Endocrine self and gut non-self intersect in the pancreatic lymph nodes.
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ABSTRACT:
SUBMITTER: Turley SJ
PROVIDER: S-EPMC1308925 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Nodal status and tumor site are prognostic factors for resectable pancreatic ductal adenocarcinoma (PDAC). Parameters for nodal status are diverse, and the number of examined lymph nodes (eNs) needed for good prognosis are uncertain. We try to modify staging system of resectable PDAC with parameters mentioned above by recursive partitioning analysis. Methods: Patients from the Surveillance, Epidemiology, and End Results (SEER) database were divided into training cohort and internal validation cohort, randomly. PDAC patients from Sun Yat-sen University Cancer Center were regarded as external validation cohort. The training cohort was used to refine staging model by recursive partitioning analysis, while the internal validation cohort and the external validation cohort were applied to assess discriminatory capacity of staging model. For parameters included in the modified model, their effects were studied. Results: The number of eNs, tumor site and tumor size were risk factors for positive nodal status. Lymph nodes ratio (LNR), tumor site, eNs and T stages of 8th the American Joint Committee on Cancer (AJCC) were selected to develop a refined model, dividing patients into 5 groups of different outcomes, preceding 8th AJCC classification. Besides, we found that (1) for small PDAC (diameter < 1cm), lymph node metastasis was rarely found; (2) enough eNs were needed to ensure better prognosis of node-negative patients; (3) tumors in the head of pancreas were prone to lymph nodes metastasis; (4) for node-positive patients, LNR was a better nodal parameter compared to positive lymph nodes (pNs). Conclusion: Our improved staging system helps to illuminate the interactions among tumor site, size and eNs.
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Project description:Type 1 diabetes (T1D) is a polygenic autoimmune disorder caused by autoreactive T cells that recognize pancreatic islet antigens and subsequently destroy insulin-producing β-cells. Pancreatic lymph nodes (PLN) are an essential site for the development of T1D, where tolerance to pancreatic self-antigens is first broken and the autoimmune responses are amplified. The purpose of this study was to identify candidate genes and pathways in the PLN that may contribute to the pathogenesis of T1D using a mouse model of T1D.
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Project description:Type 1 diabetes (T1D) is a polygenic autoimmune disorder caused by autoreactive T cells that recognize pancreatic islet antigens and subsequently destroy insulin-producing β-cells. Pancreatic lymph nodes (PLN) are an essential site for the development of T1D, where tolerance to pancreatic self-antigens is first broken and the autoimmune responses are amplified. The purpose of this study was to identify candidate genes and pathways in the PLN that may contribute to the pathogenesis of T1D using a mouse model of T1D. Genome-wide gene expression was measured in individual NOD PLN at 10 days (n=6), 4 weeks (n=6) or 12 weeks of age (n=5), against a pooled sample of age-matched NOD.B10 PLN as the control (n≥6), using Agilent Whole Mouse Genome Microarrays.
2015-03-09 | E-GEOD-66658 | biostudies-arrayexpress
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Project description:BACKGROUND:Globally, colorectal cancer (CRC) is the third and second leading cancer in men and women respectively with 600,000 deaths per year. Traditionally, clinicians have relied solely on nodal disease involvement, and measurements such as lymph node ratio (LNR; the ratio of metastatic/positive lymph nodes to total number of lymph nodes examined), when determining patient prognosis in CRC. The log odds of positive lymph nodes (LODDS) is a logistic transformation formula that uses pathologic lymph node data to stratify survival differences among patients within a single stage of disease. This formula allows clinicians to identify whether patients with clinically aggressive tumours fall into higher-risk groups regardless of nodal positivity and can potentially guide adjuvant treatment modalities. The aim of this study was to investigate whether LODDS in colon cancer provides better prognostication compared to LNR. METHODS:A retrospective study of patients on the prospectively maintained Cabrini Monash University Department of Surgery colorectal neoplasia database, incorporating data from hospitals in Melbourne Australia, identified patients entered between January 2010 and March 2016. Association of LODDS and LNR with clinical variables were analysed. Disease-free (DFS) and overall (OS) survival were investigated with Cox regression and Kaplan-Meier survival analyses. RESULTS:There were 862 treatment episodes identified in the database (402 male, 47%). The median patient age was 73 (range 22-100?years). There were 799 colonic cancers and 63 rectosigmoid cancers. The lymph node yield (LNY) was suboptimal (<?12) in 168 patients (19.5%) (p?=?0.05). The 5-year OS for the different LNR groups were 86, 91 and 61% (p?<?0.001) for LNR0 (655 episodes), LNR1 (128 episodes) and LNR2 (78 episodes), respectively. For LODDS, they were 85, 91 and 61% (p?<?0.001) in LODDS0 (569 episodes), LODDS1 (217 episodes) and LODDS2 (75 episodes) groups (p?<?0.001). Overall survival rates were comparable between the LNR and LODDS group and for LNY?<?12 and stage III patients when each were sub-grouped by LODDS and LNR. CONCLUSION:This study has shown for that the prognostic impact of LODDS is comparable to LNR for colon cancer patients. Accordingly, LNR is recommended for prognostication given its ease of calculation.
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