publication at around the same time. In view of the fact that certain of these data had already apparently been published prior to the submission of this article for publication, the Editor of Oncology Reports has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 37: 2743‑2750, 2017; DOI: 10.3892/or.2017.5555].

Retraction: "Downregulation of microRNA-205 inhibits cell invasion and angiogenesis of cervical cancer through TSLC1-mediated Akt signaling pathway".

Retraction: "Downregulation of microRNA-205 inhibits cell invasion and angiogenesis of cervical cancer through TSLC1-mediated Akt signaling pathway" by Fang Zhang, Jian Liu, Bei-Bei Xie, J Cell Physiol 2019, 234: 18626-18638. The above article, published online on 2 May 2019 in Wiley Online Library (https://onlinelibrary.wiley.com/doi/10.1002/jcp.28501) has been retracted by agreement between the authors, the journal's Editors in Chief, Alexander Hutchison, and Wiley Periodicals LLC. The retraction has been agreed due to concerns related to the data presented in the article. Several flaws and inconsistencies between results presented and experimental methods described were found. Additionally, some figure elements have been published elsewhere in a different scientific context. Thus, the conclusions of this article are considered to be invalid by the editors.

Perineural invasion in cervical cancer: A multicenter retrospective study

ObjectiveThe study aimed to evaluate the accuracy of perineural invasion (PNI) diagnosis in cervical cancer, and to analyze the impact of PNI on the prognosis and postoperative adjuvant treatment decisions for cervical cancer. MethodsA retrospective pathological review of PNI in cervical cancer was conducted from 2004 to 2016 in 15 hospitals. ResultsThis study included a total of 1208 cases, comprising 273 cases with PNI and 935 cases without. The false positive rate and false negative rate of PNI diagnosis were 5.35% (50/935) and 33.33% (91/273), respectively. Adenocarcinoma, deep stromal invasion, lymphovascular space invasion (LVSI) (+), and margin involvement were independent risk factors for PNI. Both 5-year overall survival rate (OS) and 5-year disease-free survival rate (DFS) of PNI group were worse than non-PNI group. PNI was an independent risk factor for 5-year OS and 5-year DFS. In cases receiving standard postoperative adjuvant treatment, among those with two intermediate-risk factors, both 5-year OS and DFS were worse in the PNI group. Among cases with three intermediate-risk factors or at least one high-risk factor, there was no difference in 5-year OS between the two groups, but 5-year DFS was worse in the PNI group. ConclusionThe diagnosis of PNI in cervical cancer was not accurate. Adenocarcinoma, deep stromal invasion, LVSI, and margin involvement were independent risk factors for PNI. PNI was an independent risk factor for 5-year OS and DFS. PNI has the potential to serve as a new high-risk factor, thus providing guidance for postoperative adjuvant therapy.

Multi-Parametric MRI Combined with Radiomics for the Evaluation of Lymphovascular Space Invasion in Cervical Cancer

Multi-Parametric MRI Combined with Radiomics for the Evaluation of Lymphovascular Space Invasion in Cervical Cancer

A nomogram of preoperative indicators predicting lymph vascular space invasion in cervical cancer.

To develop predictive nomograms of lymph vascular space invasion (LVSI) in patients with early-stage cervical cancer. We identified 403 patients with cervical cancer from the Affiliated Hospital of Jiangnan University from January 2015 to December 2019. Patients were divided into the training set (n = 242) and the validation set (n = 161), with patients in the training set subdivided into LVSI (+) and LVSI (-) groups according to postoperative pathology. Preoperative hematologic indexes were compared between the two subgroups. Univariate and multivariate logistic regression analyses were used to analyze the independent risk factors for LVSI, from which a nomogram was constructed using the R package. LVSI (+) was present in 94 out of 242 patients in the training set, accompanied by a significant increase in the preoperative squamous cell carcinoma antigen (SCC), white blood cells (WBC), neutrophil (NE), platelet (PLT), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic inflammation index (SII), and tumor size (P < 0.05). Univariate analysis showed that SCC, WBC, NE, NLR, PLR, SII, and tumor size were correlated with LVSI (P < 0.05), and multivariate analysis showed that tumor size, SCC, WBC, and NLR were independent risk factors for LVSI (P < 0.05). A nomogram was correspondingly established with good performance in predicting LVSI [training: ROC-AUC = 0.845 (95% CI: 0.731-0.843) and external validation: ROC-AUC = 0.704 (95% CI: 0.683-0.835)] and high accuracy (training: C-index = 0.787; external validation: C-index = 0.759). The nomogram based on preoperative tumor size, SCC, WBC, and NLR had excellent accuracy and discriminative capability to assess the risk of LVSI in early-stage cervical cancer patients.