Combining High-Content Imaging and Phenotypic Classification Analysis of Senescence-Associated Beta-Galactosidase Staining to Identify Regulators of Oncogene-Induced Senescence

Application and progress of highcontent imaging in molecular biology

Humans have adopted many different methods to explore matter imaging, among which high content imaging (HCI) could conduct automated imaging analysis of cells while maintaining its structural and functional integrity. Meanwhile, as one of the most important research tools for diagnosing human diseases, HCI is widely used in the frontier of medical research, and its future application has attracted researchers' great interests. Here, the meaning of HCI was briefly explained, the history of optical imaging and the birth of HCI were described, and the experimental methods of HCI were described. Furthermore, the directions of the application of HCI were highlighted in five aspects: protein localization changes, gene identification, chemical and genetic analysis, microbiology, and drug discovery. Most importantly, some challenges and future directions of HCI were discussed, and the application and optimization of HCI were expected to be further explored.

The Role of Big Data in Aging and Older People’s Health Research: A Systematic Review and Ecological Framework

Big data has been prominent in studying aging and older people’s health. It has promoted modeling and analyses in biological and geriatric research (like cellular senescence), developed health management platforms, and supported decision-making in public healthcare and social security. However, current studies are still limited within a single subject, rather than flourished as interdisciplinary research in the context of big data. The research perspectives have not changed, nor has big data brought itself out of the role as a modeling tool. When embedding big data as a data product, analysis tool, and resolution service into different spatial, temporal, and organizational scales of aging processes, it would present as a connection, integration, and interaction simultaneously in conducting interdisciplinary research. Therefore, this paper attempts to propose an ecological framework for big data based on aging and older people’s health research. Following the scoping process of PRISMA, 35 studies were reviewed to validate our ecological framework. Although restricted by issues like digital divides and privacy security, we encourage researchers to capture various elements and their interactions in the human-environment system from a macro and dynamic perspective rather than simply pursuing accuracy.

HighVia-A Flexible Live-Cell High-Content Screening Pipeline to Assess Cellular Toxicity

High-content screening to monitor disease-modifying phenotypes upon small-molecule addition has become an essential component of many drug and target discovery platforms. One of the most common phenotypic approaches, especially in the field of oncology research, is the assessment of cell viability. However, frequently used viability readouts employing metabolic proxy assays based on homogeneous colorimetric/fluorescent reagents are one-dimensional, provide limited information, and can in many cases yield conflicting or difficult-to-interpret results, leading to misinterpretation of data and wasted resources.The resurgence of high-content, phenotypic screening has significantly improved the quality and breadth of cell viability data, which can be obtained at the very earliest stages of drug and target discovery. Here, we describe a relatively inexpensive, high-throughput, high-content, multiparametric, fluorescent imaging protocol using a live-cell method of three fluorescent probes (Hoechst, Yo-Pro-3, and annexin V), that is amenable to the addition of further fluorophores. The protocol enables the accurate description and profiling of multiple cell death mechanisms, including apoptosis and necrosis, as well as accurate determination of compound IC50, and has been validated on a range of high-content imagers and image analysis software. To validate the protocol, we have used a small library of approximately 200 narrow-spectrum kinase inhibitors and clinically approved drugs. This fully developed, easy-to-use pipeline has subsequently been implemented in several academic screening facilities, yielding fast, flexible, and rich cell viability data for a range of early-stage high-throughput drug and target discovery programs.

Oncogene-induced senescence: From biology to therapy

Oncogene-induced senescence (OIS) is a powerful intrinsic tumor-suppressive mechanism, arresting cell cycle progression upon oncogene-activating genomic alterations. The discovery and characterization of the senescence-associated secretome unveiled a rich additional complexity to the senescence phenotype, including extrinsic impacts on the microenvironment and engagement of the immune response. Emerging evidence suggests that senescence phenotypes vary depending on the oncogenic stimulus. Therefore, understanding the mechanisms underlying OIS and how they are subverted in cancer will provide invaluable opportunities to identify alternative strategies for treating oncogene-driven cancers. In this review, we primarily discuss the key mechanisms governing OIS driven by the RAS/MAPK and PI3K/AKT pathways and how understanding the biology of senescent cells has uncovered new therapeutic possibilities to target cancer.

A functional genetic screen defines the AKT-induced senescence signaling network

Exquisite regulation of PI3K/AKT/mTORC1 signaling is essential for homeostatic control of cell growth, proliferation, and survival. Aberrant activation of this signaling network is an early driver of many sporadic human cancers. Paradoxically, sustained hyperactivation of the PI3K/AKT/mTORC1 pathway in nontransformed cells results in cellular senescence, which is a tumor-suppressive mechanism that must be overcome to promote malignant transformation. While oncogene-induced senescence (OIS) driven by excessive RAS/ERK signaling has been well studied, little is known about the mechanisms underpinning the AKT-induced senescence (AIS) response. Here, we utilize a combination of transcriptome and metabolic profiling to identify key signatures required to maintain AIS. We also employ a whole protein-coding genome RNAi screen for AIS escape, validating a subset of novel mediators and demonstrating their preferential specificity for AIS as compared with OIS. As proof of concept of the potential to exploit the AIS network, we show that neurofibromin 1 (NF1) is upregulated during AIS and its ability to suppress RAS/ERK signaling facilitates AIS maintenance. Furthermore, depletion of NF1 enhances transformation of p53-mutant epithelial cells expressing activated AKT, while its overexpression blocks transformation by inducing a senescent-like phenotype. Together, our findings reveal novel mechanistic insights into the control of AIS and identify putative senescence regulators that can potentially be targeted, with implications for new therapeutic options to treat PI3K/AKT/mTORC1-driven cancers.

Functional screening to identify senescence regulators in cancer

Cellular senescence is implicated in numerous biological processes, and can play pleiotropic, sometimes opposing, roles in cancer. Several triggers, cell types, contexts, and senescence-associated phenotypes introduce a multitude of possibilities when studying this process and its biological consequences. Recent studies continue to characterize cellular senescence at different levels, using a combination of functional screens, in silico analysis, omics characterizations and more targeted studies. However, a comprehensive analysis of its context-dependent effects and multiple phenotypes is required. Application of state-of-the-art and emerging technologies will increase our understanding of this complex process and better guide future strategies to harness senescence to our advantage, or to target it when detrimental.