Functional transcriptional signatures for tumor-type-agnostic phenotype prediction

Metabolic Objectives and Trade-Offs: Inference and Applications

Background/Objectives: Determining appropriate cellular objectives is crucial for the system-scale modeling of biological networks for metabolic engineering, cellular reprogramming, and drug discovery applications. The mathematical representation of metabolic objectives can describe how cells manage limited resources to achieve biological goals within mechanistic and environmental constraints. While rapidly proliferating cells like tumors are often assumed to prioritize biomass production, mammalian cell types can exhibit objectives beyond growth, such as supporting tissue functions, developmental processes, and redox homeostasis. Methods: This review addresses the challenge of determining metabolic objectives and trade-offs from multiomics data. Results: Recent advances in single-cell omics, metabolic modeling, and machine/deep learning methods have enabled the inference of cellular objectives at both the transcriptomic and metabolic levels, bridging gene expression patterns with metabolic phenotypes. Conclusions: These in silico models provide insights into how cells adapt to changing environments, drug treatments, and genetic manipulations. We further explore the potential application of incorporating cellular objectives into personalized medicine, drug discovery, tissue engineering, and systems biology.

An update on existing therapeutic options and status of novel anti-metastatic agents in breast cancer: Elucidating the molecular mechanisms underlying the pleiotropic action of Withania somnifera (Indian ginseng) in breast cancer attenuation

Major significant advancements in pharmacology and drug technology have been made to heighten the impact of cancer therapies, improving the life expectancy of subjects diagnosed with malignancy. Statistically, 99% of breast cancers occur in women while 0.5-1% occur in men, the female gender being the strongest breast cancer risk factor. Despite several breakthroughs, breast cancer continues to have a worldwide impact and is one of the leading causes of mortality. Additionally, resistance to therapy is a crucial factor enabling cancer cell persistence and resurgence. As a result, the search and discovery of novel modulatory agents and effective therapies capable of controlling tumor progression and cancer cell proliferation is critical. Withania somnifera (L.) Dunal (WS), commonly known as Indian ginseng, has long been used traditionally for the treatment of several ailments in the Indian context. Recently, WS and its phytoconstituents have shown promising anti-breast cancer properties and, as such, can be employed as prophylactic as well as therapeutic adjuncts to the main line of breast cancer treatment. The present review is an attempt to explore and provide experimental evidences in support of the prophylactic and therapeutic potential of WS in breast cancer, along with a deeper insight into the multiple molecular mechanisms and novel targets through which it acts against breast and other hormonally-induced cancers viz. ovarian, uterine and cervical. This exploration might prove crucial in providing better understanding of breast cancer progression and metastasis and its use as an adjunct in improving disease prognosis and therapeutic outcome.

Transcriptional drift in aging cells: A global decontroller

As cells age, they undergo a remarkable global change: In transcriptional drift, hundreds of genes become overexpressed while hundreds of others become underexpressed. Using archetype modeling and Gene Ontology analysis on data from aging Caenorhabditis elegans worms, we find that the up-regulated genes code for sensory proteins upstream of stress responses and down-regulated genes are growth- and metabolism-related. We observe similar trends within human fibroblasts, suggesting that this process is conserved in higher organisms. We propose a simple mechanistic model for how such global coordination of multiprotein expression levels may be achieved by the binding of a single factor that concentrates with age in C. elegans. A key implication is that a cell's own responses are part of its aging process, so unlike wear-and-tear processes, intervention might be able to modulate these effects.

Transcriptional drift in aging cells: A global de-controller

As cells age, they undergo a remarkable global change: In transcriptional drift, hundreds of genes become overexpressed while hundreds of others become underexpressed. Using archetype modeling and Gene Ontology analysis on data from aging Caenorhabditis elegans worms, we find that the upregulated genes code for sensory proteins upstream of stress responses and downregulated genes are growth- and metabolism-related. We propose a simple mechanistic model for how such global coordination of multi-protein expression levels may be achieved by the binding of a single ligand that concentrates with age. A key implication is that a cell's own responses are part of its aging process, so unlike for wear-and-tear processes, intervention might be able to modulate these effects.

Mapping the Single-cell Differentiation Landscape of Osteosarcoma

The genetic and intratumoral heterogeneity observed in human osteosarcomas (OS) poses challenges for drug development and the study of cell fate, plasticity, and differentiation, processes linked to tumor grade, cell metastasis, and survival. To pinpoint errors in OS differentiation, we transcriptionally profiled 31,527 cells from a tissue-engineered model that directs MSCs toward adipogenic and osteoblastic fates. Incorporating pre-existing chondrocyte data, we applied trajectory analysis and non-negative matrix factorization (NMF) to generate the first human mesenchymal differentiation atlas. This 'roadmap' served as a reference to delineate the cellular composition of morphologically complex OS tumors and quantify each cell's lineage commitment. Projecting these signatures onto a bulk RNA-seq OS dataset unveiled a correlation between a stem-like transcriptomic phenotype and poorer survival outcomes. Our study takes the critical first step in accurately quantifying OS differentiation and lineage, a prerequisite to better understanding global differentiation bottlenecks that might someday be targeted therapeutically.