An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model.

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources.

Early Detection of Cancers in the Era of Precision Oncology.

PURPOSE OF REVIEW: The increasing global incidence of cancer demands innovative cancer detection modalities. The current population-based early cancer detection approaches focus on several major types of cancers (breast, prostate, cervical, lung and colon) at their early stages, however, they generally do not target high-risk individuals at precancerous stages. RECENT FINDINGS: Some cancers, such as pancreatic cancer, are challenging to detect in their early stages. Therefore, there is a pressing need for improved, accessible, noninvasive, and cost-effective early detection methods. Harnessing cell-free-based biomarker-driven strategies paves a new era of precision diagnosis for multicancer early detection. The majority of these tests are in the early stages and expensive, but these approaches are expected to become cost sensitive in the near future. SUMMARY: This review provides an overview of early cancer detection strategies, highlighting the methods, challenges, and issues to be addressed to revolutionize and improve global early cancer detection.

Perspectives toward biosimilars among oncologists: A Malaysian survey.

INTRODUCTION: Biosimilars confer significant cost-saving advantages and expand patients' access to biologic therapies in cancer care. In line with the increasing availability of antineoplastic biosimilars, it is pertinent to understand the oncologists' view on the adoption of biosimilars in their clinical practice. The study aimed to assess (i) the prevalence of biosimilar use, (ii) perception towards biosimilars, (iii) factors influencing the use of biosimilars and (iv) knowledge about biosimilars among Malaysian oncologists. METHODS: A cross-sectional survey was conducted among clinical oncologists and medical oncologists in Malaysia between January 2020 and February 2021 using a structured 31-item questionnaire. RESULTS: Among the 121 oncologists registered in the country, 36 responded (response rate = 30%). A total of 64% of the respondents prescribed biosimilars either often or always. Most oncologists (72%) agreed or strongly agreed that switching will not have a significant effect on the treatment benefit, with lower percentages saying that they agreed or strongly agreed that it will not lead to the emergence of additional adverse effects (56%) or harmful immunogenicity (64%). Patients' preferences (40%) and the non-availability of biosimilars in hospitals (34%) are the major barriers cited to the prescribing of biosimilars. Cost differences and robust pharmacovigilance activities are the two most important factors that would influence the prescribing of biosimilars. The mean score of knowledge in biosimilar among respondents was 3.81 (± 0.86) out of a maximum possible score of 6. CONCLUSIONS: The identified gap in prescribing and the use of biosimilars among Malaysian oncologists warrant educational intervention and robust pharmacovigilance activities to facilitate the prescribing of biosimilars and ultimately increase the accessibility to biologics in cancer treatment.

Coronavirus Does It Again: Post-COVID-19 Hemophagocytic Lymphohistiocytosis (HLH).

Hemophagocytic lymphohistiocytosis (HLH) is a hematological disorder that results from an uncontrolled activation of the immune system, which can then lead to multisystem organ failure. Given the nonspecific nature of this illness, it can go undetected for too long, thereby causing permanent damage to organ systems. In adults, HLH has been associated with a number of infectious etiologies, particularly viral infections. Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global pandemic and has been associated with acute respiratory distress syndrome (ARDS). Among its other manifestations, COVID-19 has also been linked to HLH. In this report, we describe a case of a male patient who presented with multisystem organ failure and was found to have HLH. Since no clear etiology for his HLH could be elicited, it was determined to be a result of his recent COVID-19 infection.

The Promise of Epigenetics Research in the Treatment of Appendiceal Neoplasms.

Appendiceal cancers (AC) are a rare and heterogeneous group of malignancies. Historically, appendiceal neoplasms have been grouped with colorectal cancers (CRC), and treatment strategies have been modeled after CRC management guidelines due to their structural similarities and anatomical proximity. However, the two have marked differences in biological behavior and treatment response, and evidence suggests significant discrepancies in their respective genetic profiles. In addition, while the WHO classification for appendiceal cancers is currently based on traditional histopathological criteria, studies have demonstrated that histomorphology does not correlate with survival or treatment response in AC. Due to their rarity, appendiceal cancers have not been studied as extensively as other gastrointestinal cancers. However, their incidence has been increasing steadily over the past decade, making it crucial to identify new and more effective strategies for detection and treatment. Recent efforts to map and understand the molecular landscape of appendiceal cancers have unearthed a wealth of information that has made it evident that appendiceal cancers possess a unique molecular profile, distinct from other gastrointestinal cancers. This review focuses on the epigenetic landscape of epithelial appendiceal cancers and aims to provide a comprehensive overview of the current state of knowledge of epigenetic changes across different appendiceal cancer subtypes, highlighting the challenges as well as the promise of employing epigenetics in the quest for the detection of biomarkers, therapeutic targets, surveillance markers, and predictors of treatment response and survival in epithelial appendiceal neoplasms.

Utility of promoter hypermethylation in malignant risk stratification of intraductal papillary mucinous neoplasms.

BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs), a type of cystic pancreatic cancer (PC) precursors, are increasingly identified on cross-sectional imaging and present a significant diagnostic challenge. While surgical resection of IPMN-related advanced neoplasia, i.e., IPMN-related high-grade dysplasia or PC, is an essential early PC detection strategy, resection is not recommended for IPMN-low-grade dysplasia (LGD) due to minimal risk of carcinogenesis, and significant procedural risks. Based on their promising results in prior validation studies targeting early detection of classical PC, DNA hypermethylation-based markers may serve as a biomarker for malignant risk stratification of IPMNs. This study investigates our DNA methylation-based PC biomarker panel (ADAMTS1, BNC1, and CACNA1G genes) in differentiating IPMN-advanced neoplasia from IPMN-LGDs. METHODS: Our previously described genome-wide pharmaco-epigenetic method identified multiple genes as potential targets for PC detection. The combination was further optimized and validated for early detection of classical PC in previous case-control studies. These promising genes were evaluated among micro-dissected IPMN tissue (IPMN-LGD: 35, IPMN-advanced neoplasia: 35) through Methylation-Specific PCR. The discriminant capacity of individual and combination of genes were delineated through Receiver Operating Characteristics curve analysis. RESULTS: As compared to IPMN-LGDs, IPMN-advanced neoplasia had higher hypermethylation frequency of candidate genes: ADAMTS1 (60% vs. 14%), BNC1 (66% vs. 3%), and CACGNA1G (25% vs. 0%). We observed Area Under Curve (AUC) values of 0.73 for ADAMTS1, 0.81 for BNC1, and 0.63 for CACNA1G genes. The combination of the BNC1/ CACNA1G genes resulted in an AUC of 0.84, sensitivity of 71%, and specificity of 97%. Combining the methylation status of the BNC1/CACNA1G genes, blood-based CA19-9, and IPMN lesion size enhanced the AUC to 0.92. CONCLUSION: DNA-methylation based biomarkers have shown a high diagnostic specificity and moderate sensitivity for differentiating IPMN-advanced neoplasia from LGDs. Addition of specific methylation targets can improve the accuracy of the methylation biomarker panel and enable the development of noninvasive IPMN stratification biomarkers.

Liver metabolomics identifies bile acid profile changes at early stages of alcoholic liver disease in mice.

Alcohol consumption is a global healthcare problem with enormous social, economic, and clinical consequences. The liver sustains the earliest and the greatest degree of tissue injury due to chronic alcohol consumption and it has been estimated that alcoholic liver disease (ALD) accounts for almost 50% of all deaths from cirrhosis in the world. In this study, we used a modified Lieber-DeCarli (LD) diet to treat mice with alcohol and simulate chronic alcohol drinking. Using an untargeted metabolomics approach, our aim was to identify the various metabolites and pathways that are altered in the early stages of ALD. Histopathology showed minimal changes in the liver after 6 weeks of alcohol consumption. However, untargeted metabolomics analyses identified 304 metabolic features that were either up- or down-regulated in the livers of ethanol-consuming mice. Pathway analysis revealed significant alcohol-induced alterations, the most significant of which was in the FXR/RXR activation pathway. Targeted metabolomics focusing on bile acid biosynthesis showed elevated taurine-conjugated cholic acid compounds in ethanol-consuming mice. In summary, we showed that the changes in the liver metabolome manifest very early in the development of ALD, and when minimal changes in liver histopathology have occurred. Although alterations in biochemical pathways indicate a complex pathology in the very early stages of alcohol consumption, bile acid changes may serve as biomarkers of the early onset of ALD.

Interplay between APC and ALDH1B1 in a newly developed mouse model of colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide. Mutations in the adenomatous polyposis coli (APC) gene are pivotal in colorectal tumorigenesis. Recently, we demonstrated that aldehyde dehydrogenase 1B1 (ALDH1B1) knockdown dramatically reduced colon tumor growth in a mouse xenograft model. The purpose of the present preliminary study is to examine the effect of loss of ALDH1B1 in CRC development in an inducible colon-specific Apc mouse model. METHODS: ApcW/FCdx2ERT2-Cre mice develop uni-allelic inactivation of Apc specifically in colon epithelial cells following tamoxifen treatment. Aldh1b1-/- KO mice were crossed with ApcW/FCdx2ERT2-Cre mice. Six-month-old male ApcW/FCdx2ERT2-Cre/Aldh1b1-/-, and ApcW/FCdx2ERT2-Cre/Aldh1b1+/+ mice were treated with tamoxifen (50 mg/kg, i.p.) for three consecutive days. ApcW/F/Aldh1b1-/- and ApcW/F/Aldh1b1+/+ mice were treated with corn oil (i.e., tamoxifen vehicle control) for three consecutive days. Eighteen days later, mice were sacrificed and their colons examined microscopically, macroscopically and histologically for the presence of adenoma. RESULTS: All ApcW/FCdx2ERT2-Cre/Aldh1b1+/+ and ApcW/FCdx2ERT2-Cre/Aldh1b1-/- mice treated with tamoxifen developed colorectal adenoma. The ApcW/FCdx2ERT2-Cre/Aldh1b1-/- mice showed a significant decrease in the total volume of all ileal and colonic adenomas, and decreased incidence of large colonic adenoma compared to ApcW/FCdx2ERT2-Cre/Aldh1b1+/+ mice. Immunohistochemical analysis of p53 and ß-catenin showed a trend toward decreased expression score in colonic adenomas of ApcW/FCdx2ERT2-Cre/Aldh1b1-/- mice. CONCLUSION: The present preliminary study suggests that deletion of ALDH1B1 may protect against the full development of colorectal cancer. Further mechanistic studies are required to elucidate how ALDH1B1 contributes for colorectal cancer.