Dataset Information

Esophageal adenocarcinoma and obesity: peritumoral adipose tissue plays a role in lymph node invasion.

ABSTRACT: Obesity is associated with cancer risk in esophageal adenocarcinoma (EAC). Adipose tissue directly stimulates tumor progression independently from body mass index (BMI), but the mechanisms are not fully understood. We studied the morphological, histological and molecular characteristics of peritumoral and distal adipose tissue of 60 patients with EAC, to investigate whether depot-specific differences affect tumor behavior. We observed that increased adipocyte size (a hallmark of obesity) was directly associated with leptin expression, angiogenesis (CD31) and lymphangiogenesis (podoplanin); however, these parameters were associated with nodal metastasis only in peritumoral but not distal adipose tissue of patients. We treated OE33 cells with conditioned media (CM) collected from cultured biopsies of adipose tissue and we observed increased mRNA levels of leptin and adiponectin receptors, as well as two key regulator genes of epithelial-to-mesenchymal transition (EMT): alpha-smooth muscle actin (?-SMA) and E-cadherin. This effect was greater in cells treated with CM from peritumoral adipose tissue of patients with nodal metastasis and was partially blunted by a leptin antagonist. Therefore, peritumoral adipose tissue may exert a direct effect on the progression of EAC by secreting depot-specific paracrine factors, and leptin is a key player in this crosstalk.

SUBMITTER: Trevellin E

PROVIDER: S-EPMC4484450 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Esophageal adenocarcinoma and obesity: peritumoral adipose tissue plays a role in lymph node invasion.

Trevellin Elisabetta E Scarpa Marco M Carraro Amedeo A Lunardi Francesca F Kotsafti Andromachi A Porzionato Andrea A Saadeh Luca L Cagol Matteo M Alfieri Rita R Tedeschi Umberto U Calabrese Fiorella F Castoro Carlo C Vettor Roberto R

Oncotarget 20150501 13

Obesity is associated with cancer risk in esophageal adenocarcinoma (EAC). Adipose tissue directly stimulates tumor progression independently from body mass index (BMI), but the mechanisms are not fully understood. We studied the morphological, histological and molecular characteristics of peritumoral and distal adipose tissue of 60 patients with EAC, to investigate whether depot-specific differences affect tumor behavior. We observed that increased adipocyte size (a hallmark of obesity) was dir ...[more]

PMID: 25857300

Similar Datasets

Project description:Obesity-related adverse health consequences occur predominately in individuals with upper body fat distribution commonly associated with increased central adiposity. Visceral adipose tissue accumulation is described to be the greatest driver of obesity-induced inflammation, however evidence also supports that the intestines fundamentally contribute to the development of obesity-induced metabolic disease. The visceral adipose depot shares the same vasculature and lymph drainage as the small intestine. We hypothesize that the visceral lymph node, which drains adipose tissue and the gastrointestinal tract, is central to the exacerbation of systemic pro-inflammation. Male C57BL/6 mice were fed CHOW or high fat diet (HFD) for 7 weeks. At termination the mesenteric depot, visceral lymph node and ileum, jejunum and Peyer's patches were collected. Cytokine concentration was determined in adipose tissue whereas immune cell populations where investigated in the visceral lymph node and intestinal segments by flow cytometry. Visceral adipose tissue and the gastrointestinal tract mutually influence immune cells enclosed within the visceral lymph node. HFD increased visceral lymph node immune cell number. This likely resulted from 1.) an increase in immune cells migration from the small intestines likely from activated dendritic cells that travel to the lymph node and 2.) cytokine effluent from visceral adipose tissue that promoted expansion, survival and retention of pro-inflammatory immune cells. Overall, the visceral lymph node, the immune nexus of visceral adipose tissue and the small intestines, likely plays a fundamental role in exacerbation of systemic pro-inflammation by HFD-induced obesity. The research of Tim Bartness greatly enhanced the understanding of adipose tissue regulation. Studies from his laboratory significantly contributed to our awareness of extrinsic factors that influence body fatness levels. Specifically, the work he produced eloquently demonstrated that adipose tissue was more complex than an insulating storage center; it was connected to our brains via the sympathetic and sensory nervous system. Mapping studies demonstrated that adipose tissue both receives and sends information to the brain. Further, his lab demonstrated that nervous system connections contributed to lipolysis, thermogenesis and adipocyte proliferation and growth. The work of Tim Bartness will continue to influence adipose tissue research. As such, Tim Bartness directly inspired the following research. Adipose tissue extrinsic factors are not limited to the peripheral nervous system. The lymphatic system is an additional extrinsic factor that cross talks with adipose tissue, however its role in this context is under emphasized. Here we begin to elucidate how the lymphatic system may contribute to the comorbidities associated with visceral adipose tissue accumulation.

Project description:Radiomics studies to predict lymph node (LN) metastasis has only focused on either primary tumor or LN alone. However, combining radiomics features from multiple sources may reflect multiple characteristic of the lesion thereby increasing the discriminative performance of the radiomic model. Therefore, the present study intends to evaluate the efficiency of integrative nomogram, created by combining clinical parameters and radiomics features extracted from gross tumor volume (GTV), peritumoral volume (PTV) and LN, for the preoperative prediction of LN metastasis in clinical cT1N0M0 adenocarcinoma. A primary cohort of 163 patients (training cohort, 113; and internal validation cohort, 50) and an external validation cohort of 53 patients with clinical stage cT1N0M0 were retrospectively included. Features were extracted from three regions of interests (ROIs): GTV; PTV (5.0 mm around the tumor) and LN on pre-operative contrast enhanced computed tomography (CT). LASSO logistic regression method was used to build radiomic signatures. Multivariable regression analysis was used to build a nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. The discriminative performance of nomogram was validated both internally and externally. The radiomic signatures using the features of GTV, PTV and LN showed a good ability in predicting LN metastasis with an area under the curve (AUC) of 0.74 (95% CI 0.60-0.88), 0.72 (95% CI 0.57-0.87) and 0.64 (95% CI 0.48-0.80) respectively in external validation cohort. The integration of different signature together further increases the discriminatory ability: GTV + PTV (GPTV): AUC 0.75 (95% CI 0.61-0.89) and GPTV + LN: AUC 0.76 (95% CI 0.61-0.91) in external validation cohort. An integrative nomogram of clinical parameters and radiomic features demonstrated further increase in discriminatory ability with AUC of 0.79 (95% CI 0.66-0.93) in external validation cohort. The nomogram showed good calibration. Decision curve analysis demonstrated that the radiomic nomogram was clinically useful. The integration of information from clinical parameters along with CT radiomics information from GTV, PTV and LN was feasible and increases the predictive performance of the nomogram in predicting LN status in cT1N0M0 adenocarcinoma patients suggesting merit of information integration from multiple sources in building prediction model.

Project description:Lymph nodes (LNs) are common sites of metastatic invasion in breast cancer, often preceding spread to distant organs and serving as key indicators of clinical disease progression. However, the mechanisms of cancer cell invasion into LNs are not well understood. Existing in vivo models struggle to isolate the specific impacts of the tumor-draining lymph node (TDLN) milieu on cancer cell invasion due to the co-evolving relationship between TDLNs and the upstream tumor. To address these limitations, we used live ex vivo LN tissue slices with intact chemotactic function to model cancer cell spread within a spatially organized microenvironment. After showing that BRPKp110 breast cancer cells were chemoattracted to factors secreted by naïve LN tissue in a 3D migration assay, we demonstrated that ex vivo LN slices could support cancer cell seeding, invasion, and spread. This novel approach revealed dynamic, preferential cancer cell invasion within specific anatomical regions of LNs, particularly the subcapsular sinus (SCS) and cortex, as well as chemokine-rich domains of immobilized CXCL13 and CCL1. While CXCR5 was necessary for a portion of BRPKp110 invasion into naïve LNs, disruption of CXCR5/CXCL13 signaling alone was insufficient to prevent invasion towards CXCL13-rich domains. Finally, we extended this system to pre-metastatic TDLNs, where the ex vivo model predicted a lower invasion of cancer cells. The reduced invasion was not due to diminished chemokine secretion, but it correlated with elevated intranodal IL-21. In summary, this innovative ex vivo model of cancer cell spread in live LN slices provides a platform to investigate cancer invasion within the intricate tissue microenvironment, supporting time-course analysis and parallel read-outs. We anticipate that this system will enable further research into cancer-immune interactions and allow isolation of specific factors that make TDLNs resistant to cancer cell invasion, which are challenging to dissect in vivo.

Dataset Information

Esophageal adenocarcinoma and obesity: peritumoral adipose tissue plays a role in lymph node invasion.

Publications

Esophageal adenocarcinoma and obesity: peritumoral adipose tissue plays a role in lymph node invasion.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets