A retrospective longitudinal study and comprehensive review of adult patients with glycogen storage disease type III

Introduction

A deficiency of glycogen debrancher enzyme in patients with glycogen storage disease type III (GSD III) manifests with hepatic, cardiac, and muscle involvement in the most common subtype (type a), or with only hepatic involvement in patients with GSD IIIb.

Objective and methods

To describe longitudinal biochemical, radiological, muscle strength and ambulation, liver histopathological findings, and clinical outcomes in adults (≥18 years) with glycogen storage disease type III, by a retrospective review of medical records.

Results

Twenty-one adults with GSD IIIa (14 F & 7 M) and four with GSD IIIb (1 F & 3 M) were included in this natural history study. At the most recent visit, the median (range) age and follow-up time were 36 (19–68) and 16 years (0–41), respectively. For the entire cohort: 40% had documented hypoglycemic episodes in adulthood; hepatomegaly and cirrhosis were the most common radiological findings; and 28% developed decompensated liver disease and portal hypertension, the latter being more prevalent in older patients. In the GSD IIIa group, muscle weakness was a major feature, noted in 89% of the GSD IIIa cohort, a third of whom depended on a wheelchair or an assistive walking device. Older individuals tended to show more severe muscle weakness and mobility limitations, compared with younger adults. Asymptomatic left ventricular hypertrophy (LVH) was the most common cardiac manifestation, present in 43%. Symptomatic cardiomyopathy and reduced ejection fraction was evident in 10%. Finally, a urinary biomarker of glycogen storage (Glc₄) was significantly associated with AST, ALT and CK.

Conclusion

GSD III is a multisystem disorder in which a multidisciplinary approach with regular clinical, biochemical, radiological and functional (physical therapy assessment) follow-up is required. Despite dietary modification, hepatic and myopathic disease progression is evident in adults, with muscle weakness as the major cause of morbidity. Consequently, definitive therapies that address the underlying cause of the disease to correct both liver and muscle are needed.

Machine learning and deep learning methods that use omics data for metastasis prediction

Knowing metastasis is the primary cause of cancer-related deaths, incentivized research directed towards unraveling the complex cellular processes that drive the metastasis. Advancement in technology and specifically the advent of high-throughput sequencing provides knowledge of such processes. This knowledge led to the development of therapeutic and clinical applications, and is now being used to predict the onset of metastasis to improve diagnostics and disease therapies. In this regard, predicting metastasis onset has also been explored using artificial intelligence approaches that are machine learning, and more recently, deep learning-based. This review summarizes the different machine learning and deep learning-based metastasis prediction methods developed to date. We also detail the different types of molecular data used to build the models and the critical signatures derived from the different methods. We further highlight the challenges associated with using machine learning and deep learning methods, and provide suggestions to improve the predictive performance of such methods.

Differentiating benign from malignant pancreatic cysts on computed tomography

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CT can distinguish between benign and premalignant or malignant pancreatic cysts.

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Solid component and septation were the only CT features that could differentiate benign from malignant cysts.

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Cyst wall enhancements on CT were more commonly observed in premalignant or malignant cysts than in benign cysts.

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CT is a necessary diagnostic modality to preoperatively detect and characterize pancreatic lesions.

Purpose

It is important to identify features on computed tomography (CT) that can distinguish between benign and premalignant or malignant pancreatic cysts to avoid unnecessary surgeries. This study investigated the preoperative diagnostic evaluation of cystic pancreatic lesions to determine how advanced imaging and clinical factors should guide management.

Methods

In total, 53 patients with 27 benign and 26 premalignant or malignant cysts were enrolled. CT features of the cysts were compared using univariate and multivariate analyses.

Results

On univariate analysis, a solid component (p < 0.01), septation (p < 0.01), location (p < 0.01), border (p < 0.01), wall enhancement (p = 0.01), lesion margins (p < 0.01), pancreatic atrophy (p = 0.04), and a cystic wall (p < 0.01) were all significantly different between benign and premalignant or malignant cysts. On multivariate analysis, only a solid component (p < 0.01) and septation (p < 0.01) were significant.

Conclusion

A thin cystic wall, uniform homogeneity, a clear border, the presence of septation, pancreatic atrophy, and the absence of both wall enhancements and solid components were more frequently seen in benign cysts. A thick wall, lack of homogeneity, the presence of wall enhancements and solid components, absence of septation, only a small degree of pancreatic atrophy, and unclear borders were more frequent among premalignant or malignant cysts. The only CT features to differentiate benign from premalignant or malignant cysts were a solid component and septation.

Bilateral Adnexal Masses in a Young Female: Rare Presentation of Hepatocellular Carcinoma With Review of the Literature

Ovaries are a common niche for metastasis. Metastatic malignancies account for 5-30% of all ovarian malignancies. Hepatocellular carcinoma (HCC) is one of the rare malignancies to metastasize to the ovaries. Of all the variants of HCC, fibrolamellar HCC (FLHCC) variant is extremely uncommon and accounts for around 1% of all HCC cases. FLHCC metastasizing to ovaries, at presentation, is an exceptional occurrence. We present a case of a young female who presented with bilateral adnexal masses and was diagnosed as metastatic FLHCC on histopathological examination and confirmed by immunohistochemistry. In addition, a thorough literature review highlighting the previously reported cases is also presented.

Mucosa-associated lymphoid tissue lymphoma with metachronous involvement of the palpebral conjunctiva and bronchus: A case report

A 61-year-old woman with a history of palpebral conjunctival mucosa-associated lymphoid tissue (MALT) lymphoma, treated with rituximab, was referred to the authors' hospital after follow-up positron emission tomography/computed tomography revealed ¹⁸F-fluoro-2-deoxy-d-glucose uptake in a tumor located in the left main bronchus. The diagnosis of MALT lymphoma was made by pathological and immunohistochemical findings homologous to previous palpebral conjunctival lesion via bronchoscopic biopsy. The disease was controlled with rituximab, cyclophosphamide, oncovin, and prednisolone (i.e., R-COP) chemotherapy. Although MALT lymphoma occurs in several organs, metachronous occurrence in the palpebral conjunctiva and bronchus is especially rare, and careful check-up is required to monitor for occurrence of systemic relapse.

TroVax in colorectal cancer

Currently, the backbone of therapy for metastatic disease is cytotoxic chemotherapy, along with the recent addition of targeted therapy based on molecular markers with KRAS testing. Despite the improvement in survival for metastatic colon cancer, newer agents are still needed. The clinical activity of TroVax in metastatic colon cancer has been studied in a small number of clinical trials. There is evidence that supports the vaccine's ability to induce humoral and cellular responses, as demonstrated by positive 5T4 and MVA-specific antibody titers and cellular proliferation assays. Future strategies should focus on investigating the immunomodulatory effects of chemotherapy in conjunction with TroVax, understanding the optimal dosing and schedule of the combination, and examining potential predictive biomarkers to determine which patients may benefit from immunotherapy from those who do not.