Circadian transcriptome of pancreatic adenocarcinoma unravels chronotherapeutic targets.

Pancreatic ductal adenocarcinoma (PDA) is a lethal cancer characterized by a poor outcome and an increasing incidence. A significant majority (>80%) of newly diagnosed cases are deemed unresectable, leaving chemotherapy as the sole viable option, though with only moderate success. This necessitates the identification of improved therapeutic options for PDA. We hypothesized that there are temporal variations in cancer-relevant processes within PDA tumors, offering insights into the optimal timing of drug administration - a concept termed chronotherapy. In this study, we explored the presence of the circadian transcriptome in PDA using patient-derived organoids and validated these findings by comparing PDA data from The Cancer Genome Atlas with noncancerous healthy pancreas data from GTEx. Several PDA-associated pathways (cell cycle, stress response, Rho GTPase signaling) and cancer driver hub genes (EGFR and JUN) exhibited a cancer-specific rhythmic pattern intricately linked to the circadian clock. Through the integration of multiple functional measurements for rhythmic cancer driver genes, we identified top chronotherapy targets and validated key findings in molecularly divergent pancreatic cancer cell lines. Testing the chemotherapeutic efficacy of clinically relevant drugs further revealed temporal variations that correlated with drug-target cycling. Collectively, our study unravels the PDA circadian transcriptome and highlights a potential approach for optimizing chrono-chemotherapeutic efficacy.

Patient-Derived Organoids as Therapy Screening Platforms in Cancer Patients.

Patient-derived organoids (PDOs) developed ex vivo and in vitro are increasingly used for therapeutic screening. They provide a more physiologically relevant model for drug discovery and development compared to traditional cell lines. However, several challenges remain to be addressed to fully realize the potential of PDOs in therapeutic screening. This paper summarizes recent advancements in PDO development and the enhancement of PDO culture models. This is achieved by leveraging materials engineering and microfabrication technologies, including organs-on-a-chip and droplet microfluidics. Additionally, this work discusses the application of PDOs in therapy screening to meet diverse requirements and overcome bottlenecks in cancer treatment. Furthermore, this work introduces tools for data processing and analysis of organoids, along with their microenvironment. These tools aim to achieve enhanced readouts. Finally, this work explores the challenges and future perspectives of using PDOs in drug development and personalized screening for cancer patients.

Early-onset Colon Cancer Shows a Distinct Intestinal Microbiome and a Host-Microbe Interaction.

The incidence rate of colorectal cancer in younger adults has been rising in developed countries. This trend may be attributed to environmental exposures as a result of lifestyle changes. Many of the lifestyle factors that promote colorectal cancer can also affect the gut microbiome, which may be associated with colorectal cancer risks. The role of the microbiome in the ongoing rise of early-onset colorectal cancer is unknown. Here, we aimed to investigate age-related differences in the gut microbiome of patients with colorectal cancer and healthy individuals by examining both the fecal and tumor microbiomes. We utilized the publicly accessible data on fecal shotgun metagenomics from CuratedMetagenomeData and TCGA via the GDC Data Portal. Comparison of 701 colorectal cancer and 693 controls revealed that microbial features were age dependent, with a significant difference in species enrichment between early-onset (<50 years) and late-onset (>65 years) patients with colorectal cancer. Analysis of the tumor-associated microbiome in a separate dataset of 85 patients with colorectal cancer verified age-specific differences in taxon abundance between early- and late-onset patients with colorectal cancer. Finally, using host gene expression data, we found a stronger microbe-host interaction in early- vs. late-onset colorectal cancers. Altogether, these findings indicate that microbial features were age-dependent with stronger microbial-host interactions at the tumor site in early-onset colorectal cancers, suggesting a direct role of microbes in tumorigenesis via interaction with cancer-related pathways in this age group. PREVENTION RELEVANCE: Early-onset colorectal cancer is on the rise, presumably because of changes in environmental exposures. Lifestyle changes may contribute to colorectal cancer via alterations in gut microbes. Here, we show that microbial association with colorectal cancer is age-dependent, and microbe interactions with tumor pathways are stronger in young versus older colorectal cancers.

Multi-omics approach to socioeconomic disparity in metabolic syndrome reveals roles of diet and microbiome.

The epidemy of metabolic syndrome (MetS) is typically preceded by adoption of a "risky" lifestyle (e.g., dietary habit) among populations. Evidence shows that those with low socioeconomic status (SES) are at an increased risk for MetS. To investigate this, we recruited 123 obese subjects (body mass index [BMI] ≥ 30) from Chicago. Multi-omic data were collected to interrogate fecal microbiota, systemic markers of inflammation and immune activation, plasma metabolites, and plasma glycans. Intestinal permeability was measured using the sugar permeability testing. Our results suggest a heterogenous metabolic dysregulation among obese populations who are at risk of MetS. Systemic inflammation, linked to poor diet, intestinal microbiome dysbiosis, and gut barrier dysfunction may explain the development of MetS in these individuals. Our analysis revealed 37 key features associated with increased numbers of MetS features. These features were used to construct a composite metabolic-inflammatory (MI) score that was able to predict progression of MetS among at-risk individuals. The MI score was correlated with several markers of poor diet quality as well as lower levels of gut microbial diversity and abnormalities in several species of bacteria. This study reveals novel targets to reduce the burden of MetS and suggests access to healthy food options as a practical intervention.

Inconsistent eating time is associated with obesity: A prospective study.

Obesity is characterized by an accumulation of redundant body fat linked to metabolic dysregulation and low-grade systemic inflammation. Lifestyle choices are imperative determining factors of obesity. The contemporary lifestyle is associated with behaviors that disrupt circadian rhythms, impacting metabolic homeostasis. Our animal and human studies suggest that circadian phenotypes could be related to the risk of metabolic dysregulation and obesity. The purpose of this study is to examine the role of inconsistent eating habits on body weight in adults. Individuals who presented for colon cancer screening were enrolled. Subjects received structured questionnaires to capture 7-day eating and sleeping times in a week prospectively. Bodyweight and height were extracted from medical records, and Body Mass Index (BMI) was calculated. Inconsistent eating times were defined as an average difference of >2 hours between the largest meal on weekdays and weekends. Forty-nine of the 61 (80.3 %) individuals enrolled in the study completed the questionnaires. The mean age and standard deviation (SD) were 60.8 (7.9), and 27 (55.1 %) were male. Subjects with inconsistent eating times had a significantly higher BMI (33.8 ± 3.6 SD, n = 9) than subjects who did not (27.5 ± 6.5 SD, n = 40; p = 0.001). The highest BMI was observed in subjects who ate inconsistently and late (35.8 ± 4.6 SD). In this cross-sectional study, time of eating habits was associated with BMI. Controlled cohort studies are needed to determine the potential link between eating time and the risk of obesity in the long term.

Behavioral circadian phenotypes are associated with the risk of elevated body mass index.

BACKGROUND: Metabolic dysfunction and obesity rates are on the rise. Although the central modes of circadian disruption has been studied in relation to the risk of obesity, the role of eating time has remained unclear. Here, we aimed to assess circadian behavioral phenotypes and their association with the risk of elevated body mass index (BMI). METHODS: This was a prospective cross-sectional study of individuals presenting for colorectal cancer screening colonoscopy. Participants completed demographic questionnaires, The Munich ChronoType Questionnaire (MCTQ), and Food Timing Screener (FTS). The primary outcome of the study was the association between circadian phenotypes and elevated BMI. RESULTS: A total of 488 individuals completed the survey, with a mean (SD) age of 57.5 (10.8) years. The mean body mass index (BMI) was 28.8 (6.1) kg/m2, with 72.3% of individuals met criteria for elevated BMI. Four circadian behavioral phenotypes were generated: early chronotype with regular food timing (ER) (34.7%), early chronotype with irregular food timing (EI) (11.7%), intermediate/late chronotype with regular food timing (LR) (33.9%), and intermediate/late chronotype with irregular food timing (LI) (19.7%). In a multivariable regression analysis, LI phenotype had 2.9 times higher odds of elevated BMI as compared to ER phenotype (OR 2.9, 95% CI 1.3-6.7, P = 0.01). CONCLUSION: The combination of late chronotype and irregular food timing, representative of a behavioral circadian rhythm disruption, is associated with higher rates of elevated BMI. The majority of individuals with this abnormal circadian phenotype were younger than 60 years old. This observation is especially relevant because of the ongoing rise in the obesity rates among young adults. LEVEL III: Evidence obtained from well-designed cohort or case-control analytic studies.

Gastrointestinal Symptoms Predict the Outcomes From COVID-19 Infection.

Coronavirus disease 2019 (COVID-19) has taken hundreds of thousands of lives globally. Besides the respiratory tract, the virus can affect the gastrointestinal (GI) tract. Data regarding the significance of GI symptoms in the COVID-19 course are limited. In this largest US study to date, the authors reviewed electronic encounters of 1003 consecutive patients who were tested positive for the virus between March 12 and April 3, 2020. Initial GI symptoms were present in up to 22.4% of patients and were associated with worse outcomes after adjustment for demographics, comorbidities, and other clinical symptoms. COVID-19 with GI involvement may define a more severe phenotype.

Abnormal food timing and predisposition to weight gain: Role of barrier dysfunction and microbiota.

Obesity has become a common rising health care problem, especially in "modern" societies. Obesity is considered a low-grade systemic inflammation, partly linked to leaky gut. Circadian rhythm disruption, a common habit in modern life, has been reported to cause gut barrier impairment. Abnormal time of eating, defined by eating close to or during rest time, is shown to cause circadian rhythm disruption. Here, using a non-obesogenic diet, we found that abnormal feeding time facilitated weight gain and induced metabolic dysregulation in mice. The effect of abnormal time of eating was associated with increased gut permeability, estimated by sucralose and/or lactulose ratio and disrupted intestinal barrier marker. Analysis of gut microbiota and their metabolites, as important regulators of barrier homeostasis, revealed that abnormal food timing reduced relative abundance of butyrate-producing bacteria, and the colonic butyrate level. Overall, our data supported that dysbiosis was characterized by increased intestinal permeability and decreased beneficial barrier butyrate-producing bacteria and/or metabolite to mechanistically link the time of eating to obesity. This data provides basis for noninvasive microbial-targeted interventions to improve intestinal barrier function as new opportunities for combating circadian rhythm disruption induced metabolic dysfunction.

Marked Elevation of Lipase in COVID-19 Disease: A Cohort Study.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing the pandemic of coronavirus disease 2019 (COVID-19) is a global health crisis. Possible pancreatic involvement has recently been observed in these patients; however, its significance is unclear. The aim of this study was to evaluate the association of significantly elevated lipase with disease outcomes. METHODS: Data about demographics, symptoms, laboratory values, and clinical outcomes were collected for 1,003 consecutive patients testing positive for COVID-19. Elevated lipase was defined as greater than 3 times the upper limit of normal (>3 × ULN). Baseline characteristics among patients with or without elevated lipase were compared using Fisher exact test or Student t-test for categorical or numerical variables, respectively. Logistic regression was used to evaluate the association of lipase levels with primary clinical outcomes (intensive care unit admission and intubation) adjusted for age, sex, body mass index, history of diabetes, and hypertension. RESULTS: Of 1,003 patients with COVID-19, 83 had available lipase levels and were all admitted to the hospital. Of 83, 14 (16.8%) had elevated lipase (>3 × ULN), which was associated with higher rates of leukocytosis (P < 0.001) and abnormal liver enzymes (P < 0.01). Compared with lower lipase levels (<3 × ULN), patients with elevated lipase had higher rates of ICU admission (92.9% vs 32.8%; P < 0.001) and intubation (78.6% vs 23.5%; P 0.002). In a multivariable-adjusted model, higher lipase levels were significantly associated with admission to the ICU and rate of intubation. DISCUSSION: Lipase elevation is seen in COVID-19 and is associated with worse disease outcomes.