2021
DOI: 10.1158/1940-6207.capr-20-0592
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Immune Responses Vary in Preinvasive Colorectal Lesions by Tumor Location and Histology

Abstract: Immune responses vary in colorectal cancers, which strongly influence prognosis. However, little is known about the variance in immune response within preinvasive lesions. The study aims to investigate how the immune contexture differs by clinicopathologic features (location, histology, dysplasia) associated with progression and recurrence in early carcinogenesis. We performed a cross-sectional study using preinvasive lesions from the surgical pathology laboratory at the Medical University of South Carolina. W… Show more

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Cited by 5 publications
(4 citation statements)
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“…In addition, it might indicate that the 'just-right' window varies across the colon, with lesions in the distal under selection for higher Wnt, e.g. due to enhanced immune surveillance 54 .…”
Section: Discussionmentioning
confidence: 99%
“…In addition, it might indicate that the 'just-right' window varies across the colon, with lesions in the distal under selection for higher Wnt, e.g. due to enhanced immune surveillance 54 .…”
Section: Discussionmentioning
confidence: 99%
“…This finding not only suggests the impact of the microbe-associated inflammatory response mediated by Th17 cells on cancer progression but also highlights the significant role of Th17 cells in the transition from precancerous lesions (colitis) to colorectal cancer ( 101 ). Similarly, the presence of Th17 cells has been observed in the progression from colorectal adenoma to colorectal cancer; however, it remains unclear whether microbes are involved in this process ( 102 ). The presence of Helicobacter pylori in gastric cancer also promotes the development of Th17 cells, contributing to a tumorigenic effect ( 103 ).…”
Section: Microbial Community Dynamics and Th17 Cellsmentioning
confidence: 99%
“… 39 We demonstrate SpaceANOVA’s robustness and superior power as compared to the popular method named SpicyR, 27 in realistic simulation scenarios, one of which particularly focuses particularly on images with missing regions. We use SpaceANOVA to spatially differentiate between distinct types of colorectal adenoma 40 by analyzing an mIF data set collected using the Vectra Polaris platform (Akoya Biosciences) at the Medical University of South Carolina (MUSC). In addition to that, we analyze two publicly available data sets: an IMC data set on type 1 diabetes 18 and a colorectal cancer (CRC) data set collected using the CODEX platform (Akoya Biosciences).…”
Section: Introductionmentioning
confidence: 99%