Advances in development and application of human organoids

Innumerable studies associated with cellular differentiation, tissue response and disease modeling have been conducted in two-dimensional (2D) culture systems or animal models. This has been invaluable in deciphering the normal and disease states in cell biology; the key shortcomings of it being suitability for translational or clinical correlations. The past decade has seen several major advances in organoid culture technologies and this has enhanced our understanding of mimicking organ reconstruction. The term organoid has generally been used to describe cellular aggregates derived from primary tissues or stem cells that can self-organize into organotypic structures. Organoids mimic the cellular microenvironment of tissues better than 2D cell culture systems and represent the tissue physiology. Human organoids of brain, thyroid, gastrointestinal, lung, cardiac, liver, pancreatic and kidney have been established from various diseases, healthy tissues and from pluripotent stem cells (PSCs). Advances in patient-derived organoid culture further provides a unique perspective from which treatment modalities can be personalized. In this review article, we have discussed the current strategies for establishing various types of organoids of ectodermal, endodermal and mesodermal origin. We have also discussed their applications in modeling human health and diseases (such as cancer, genetic, neurodegenerative and infectious diseases), applications in regenerative medicine and evolutionary studies

Comorbidities and inflammation associated with ovarian cancer and its influence on SARS-CoV-2 infection

Abstract Coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide is a major public health concern. Cancer patients are considered a vulnerable population to SARS-CoV-2 infection and may develop several COVID-19 symptoms. The heightened immunocompromised state, prolonged chronic pro-inflammatory milieu coupled with comorbid conditions are shared in both disease conditions and may influence patient outcome. Although ovarian cancer (OC) and COVID-19 are diseases of entirely different primary organs, both diseases share similar molecular and cellular characteristics in their microenvironment suggesting a potential cooperativity leading to poor outcome. In COVID-19 related cases, hospitalizations and deaths worldwide are lower in women than in males; however, comorbidities associated with OC may increase the COVID-19 risk in women. The women at the age of 50-60 years are at greater risk of developing OC as well as SARS-CoV-2 infection. Increased levels of gonadotropin and androgen, dysregulated renin-angiotensin-aldosterone system (RAAS), hyper-coagulation and chronic inflammation are common conditions observed among OC and severe cases of COVID-19. The upregulation of common inflammatory cytokines and chemokines such as tumor necrosis factor α (TNF-α), interleukin (IL)-1β, IL-2, IL-6, IL-10, interferon-γ-inducible protein 10 (IP-10), granulocyte colony-stimulating factor (G-CSF), monocyte chemoattractant protein-1 (MCP-1), macrophage colony-stimulating factor (M-CSF), among others in the sera of COVID-19 and OC subjects suggests potentially similar mechanism(s) involved in the hyper-inflammatory condition observed in both disease states. Thus, it is conceivable that the pathogenesis of OC may significantly contribute to the potential infection by SARS-CoV-2. Our understanding of the influence and mechanisms of SARS-CoV-2 infection on OC is at an early stage and in this article, we review the underlying pathogenesis presented by various comorbidities of OC and correlate their influence on SARS-CoV-2 infection

Schematic representation showing genome organization of <i>ABCB1</i> gene and the analyzed regions for SNPs and CpG sites (indicated in blue).

<p>Exons are indicated as boxes.</p

Genotype/allele frequency data of SNPs of <i>ABCB1</i> gene and the results of the test for genetic association with case (uncomplicated, complicated and all malaria) and control, with measures of statistical significance.

<p>Genotype/allele frequency data of SNPs of <i>ABCB1</i> gene and the results of the test for genetic association with case (uncomplicated, complicated and all malaria) and control, with measures of statistical significance.</p

Demographic data and the clinical profile of the malaria patients recruited as participants for the study.

<p>Demographic data and the clinical profile of the malaria patients recruited as participants for the study.</p

Correlation analysis of the three SNPs of <i>ABCB1</i> gene and DNA methylation levels in all malaria cases and controls.

<p>Correlation analysis of the three SNPs of <i>ABCB1</i> gene and DNA methylation levels in all malaria cases and controls.</p

Promoter activity analysis of ABCB1 constructs using luciferase assays.

<p>Showing pGL3- ABCB1 construct (contains 949bp DNA fragment) promoter activity results upon artemisinin and 3-methylcholanthrene treatments.</p

Global methylation estimation by RP-HPLC.

<p>A. Global methylation values (5mC) in malaria patients (with and without complications) and controls. Each dot represents the total methylation cytosine content of the individual sample. B. Global methylation values (5mC) in malaria patients (with different parasite levels). C. Global methylation values (5mC) in malaria patients (before and after treatment). Patient blood was collected twice at the time of admission (before medication) and after 7days of treatment. Within the groups mean ± standard error was shown in lines. The aster sign indicates the p value significance. **P<0.01, *P<0.05.</p

Dot plot of ABCB1 promoter DNA methylation at 30 CpG sites.

<p>Complicated malaria (Panel A), Uncomplicated malaria (Panel B), All malaria cases (Panel C) and Controls (Panel D).</p