Relationship Between High Density of Peritumoral Lymphatic Vessels and Biological Behavior of Cervical Cancer

Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in early-stage cervical squamous cell carcinoma

BACKGROUND

Surgery combined with radiotherapy substantially escalates the likelihood of encountering complications in early-stage cervical squamous cell carcinoma(ESCSCC). We aimed to investigate the feasibility of Deep-learning-based radiomics of intratumoral and peritumoral MRI images to predict the pathological features of adjuvant radiotherapy in ESCSCC and minimize the occurrence of adverse events associated with the treatment.

METHODS

A dataset comprising MR images was obtained from 289 patients who underwent radical hysterectomy and pelvic lymph node dissection between January 2019 and April 2022. The dataset was randomly divided into two cohorts in a 4:1 ratio.The postoperative radiotherapy options were evaluated according to the Peter/Sedlis standard. We extracted clinical features, as well as intratumoral and peritumoral radiomic features, using the least absolute shrinkage and selection operator (LASSO) regression. We constructed the Clinical Signature (Clinic_Sig), Radiomics Signature (Rad_Sig) and the Deep Transformer Learning Signature (DTL_Sig). Additionally, we fused the Rad_Sig with the DTL_Sig to create the Deep Learning Radiomic Signature (DLR_Sig). We evaluated the prediction performance of the models using the Area Under the Curve (AUC), calibration curve, and Decision Curve Analysis (DCA).

RESULTS

The DLR_Sig showed a high level of accuracy and predictive capability, as demonstrated by the area under the curve (AUC) of 0.98(95% CI: 0.97-0.99) for the training cohort and 0.79(95% CI: 0.67-0.90) for the test cohort. In addition, the Hosmer-Lemeshow test, which provided p-values of 0.87 for the training cohort and 0.15 for the test cohort, respectively, indicated a good fit. DeLong test showed that the predictive effectiveness of DLR_Sig was significantly better than that of the Clinic_Sig(P < 0.05 both the training and test cohorts). The calibration plot of DLR_Sig indicated excellent consistency between the actual and predicted probabilities, while the DCA curve demonstrating greater clinical utility for predicting the pathological features for adjuvant radiotherapy.

CONCLUSION

DLR_Sig based on intratumoral and peritumoral MRI images has the potential to preoperatively predict the pathological features of adjuvant radiotherapy in early-stage cervical squamous cell carcinoma (ESCSCC).

Lymphatic vessels in cancer

The lymphatic system, composed of initial and collecting lymphatic vessels as well as lymph nodes that are present in almost every tissue of the human body, acts as an essential transport system for fluids, biomolecules and cells between peripheral tissues and the central circulation. Consequently, it is required for normal body physiology but is also involved in the pathogenesis of various diseases, most notably cancer. The important role of tumor-associated lymphatic vessels and lymphangiogenesis in the formation of lymph node metastasis has been elucidated during the last two decades, whereas the underlying mechanisms and the relation between lymphatic and peripheral organ dissemination of cancer cells are incompletely understood. Lymphatic vessels are also important for tumor-host communication, relaying molecular information from a primary or metastatic tumor to regional lymph nodes and the circulatory system. Beyond antigen transport, lymphatic endothelial cells, particularly those residing in lymph node sinuses, have recently been recognized as direct regulators of tumor immunity and immunotherapy responsiveness, presenting tumor antigens and expressing several immune-modulatory signals including PD-L1. In this review, we summarize recent discoveries in this rapidly evolving field and highlight strategies and challenges of therapeutic targeting of lymphatic vessels or specific lymphatic functions in cancer patients.

Prognostic value of lymphatic vessel density in oral squamous cell carcinoma

AIMS

Lymphatic vessel density (LVD) for the evaluation of tumor metastasis and prognosis remains controversial. The aim of this study was to elucidate the association between tumor cells and lymphatic vessels, and evaluate LVD in oral squamous cell carcinoma (OSCC).

MAIN METHODS

128 OSCC cases were used to determine the expression of lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1) and vascular endothelial growth factor C (VEGF-C). Mann-Whitney or Kruskal-Wallis tests were employed to analyze the association between clinicopathological data and intratumoral LVD (ILVD), peritumoral LVD (PLVD), and VEGF-C; comparisons between ILVD and PLVD were made with t-test. Correlations between LVD and VEGF-C were analyzed by Spearman's correlation coefficient. Disease-specific survival curves were obtained with Kaplan-Meier method and compared using the log-rank test. Cox multiple regression was used to clarify the independent effect of clinicopathological data on clinical outcome.

KEY FINDINGS

Tumor tissues were positively stained with LYVE-1 and VEGF-C. Both tumor metastasis and recurrence were associated with ILVD. A significant association between ILVD and VEGF-C expression was observed (P < 0.05). A significant association between high ILVD and poor disease-specific survival was observed (P < 0.05).

SIGNIFICANCE

This study showed that ILVD was significantly associated with increased lymphatic metastasis, tumor recurrence, and reduced disease-specific survival in patients with OSCC. ILVD could be an indicator to predict the prognosis of OSCC.

A multi-scanner study of MRI radiomics in uterine cervical cancer: prediction of in-field tumor control after definitive radiotherapy based on a machine learning method including peritumoral regions

PURPOSE

This study aimed to identify the most appropriate volume of interest (VOI) setting in prognostic prediction using pretreatment magnetic resonance imaging (MRI) radiomic analysis for cervical cancer (CC) treated with definitive radiotherapy.

MATERIALS AND METHODS

The study participants were 87 patients who had undergone pretreatment MRI and definitive radiotherapy for CC. VOI_tumor was created with tumor alone and VOI_+4 mm-VOI_+20 mm mechanically expanded by 4-20 mm around each VOI_tumor in axial T2-weighted images (T2WI) and an apparent diffusion coefficient (ADC) map. A model was constructed to predict recurrence within the irradiation field within 2 years after treatment using imaging features from the VOI of each sequence. Sorting ability was evaluated by area under the receiver operator characteristic curve (AUC-ROC) analysis.

RESULTS

VOI expansion improved AUC-ROCs compared with the predictive models of VOI_tumor (0.59 and 0.67 in T2WI and ADC, respectively). The AUC-ROCs of the models with imaging features from expanded VOI_+4 mm in T2WI and VOI_+4 mm and VOI_+8 mm in ADC were 0.82, 0.82, and 0.86, respectively.

CONCLUSION

Recurrence could be predicted with high accuracy using expanded VOI for CC treated with definitive radiotherapy, suggesting that including the pathological characteristics of invasive margins in radiomics may improve predictive ability.

Tumor lymphangiogenesis and new drug development

Traditionally, tumor-associated lymphatic vessels have been regarded as passive by-standers, serving simply as a drainage system for interstitial fluid generated within the tumor. However, with growing evidence that tumors actively induce lymphangiogenesis, and that the number of lymphatic vessels closely correlates with metastasis and clinical outcome in various types of cancer, this picture has changed dramatically in recent years. Tumor-associated lymphatic vessels have now emerged as a valid therapeutic target to control metastatic disease, and the first specific anti-lymphangiogenic drugs have recently entered clinical testing. Furthermore, we are just beginning to understand the whole functional spectrum of tumor-associated lymphatic vessels, which not only concerns transport of fluid and metastatic cells, but also includes the regulation of cancer stemness and specific inhibition of immune responses, opening new venues for therapeutic applications. Therefore, we predict that specific targeting of lymphatic vessels and their function will become an important tool for future cancer treatment.

Improved computer-assisted analysis of the global lymphatic network in human cervical tissues

Lymphatic dissemination is a key event in cervical cancer progression and related tumor lymphatic markers are viewed as promising prognostic factor of nodal extension. However, validating such parameters requires an objective characterization of the lymphatic vasculature. Here, we performed a global analysis of the lymphatic network using a new computerized method applied on whole uterine cervical digital images. Sixty-eight cases of cervical neoplasia (12 CIN3, 10 FIGO stage 1A and 46 stage IB1) and 10 cases of normal cervical tissue were reacted with antibodies raised against D2-40, D2-40/p16 and D2-40/Ki67. Immunostained structures were automatically detected on whole slides. The lymphatic vessel density (D2-40), proliferating lymphatic vessel density (D2-40/ki67) and spatial lymphatic distribution in respect to the adjacent epithelium were assessed from normal cervix to early cervical cancer and correlated with lymphovascular space invasion and lymph node status. Prominent lymphatic vessel density and proliferating lymphatic vessel density are detected under the transformation zone of benign cervix and no further increase is noted during cancer progression. Notably, a shift of lymphatic vessel distribution toward the neoplastic edges is detected. In IB1 cervical cancer, although intra- and peritumoral lymphatic vessel density are neither correlated with lymphovascular space invasion nor with lymph node metastasis, a specific spatial distribution with more lymphatic vessels in the vicinity of tumor edges is predictive of lymphatic dissemination. Herein, we provide a new computerized method suitable for an innovative detailed analysis of the lymphatic network. We show that the transformation zone of the benign cervix acts as a baseline lymphangiogenic niche before the initiation of neoplastic process. During cancer progression, this specific microenvironment is maintained with lymphatic vessels even in closer vicinity to tumor cells.