| 1. |
- Jansen, Iris E, et al.
(författare)
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Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers.
- 2022
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Ingår i: Acta neuropathologica. - : Springer Science and Business Media LLC. - 1432-0533 .- 0001-6322. ; 144:5, s. 821-842
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Tidskriftsartikel (refereegranskat)abstract
- Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n=8074; replication n=5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume.
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| 2. |
- van Akkooi, Alexander C. J., et al.
(författare)
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Neoadjuvant Systemic Therapy (NAST) in Patients with Melanoma: Surgical Considerations by the International Neoadjuvant Melanoma Consortium (INMC)
- 2022
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Ingår i: ANNALS OF SURGICAL ONCOLOGY. - : Springer Science and Business Media LLC. - 1068-9265 .- 1534-4681. ; 29:6, s. 3694-3708
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Tidskriftsartikel (refereegranskat)abstract
- Exciting advances in melanoma systemic therapies have presented the opportunity for surgical oncologists and their multidisciplinary colleagues to test the neoadjuvant systemic treatment approach in high-risk, resectable metastatic melanomas. Here we describe the state of the science of neoadjuvant systemic therapy (NAST) for melanoma, focusing on the surgical aspects and the key role of the surgical oncologist in this treatment paradigm. This paper summarizes the past decade of developments in melanoma treatment and the current evidence for NAST in stage III melanoma specifically. Issues of surgical relevance are discussed, including the risk of progression on NAST prior to surgery. Technical aspects, such as the definition of resectability for melanoma and the extent and scope of routine surgery are presented. Other important issues, such as the utility of radiographic response evaluation and method of pathologic response evaluation, are addressed. Surgical complications and perioperative management of NAST related adverse events are considered. The International Neoadjuvant Melanoma Consortium has the goal of harmonizing NAST trials in melanoma to facilitate rapid advances with new approaches, and facilitating the comparison of results across trials evaluating different treatment regimens. Our ultimate goals are to provide definitive proof of the safety and efficacy of NAST in melanoma, sufficient for NAST to become an acceptable standard of care, and to leverage this platform to allow more personalized, biomarker-driven, tailored approaches to subsequent treatment and surveillance.
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| 3. |
- Wan, Guihong, et al.
(författare)
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Prediction of early-stage melanoma recurrence using clinical and histopathologic features
- 2022
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Ingår i: NPJ precision oncology. - : Springer Science and Business Media LLC. - 2397-768X. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Prognostic analysis for early-stage (stage I/II) melanomas is of paramount importance for customized surveillance and treatment plans. Since immune checkpoint inhibitors have recently been approved for stage IIB and IIC melanomas, prognostic tools to identify patients at high risk of recurrence have become even more critical. This study aims to assess the effectiveness of machine-learning algorithms in predicting melanoma recurrence using clinical and histopathologic features from Electronic Health Records (EHRs). We collected 1720 early-stage melanomas: 1172 from the Mass General Brigham healthcare system (MGB) and 548 from the Dana-Farber Cancer Institute (DFCI). We extracted 36 clinicopathologic features and used them to predict the recurrence risk with supervised machine-learning algorithms. Models were evaluated internally and externally: (1) five-fold cross-validation of the MGB cohort; (2) the MGB cohort for training and the DFCI cohort for testing independently. In the internal and external validations, respectively, we achieved a recurrence classification performance of AUC: 0.845 and 0.812, and a time-to-event prediction performance of time-dependent AUC: 0.853 and 0.820. Breslow tumor thickness and mitotic rate were identified as the most predictive features. Our results suggest that machine-learning algorithms can extract predictive signals from clinicopathologic features for early-stage melanoma recurrence prediction, which will enable the identification of patients that may benefit from adjuvant immunotherapy.
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