Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd

Liebig's law of the minimum in the TGF-β/SMAD pathway

Cells use signaling pathways to sense and respond to their environments. The transforming growth factor-β (TGF-β) pathway produces context-specific responses. Here, we combined modeling and experimental analysis to study the dependence of the output of the TGF-β pathway on the abundance of signaling molecules in the pathway. We showed that the TGF-β pathway processes the variation of TGF-β receptor abundance using Liebig's law of the minimum, meaning that the output-modifying factor is the signaling protein that is most limited, to determine signaling responses across cell types and in single cells. We found that the abundance of either the type I (TGFBR1) or type II (TGFBR2) TGF-β receptor determined the responses of cancer cell lines, such that the receptor with relatively low abundance dictates the response. Furthermore, nuclear SMAD2 signaling correlated with the abundance of TGF-β receptor in single cells depending on the relative expression levels of TGFBR1 and TGFBR2. A similar control principle could govern the heterogeneity of signaling responses in other signaling pathways.

Machine learning and bioinformatic analyses link the cell surface receptor transcript levels to the drug response of breast cancer cells and drug off-target effects

Breast cancer responds variably to anticancer therapies, often leading to significant off-target effects. This study proposes that the variability in tumour responses and drug-induced adverse events is linked to the transcriptional profiles of cell surface receptors (CSRs) in breast tumours and normal tissues. We analysed multiple datasets to compare CSR expression in breast tumours with that in non-cancerous human tissues. Our findings correlate the drug responses of breast cancer cell lines with the expression levels of their targeted CSRs. Notably, we identified distinct differences in CSR expression between primary breast tumour subtypes and corresponding cell lines, which may influence drug response predictions. Additionally, we used clinical trial data to uncover associations between CSR gene expression in healthy tissues and the incidence of adverse drug reactions. This integrative approach facilitates the selection of optimal CSR targets for therapy, leveraging cell line dose-responses, CSR expression in normal tissues, and patient adverse event profiles.

Causal inference in drug discovery and development

To discover new drugs is to seek and to prove causality. As an emerging approach leveraging human knowledge and creativity, data, and machine intelligence, causal inference holds the promise of reducing cognitive bias and improving decision-making in drug discovery. Although it has been applied across the value chain, the concepts and practice of causal inference remain obscure to many practitioners. This article offers a nontechnical introduction to causal inference, reviews its recent applications, and discusses opportunities and challenges of adopting the causal language in drug discovery and development.

Oscillatory ERK Signaling and Morphology Determine Heterogeneity of Breast Cancer Cell Chemotaxis via MEK-ERK and p38-MAPK Signaling Pathways

Chemotaxis, regulated by oscillatory signals, drives critical processes in cancer metastasis. Crucial chemoattractant molecules in breast cancer, CXCL12 and EGF, drive the activation of ERK and Akt. Regulated by feedback and crosstalk mechanisms, oscillatory signals in ERK and Akt control resultant changes in cell morphology and chemotaxis. While commonly studied at the population scale, metastasis arises from small numbers of cells that successfully disseminate, underscoring the need to analyze processes that cancer cells use to connect oscillatory signaling to chemotaxis at single-cell resolution. Furthermore, little is known about how to successfully target fast-migrating cells to block metastasis. We investigated to what extent oscillatory networks in single cells associate with heterogeneous chemotactic responses and how targeted inhibitors block signaling processes in chemotaxis. We integrated live, single-cell imaging with time-dependent data processing to discover oscillatory signal processes defining heterogeneous chemotactic responses. We identified that short ERK and Akt waves, regulated by MEK-ERK and p38-MAPK signaling pathways, determine the heterogeneous random migration of cancer cells. By comparison, long ERK waves and the morphological changes regulated by MEK-ERK signaling, determine heterogeneous directed motion. This study indicates that treatments against chemotaxis in consider must interrupt oscillatory signaling.

Determination of WWOX Function in Modulating Cellular Pathways Activated by AP-2α and AP-2γ Transcription Factors in Bladder Cancer

Following the invention of high-throughput sequencing, cancer research focused on investigating disease-related alterations, often inadvertently omitting tumor heterogeneity. This research was intended to limit the impact of heterogeneity on conclusions related to WWOX/AP-2α/AP-2γ in bladder cancer which differently influenced carcinogenesis. The study examined the signaling pathways regulated by WWOX-dependent AP-2 targets in cell lines as biological replicates using high-throughput sequencing. RT-112, HT-1376 and CAL-29 cell lines were subjected to two stable lentiviral transductions. Following CAGE-seq and differential expression analysis, the most important genes were identified and functionally annotated. Western blot was performed to validate the selected observations. The role of genes in biological processes was assessed and networks were visualized. Ultimately, principal component analysis was performed. The studied genes were found to be implicated in MAPK, Wnt, Ras, PI3K-Akt or Rap1 signaling. Data from pathways were collected, explaining the differences/similarities between phenotypes. FGFR3, STAT6, EFNA1, GSK3B, PIK3CB and SOS1 were successfully validated at the protein level. Afterwards, a definitive network was built using 173 genes. Principal component analysis revealed that the various expression of these genes explains the phenotypes. In conclusion, the current study certified that the signaling pathways regulated by WWOX and AP-2α have more in common than that regulated by AP-2γ. This is because WWOX acts as an EMT inhibitor, AP-2γ as an EMT enhancer while AP-2α as a MET inducer. Therefore, the relevance of AP-2γ in targeted therapy is now more evident. Some of the differently regulated genes can find application in bladder cancer treatment.