Incidence and Impact of Lymph Node Metastases in Advanced Ovarian Cancer: Implications for Surgical Treatment

Development and validation of an ultrasound‑based radiomics nomogram to predict lymph node status in patients with high-grade serous ovarian cancer: a retrospective analysis

BACKGROUND

Despite advances in medical imaging technology, the accurate preoperative prediction of lymph node status remains challenging in ovarian cancer. This retrospective study aimed to investigate the feasibility of using ultrasound-based radiomics combined with preoperative clinical characteristics to predict lymph node metastasis (LNM) in patients with high-grade serous ovarian cancer (HGSOC).

RESULTS

Patients with 401 HGSOC lesions from two institutions were enrolled: institution 1 for the training cohort (n = 322) and institution 2 for the external test cohort (n = 79). Radiomics features were extracted from the three preoperative ultrasound images of each lesion. During feature selection, primary screening was first performed using the sample variance F-value, followed by recursive feature elimination (RFE) to filter out the 12 most significant features for predicting LNM. The radscore derived from these 12 radiomic features and three clinical characteristics were used to construct a combined model and nomogram to predict LNM, and subsequent 10-fold cross-validation was performed. In the test phase, the three models were tested with external test cohort. The radiomics model had an area under the curve (AUC) of 0.899 (95% confidence interval [CI]: 0.864-0.933) in the training cohort and 0.855 (95%CI: 0.774-0.935) in the test cohort. The combined model showed good calibration and discrimination in the training cohort (AUC = 0.930) and test cohort (AUC = 0.881), which were superior to those of the radiomic and clinical models alone.

CONCLUSIONS

The nomogram consisting of the radscore and preoperative clinical characteristics showed good diagnostic performance in predicting LNM in patients with HGSOC. It may be used as a noninvasive method for assessing the lymph node status in these patients.

Predictive value of PET metabolic parameters for occult lymph node metastases in PET/CT defined node-negative patients with advanced epithelial ovarian cancer

Accurate lymph node metastasis (LNM) prediction is crucial for patients with advanced epithelial ovarian cancer (AEOC) since it guides the decisions about lymphadenectomy. Previous studies have shown that occult lymph node metastasis (OLNM) is common in AEOC. The objective of our study is to quantitatively assess the probability of occult lymph node metastasis defined by 18F-Fluorodeoxyglucose PET/CT in AEOC and explore relationship between OLNM and PET metabolic parameters. The patients with pathologically confirmed AEOC who underwent PET/CT for preoperative staging at our institute were reviewed. Univariate and multivariate analysis were performed to evaluate the predictive value of PET/CT-related metabolic parameters for OLNM. The result of our study showed metastatic TLG index had a better diagnostic performance than other PET/CT-related metabolic parameters. Two variables were independently and significantly associated with OLNM in multivariate analysis: metastatic TLG index and primary tumor location. The logistic model combining metastatic TLG index, primary tumor location, and CA125 might be a promising tool to effectively predict the individualized possibility of OLNM for AEOC patients.

Molecular mechanisms of miR-1236 in the assessment of tumor lymphangiogenesis in human ovarian cancer patients

BACKGROUND

Tumor lymphangiogenesis is a critical component in the progression of cancers and specific microRNAs have been reported to be implicated in this process. Recent studies revealed the involvement of miR-1236 in lymphangiogenic signaling by targeting vascular endothelial growth factor receptor 3 (VEGFR3). However, the prognostic importance of miR-1236 and its clinical relevance for lymphangiogenesis in ovarian cancer (OC) remains unclear.

METHODS

The study included 52 ovarian tumors and 28 normal ovarian tissues. Quantitative real-time PCR was utilized to analyze the VEGFR3, VEGF-C, LYVE-1 and PROX1 mRNA expression as well as miR-1236. VEGFR3 protein expression was measured by immunohistochemistry staining. Immunohistochemistry for the podoplanin marker (D2-40) was performed to measure lymphatic vessel density (LVD). In addition, diagnostic evaluation based on the receiver-operating characteristic (ROC) curve was performed. The influence of miR-1236 on overall survival was evaluated by Kaplan-Meier method.

RESULTS

Here, we show that miR-1236 expression was significantly decreased in ovarian tumors compared with control tissues (p < 0.001) and correlated with advanced clinical stage, lymph node metastasis, distant metastasis and patient survival (All P < 0.05). Moreover, in ovarian tumors, LVD as well as the gene expression of VEGFR3, VEGF-C and LYVE-1, but not PROX1, were found to be remarkably higher compared with control tissues. We also detected a more robust positive staining for VEGFR3 in OC tissues than in control tissues. Furthermore, our results demonstrated an inverse association of miR-1236 expression with LVD, VEGFR3, LYVE-1 and PROX1 expression in OC tissues. The ROC curve analysis indicated that miR-1236 expression has the potential to be used as a diagnostic and prognostic biomarker in OC. Survival analysis further verified a lowered overall survival rate in patients with low miR-1236 expression than in those with high expression.

CONCLUSIONS

Our results provide evidence for the translational involvement of miR-1236 in the lymphangiogenesis of OC by regulating lymphangiogenesis-related factors and support the clinical importance of miR-1236 as a new diagnostic and prognostic biomarker for OC.

Preoperative Prediction of Metastasis for Ovarian Cancer Based on Computed Tomography Radiomics Features and Clinical Factors

Background

There is urgent need for an accurate preoperative prediction of metastatic status to optimize treatment for patients with ovarian cancer (OC). The feasibility of predicting the metastatic status based on radiomics features from preoperative computed tomography (CT) images alone or combined with clinical factors were investigated.

Methods

A total of 101 OC patients who underwent primary debulking surgery were enrolled. Radiomics features were extracted from the tumor volumes contoured on CT images with LIFEx package. Mann-Whitney U tests, least absolute shrinkage selection operator (LASSO), and Ridge Regression were applied to select features and to build prediction models. Univariate and regression analysis were applied to select clinical factors for metastatic prediction. The performance of models generated with radiomics features alone, clinical factors, and combined factors were evaluated and compared.

Results

Nine radiomics features were screened out from 184 extracted features to classify patients with and without metastasis. Age and cancer antigen 125 (CA125) were the two clinical factors that were associated with metastasis. The area under curves (AUCs) for the radiomics signature, clinical factors model, and combined model were 0.82 (95% CI, 0.66-0.98; sensitivity = 0.90, specificity = 0.70), 0.83 (95% CI, 0.67-0.95; sensitivity = 0.71, specificity = 0.8), and 0.86 (95% CI, 0.72-0.99, sensitivity = 0.81, specificity = 0.8), respectively.

Conclusions

Radiomics features alone or radiomics features combined with clinical factors are feasible and accurate enough to predict the metastatic status for OC patients.

A strangulated internal hernia beneath the left external iliac artery after radical hysterectomy with laparoscopic pelvic lymphadenectomy: a case report and literature review

Background

Ileum obstruction due to internal hernia beneath external iliac artery after pelvic lymph node dissection (PLND) is extremely rare. We reported a case of acute strangulated internal hernia between the left external iliac artery and psoas major as late complication of laparoscopic hysterectomy with pelvic lymphadenectomy.

Case presentation

A 46-year-old woman, who with histories of laparoscopic hysterectomy, bilateral salpingo-oophorectomy and PLND 9 years ago for the cervical malignant tumor, open appendectomy 18 years ago, visited our hospital complaining of aggravated left lower abdominal pain, bloating, nausea and vomiting from few hours ago. Left abdomen distention, tympanitic with rebound tenderness and muscular tension was detected during physical examinations. Accompanying with elevated inflammatory markers and mild intestinal dilatation showed in lab results and contrast-enhanced computed tomography (CT) respectively. After carefully reading the CT images, a small bowel was found between the left external iliac artery (EIA) and the psoas major, combined with the patient's surgical history, we suspected it might be internal hernia. Eventually, the emergency laparoscopic laparotomy confirmed our conjecture, the gap between the iliac vessels and the psoas major was closed with an absorbable suture, the patient was discharged on the fourth postoperative day.

Conclusion

Primary closure of peritoneal fissue maybe an effective measure to potentially prevent internal hernia. The choice of surgical approach for pelvic tumors still needs further exploration but faster diagnosis and immediate laparotomy might promise a better prognosis.

Inflammatory state of lymphatic vessels and miRNA profiles associated with relapse in ovarian cancer patients

Lymphogenic spread is associated with poor prognosis in epithelial ovarian cancer (EOC), yet little is known regarding roles of non-peri-tumoural lymphatic vessels (LVs) outside the tumour microenvironment that may impact relapse. The aim of this feasibility study was to assess whether inflammatory status of the LVs and/or changes in the miRNA profile of the LVs have potential prognostic and predictive value for overall outcome and risk of relapse. Samples of macroscopically normal human lymph LVs (n = 10) were isolated from the external iliac vessels draining the pelvic region of patients undergoing debulking surgery. This was followed by quantification of the inflammatory state (low, medium and high) and presence of cancer-infiltration of each LV using immunohistochemistry. LV miRNA expression profiling was also performed, and analysed in the context of high versus low inflammation, and cancer-infiltrated versus non-cancer-infiltrated. Results were correlated with clinical outcome data including relapse with an average follow-up time of 13.3 months. The presence of a high degree of inflammation correlated significantly with patient relapse (p = 0.033). Cancer-infiltrated LVs showed a moderate but non-significant association with relapse (p = 0.07). Differential miRNA profiles were identified in cancer-infiltrated LVs and those with high versus low inflammation. In particular, several members of the let-7 family were consistently down-regulated in highly inflamed LVs (>1.8-fold, p<0.05) compared to the less inflamed ones. Down-regulation of the let-7 family appears to be associated with inflammation, but whether inflammation contributes to or is an effect of cancer-infiltration requires further investigation.

Current insights into the metastasis of epithelial ovarian cancer - hopes and hurdles

BACKGROUND

Ovarian cancer is the most lethal gynecologic cancer and the fifth leading cause of cancer-related mortality in women worldwide. Despite various attempts to improve the diagnosis and therapy of ovarian cancer patients, the survival rate for these patients is still dismal, mainly because most of them are diagnosed at a late stage. Up to 90% of ovarian cancers arise from neoplastic transformation of ovarian surface epithelial cells, and are usually referred to as epithelial ovarian cancer (EOC). Unlike most human cancers, which are disseminated through blood-borne metastatic routes, EOC has traditionally been thought to be disseminated through direct migration of ovarian tumor cells to the peritoneal cavity and omentum via peritoneal fluid. It has recently been shown, however, that EOC can also be disseminated through blood-borne metastatic routes, challenging previous thoughts about ovarian cancer metastasis.

CONCLUSIONS

Here, we review our current understanding of the most updated cellular and molecular mechanisms underlying EOC metastasis and discuss in more detail two main metastatic routes of EOC, i.e., transcoelomic metastasis and hematogenous metastasis. The emerging concept of blood-borne EOC metastasis has led to exploration of the significance of circulating tumor cells (CTCs) as novel and non-invasive prognostic markers in this daunting cancer. We also evaluate the role of tumor stroma, including cancer associated fibroblasts (CAFs), tumor associated macrophages (TAMs), endothelial cells, adipocytes, dendritic cells and extracellular matrix (ECM) components in EOC growth and metastasis. Lastly, we discuss therapeutic approaches for targeting EOC. Unraveling the mechanisms underlying EOC metastasis will open up avenues to the design of new therapeutic options. For instance, understanding the molecular mechanisms involved in the hematogenous metastasis of EOC, the biology of CTCs, and the detailed mechanisms through which EOC cells take advantage of stromal cells may help to find new opportunities for targeting EOC metastasis.

Gene signature characteristic of elevated stromal infiltration and activation is associated with increased risk of hematogenous and lymphatic metastasis in serous ovarian cancer

Background

The clinical significance of hematogenous and lymphatic metastasis in ovarian cancer has been increasingly addressed, as it plays an imperative role in the formation of both intraperitoneal and distant metastases. Our objective is to identify the key molecules and biological processes potentially related to this relatively novel metastatic route in serous ovarian cancer.

Methods

Since lymphovascular space invasion (LVSI) is considered as the first step of hematogenous and lymphatic dissemination, we developed a gene signature mainly based on the transcriptome profiles with available information on LVSI status in the Cancer Genome Atlas (TCGA) dataset. We then explored the underlying biological rationale and prognostic value of the identified gene signature using multiple public databases.

Results

We observe that primary tumors with increased risk of hematogenous and lymphatic metastasis highly express a panel of genes, namely POSTN, LUM, THBS2, COL3A1, COL5A1, COL5A2, FAP1 and FBN1. The identified geneset is characterized by enhanced deposition of extracellular matrix and extensive stromal activation. Mechanistically, both the recruitment and the activation of stromal cells, especially fibroblasts, are closely associated with lymphovascular metastasis. Survival analysis further reveals that the elevated expression of the identified genes correlates to cancer progression and poor prognosis in patients with serous ovarian cancer.

Conclusions

Our findings indicate that tumor stroma supports the hematogenous and lymphatic spread of ovarian cancer, increasing tumor invasiveness and ultimately resulting in worse survival. Thus stroma-targeted therapies may improve the clinical outcomes in combination with cytoreductive surgery and chemotherapy.

The Role of Cancer Stem Cells and Mechanical Forces in Ovarian Cancer Metastasis

Ovarian cancer is an extremely lethal gynecologic disease; with the high-grade serous subtype predominantly associated with poor survival rates. Lack of early diagnostic biomarkers and prevalence of post-treatment recurrence, present substantial challenges in treating ovarian cancers. These cancers are also characterized by a high degree of heterogeneity and protracted metastasis, further complicating treatment. Within the ovarian tumor microenvironment, cancer stem-like cells and mechanical stimuli are two underappreciated key elements that play a crucial role in facilitating these outcomes. In this review article, we highlight their roles in modulating ovarian cancer metastasis. Specifically, we outline the clinical relevance of cancer stem-like cells, and challenges associated with their identification and characterization and summarize the ways in which they modulate ovarian cancer metastasis. Further, we review the mechanical cues in the ovarian tumor microenvironment, including, tension, shear, compression and matrix stiffness, that influence (cancer stem-like cells and) metastasis in ovarian cancers. Lastly, we outline the challenges associated with probing these important modulators of ovarian cancer metastasis and provide suggestions for incorporating these cues in basic biology and translational research focused on metastasis. We conclude that future studies on ovarian cancer metastasis will benefit from the careful consideration of mechanical stimuli and cancer stem cells, ultimately allowing for the development of more effective therapies.

Molecular Mechanisms Regulating Organ-Specific Metastases in Epithelial Ovarian Carcinoma

Epithelial ovarian carcinoma is the most predominant type of ovarian carcinoma, the deadliest gynecologic malignancy. It is typically diagnosed late when the cancer has already metastasized. Transcoelomic metastasis is the most predominant mechanism of dissemination from epithelial ovarian carcinoma, although both hematogenously and lymphogenously spread metastases also occur. In this review, we describe molecular mechanisms known to regulate organ-specific metastasis from epithelial ovarian carcinoma. We begin by discussing the sites colonized by metastatic ovarian carcinoma and rank them in the order of prevalence. Next, we review the mechanisms regulating the transcoelomic metastasis. Within this chapter, we specifically focus on the mechanisms that were demonstrated to regulate peritoneal adhesion—one of the first steps in the transcoelomic metastatic cascade. Furthermore, we describe mechanisms of the transcoelomic metastasis known to regulate colonization of specific sites within the peritoneal cavity, including the omentum. Mechanisms underlying hematogenous and lymphogenous metastatic spread are less comprehensively studied in ovarian cancer, and we summarize mechanisms that were identified to date. Lastly, we discuss the outcomes of the clinical trials that attempted to target some of the mechanisms described in this review.