Pancreatic neuroendocrine tumors: the basics, the gray zone, and the target

Kelgiorgi, Dionysia; Dervenis, Christos

doi:10.12688/f1000research.10188.1

Cited by 9 publications

(9 citation statements)

References 61 publications

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“…Pancreatic Neuroendocrine Tumors (PanNETs), also known as islet cell tumors, comprise 1–2% of all pancreatic tumors and are thought to derive from cells of pluripotent pancreatic cells of the ductal/acinar system [ 140 ]. PanNETs can be divided into two groups according to secretory status: functional and non-functional.…”

Section: Alt Positive Neuroendocrine Tumorsmentioning

confidence: 99%

“…Most PanNETs have slow, indolent growth and are asymptomatic. Therefore, a majority of patients with PanNET are at an advanced stage at diagnosis [ 140 ]. PanNETs are rare tumors with multifaceted presentations that continue to confound the medical community; thus, a consensus on the standard of care has yet to be met.…”

Section: Alt Positive Neuroendocrine Tumorsmentioning

confidence: 99%

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ALT Positivity in Human Cancers: Prevalence and Clinical Insights

MacKenzie

Watters

et al. 2021

Cancers

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Since it was first described over two decades ago, the Alternative Lengthening of Telomeres (ALT) pathway has been well accepted to hold clinical significance in cancer development, cancer diagnosis and cancer treatment. In this review, we first discuss how the activation of this pathway is determined. We then provide up-to-date statistics on the cancers ALT activity is detected. Additionally, we discussed the relationship between ALT positivity and prognosis as well as the pathogenetics of the ALT positive cancers. Finally, we evaluated the pre-clinical and clinical investigation of potential therapy for ALT cancers.Abstract: Many exciting advances in cancer-related telomere biology have been made in the past decade. Of these recent advances, great progress has also been made with respect to the Alternative Lengthening of Telomeres (ALT) pathway. Along with a better understanding of the molecular mechanism of this unique telomere maintenance pathway, many studies have also evaluated ALT activity in various cancer subtypes. We first briefly review and assess a variety of commonly used ALT biomarkers. Then, we provide both an update on ALT-positive (ALT+) tumor prevalence as well as a systematic clinical assessment of the presently studied ALT+ malignancies. Additionally, we discuss the pathogenetic alterations in ALT+ cancers, for example, the mutation status of ATRX and DAXX, and their correlations with the activation of the ALT pathway. Finally, we highlight important ALT+ clinical associations within each cancer subtype and subdivisions within, as well as their prognoses. We hope this alternative perspective will allow scientists, clinicians, and drug developers to have greater insight into the ALT cancers so that together, we may develop more efficacious treatments and improved management strategies to meet the urgent needs of cancer patients.

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Section: Alt Positive Neuroendocrine Tumorsmentioning

confidence: 99%

Section: Alt Positive Neuroendocrine Tumorsmentioning

confidence: 99%

ALT Positivity in Human Cancers: Prevalence and Clinical Insights

MacKenzie

Watters

et al. 2021

Cancers

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“…Only a small percentage (1-2%) of all pancreatic cancers correspond to slower-growing pancreatic neuroendocrine tumors (PanNETs), previously known as islet cell tumors, which have a slow, indolent growth and are asymptomatic (7). Because PanNETs affect the secretion of hormones, they are named after the hormone they secrete (gastrinoma, insulinoma, somatostatinoma, VIPoma, and glucagonoma, affecting cells making gastrin, insulin, somatostain, VIP and glucagon, respectively).…”

Section: Pancreatic Cancermentioning

confidence: 99%

Novel therapeutic approaches for pancreatic cancer by combined targeting of RAF→MEK→ERK signaling and autophagy survival response

Mollinedo

Gajate

2019

Ann. Transl. Med

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“…Though preliminary, these results demonstrate the ability of our multi-structured deep learning-based model to provide metastasis risk stratification, and potentially facilitate clinical decision making. Additionally, the pipeline described here can help identify patients who might benefit from adjuvant therapy ( 46 ) or candidates for clinical trials, as well as enable personalized treatment ( 47 ).…”

Section: Discussionmentioning

confidence: 99%

Predicting Metastasis Risk in Pancreatic Neuroendocrine Tumors Using Deep Learning Image Analysis

et al. 2021

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BackgroundThe prognosis of patients with pancreatic neuroendocrine tumors (PanNET), the second most common type of pancreatic cancer, varies significantly, and up to 15% of patients develop metastasis. Although certain morphological characteristics of PanNETs have been associated with patient outcome, there are no available morphology-based prognostic markers. Given that current clinical histopathology markers are unable to identify high-risk PanNET patients, the development of accurate prognostic biomarkers is needed. Here, we describe a novel machine learning, multiclassification pipeline to predict the risk of metastasis using morphological information from whole tissue slides.MethodsDigital images from surgically resected tissues from 89 PanNET patients were used. Pathologist-annotated regions were extracted to train a convolutional neural network (CNN) to identify tiles consisting of PanNET, stroma, normal pancreas parenchyma, and fat. Computationally annotated cancer or stroma tiles and patient metastasis status were used to train CNN to calculate a region based metastatic risk score. Aggregation of the metastatic probability scores across the slide was performed to predict the risk of metastasis.ResultsThe ability of CNN to discriminate different tissues was high (per-tile accuracy >95%; whole slide cancer regions Jaccard index = 79%). Cancer and stromal tiles with high evaluated probability provided F1 scores of 0.82 and 0.69, respectively, when we compared tissues from patients who developed metastasis and those who did not. The final model identified low-risk (n = 76) and high-risk (n = 13) patients, as well as predicted metastasis-free survival (hazard ratio: 4.71) after adjusting for common clinicopathological variables, especially in grade I/II patients.ConclusionUsing slides from surgically resected PanNETs, our novel, multiclassification, deep learning pipeline was able to predict the risk of metastasis in PanNET patients. Our results suggest the presence of prognostic morphological patterns in PanNET tissues, and that these patterns may help guide clinical decision making.

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Pancreatic neuroendocrine tumors: the basics, the gray zone, and the target

Cited by 9 publications

References 61 publications

ALT Positivity in Human Cancers: Prevalence and Clinical Insights

ALT Positivity in Human Cancers: Prevalence and Clinical Insights

Novel therapeutic approaches for pancreatic cancer by combined targeting of RAF→MEK→ERK signaling and autophagy survival response

Predicting Metastasis Risk in Pancreatic Neuroendocrine Tumors Using Deep Learning Image Analysis

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