Targeting phase separation on enhancers induced by transcription factor complex formations as a new strategy for treating drug-resistant cancers

MUC1-C dependency in drug resistant HR+/HER2- breast cancer identifies a new target for antibody-drug conjugate treatment

Treatment of hormone receptor (HR)-positive, HER2-negative breast cancer (HR+/HER2- BC) is limited by resistance to endocrine therapy (ET) and CDK4/6 inhibitors. There is no known common pathway that confers resistance to these agents. We report that (i) the MUC1 gene is upregulated in HR+/HER2- BCs and (ii) the MUC1-C protein regulates estrogen receptor alpha (ER)-driven transcriptomes. Mechanistically, we demonstrate that MUC1-C is necessary for expression of SRC-3 and MED1 coactivators that drive ER-mediated target gene transcription. Cells with ESR1 mutations that confer ET resistance, as well as cells with acquired resistance to the CDK4/6 inhibitor abemaciclib, are dependent on MUC1-C for (i) expression of these coactivators and ER target genes, (ii) survival, and (iii) self-renewal capacity. In support of these results, we show that treatment of HR+/HER2- BC cells with an anti-MUC1-C antibody-drug conjugate (ADC) effectively inhibits survival, self-renewal and tumorgenicity. These findings indicate that MUC1-C is a common effector of drug-resistant HR+/HER2- BC cells and is a potential target for their treatment.

Tailoring solid-state DNP methods to the study of α-synuclein LLPS

Dynamic Nuclear Polarization (DNP) is a technique that leverages the quantum sensing capability of electron spins to enhance the sensitivity of nuclear magnetic resonance (NMR) signals, especially for insensitive samples. Glassing agents play a crucial role in the DNP process by facilitating the transfer of polarization from the unpaired electron spins to the nuclear spins along with cryoprotection of biomolecules. DNPjuice comprising of glycerol-d8/D2O/H2O has been extensively used for this purpose over the past two decades. Polyethylene glycol (PEG), also used as a cryoprotectant, is often used as a crowding agent in experimental setups to mimic cellular conditions, particularly the invitro preparation of liquid-liquid phase separated (LLPS) condensates. In this study, we investigate the efficacy of PEG as an alternative to glycerol in the DNP juice, critical for signal enhancement. The modified DNP matrix leads to high DNP enhancement which enables direct study of LLPS condensates by solid-state DNP methods without adding any external constituents. An indirect advantage of employing PEG is that the PEG signals appear at ∼72.5 ppm and are relatively well-separated from the aliphatic region of the protein spectra. Large cross-effect DNP enhancement is attained for 13C-glycine by employing the PEG-water mixture as a glassing agent and ASYMPOL-POK as the state-of-art polarizing agent, without any deuteration. The DNP enhancement and the buildup rates are similar to results obtained with DNP juice, conforming to that PEG serves as a good candidate for both inducing crowding and glassing agent in the study of LLPS.

Subcellular Drug Distribution: Exploring Organelle-Specific Characteristics for Enhanced Therapeutic Efficacy

The efficacy and potential toxicity of drug treatments depends on the drug concentration at its site of action, intricately linked to its distribution within diverse organelles of mammalian cells. These organelles, including the nucleus, endosome, lysosome, mitochondria, endoplasmic reticulum, Golgi apparatus, lipid droplets, exosomes, and membrane-less structures, create distinct sub-compartments within the cell, each with unique biological features. Certain structures within these sub-compartments possess the ability to selectively accumulate or exclude drugs based on their physicochemical attributes, directly impacting drug efficacy. Under pathological conditions, such as cancer, many cells undergo dynamic alterations in subcellular organelles, leading to changes in the active concentration of drugs. A mechanistic and quantitative understanding of how organelle characteristics and abundance alter drug partition coefficients is crucial. This review explores biological factors and physicochemical properties influencing subcellular drug distribution, alongside strategies for modulation to enhance efficacy. Additionally, we discuss physiologically based computational models for subcellular drug distribution, providing a quantifiable means to simulate and predict drug distribution at the subcellular level, with the potential to optimize drug development strategies.

KAT6A Condensates Impair PARP1 Trapping of PARP Inhibitors in Ovarian Cancer

Most clinical PARP inhibitors (PARPis) trap PARP1 in a chromatin-bound state, leading to PARPi-mediated cytotoxicity. PARPi resistance impedes the treatment of ovarian cancer in clinical practice. However, the mechanism by which cancer cells overcome PARP1 trapping to develop PARPi resistance remains unclear. Here, it is shown that high levels of KAT6A promote PARPi resistance in ovarian cancer, regardless of its catalytic activity. Mechanistically, the liquid-liquid phase separation (LLPS) of KAT6A, facilitated by APEX1, inhibits the cytotoxic effects of PARP1 trapping during PARPi treatment. The stable KAT6A-PARP1-APEX1 complex reduces the amount of PARP1 trapped at the DNA break sites. In addition, inhibition of KAT6A LLPS, rather than its catalytic activity, impairs DNA damage repair and restores PARPi sensitivity in ovarian cancer both in vivo and in vitro. In conclusion, the findings demonstrate the role of KAT6A LLPS in fostering PARPi resistance and suggest that repressing KAT6A LLPS can be a potential therapeutic strategy for PARPi-resistant ovarian cancer.

Liquid-liquid phase separation-related features of PYGB/ACTR3/CCNA2/ITGB1/ATP8A1/RAP1GAP2 predict the prognosis of pancreatic cancer

Background

The growth and metastasis of pancreatic cancer (PC) has been found to be closely associated with liquid-liquid phase separation (LLPS). This study sought to identify LLPS-related biomarkers in PC to construct a robust prognostic model.

Methods

Transcriptomic data and clinical information related to PC were retrieved from publicly accessible databases. The PC-related data set was subjected to differential expression, Mendelian randomization (MR), univariate Cox, and least absolute selection and shrinkage operator analyses to identify biomarkers. Using the biomarkers, we subsequently constructed a risk model, identified the independent prognostic factors of PC, established a nomogram, and conducted an immune analysis.

Results

The study identified four genes linked with an increased risk of PC; that is, PYGB, ACTR3, CCNA2, and ITGB1. Conversely, ATP8A1, and RAP1GAP2 were found to provide protection against PC. These findings contributed significantly to the development of a highly precise risk model in which risk, age, and pathology N stage were categorized as independent factors in predicting the prognosis of PC patients. Using these factors, a nomogram was established to predict survival outcomes accurately. An immune analysis revealed varying levels of eosinophils, gamma delta T cells, and other immune cells between the distinct risk groups. The high-risk patients exhibited increased potential for immune escape, while the low-risk patients showed a higher response to immunotherapy.

Conclusions

Six genes were identified as having potential causal relationships with PC. These genes were integrated into a prognostic risk model, thereby serving as unique prognostic signatures. Our findings provide novel insights into predicting the prognosis of PC patients.

Phase-separated ParB enforces diverse DNA compaction modes and stabilizes the parS-centered partition complex

The tripartite ParABS system mediates chromosome segregation in the majority of bacterial species. Typically, DNA-bound ParB proteins around the parS sites condense the chromosomal DNA into a higher-order multimeric nucleoprotein complex for the ParA-driven partition. Despite extensive studies, the molecular mechanism underlying the dynamic assembly of the partition complex remains unclear. Herein, we demonstrate that Bacillus subtilis ParB (Spo0J), through the multimerization of its N-terminal domain, forms phase-separated condensates along a single DNA molecule, leading to the concurrent organization of DNA into a compact structure. Specifically, in addition to the co-condensation of ParB dimers with DNA, the engagement of well-established ParB condensates with DNA allows for the compression of adjacent DNA and the looping of distant DNA. Notably, the presence of CTP promotes the formation of condensates by a low amount of ParB at parS sites, triggering two-step DNA condensation. Remarkably, parS-centered ParB-DNA co-condensate constitutes a robust nucleoprotein architecture capable of withstanding disruptive forces of tens of piconewton. Overall, our findings unveil diverse modes of DNA compaction enabled by phase-separated ParB and offer new insights into the dynamic assembly and maintenance of the bacterial partition complex.

Role of RNA binding proteins of the Drosophila behavior and human splicing (DBHS) family in health and cancer

RNA-binding proteins (RBPs) play crucial roles in the functions and homoeostasis of various tissues by regulating multiple events of RNA processing including RNA splicing, intracellular RNA transport, and mRNA translation. The Drosophila behavior and human splicing (DBHS) family proteins including PSF/SFPQ, NONO, and PSPC1 are ubiquitously expressed RBPs that contribute to the physiology of several tissues. In mammals, DBHS proteins have been reported to contribute to neurological diseases and play crucial roles in cancers, such as prostate, breast, and liver cancers, by regulating cancer-specific gene expression. Notably, in recent years, multiple small molecules targeting DBHS family proteins have been developed for application as cancer therapeutics. This review provides a recent overview of the functions of DBHS family in physiology and pathophysiology, and discusses the application of DBHS family proteins as promising diagnostic and therapeutic targets for cancers.

A Liquid–Liquid Phase Separation-Related Index Associate with Biochemical Recurrence and Tumor Immune Environment of Prostate Cancer Patients

To identify liquid–liquid phase separation (LLPS)-related molecular clusters, and to develop and validate a novel index based on LLPS for predicting the prognosis of prostate cancer (PCa) patients. We download the clinical and transcriptome data of PCa from TCGA and GEO database. The LLPS-related genes (LRGs) were extracted from PhaSepDB. Consensus clustering analysis was used to develop LLPS-related molecular subtypes for PCa. The LASSO cox regression analysis was performed to establish a novel LLPS-related index for predicting biochemical recurrence (BCR)-free survival (BCRFS). Preliminary experimental verification was performed. We initially identified a total of 102 differentially expressed LRGs for PCa. Three LLPS related molecular subtypes were identified. Moreover, we established a novel LLPS related signature for predicting BCRFS of PCa patients. Compared to low-risk patients in the training cohort, testing cohort and validating cohort, high-risk populations meant a higher risk of BCR and significantly poorer BCRFS. The area under receiver operating characteristic curve were 0.728, 0.762, and 0.741 at 1 year in the training cohort, testing cohort and validating cohort. Additionally, the subgroup analysis indicated that this index was especially suitable for PCa patients with age ≤ 65, T stage III-IV, N0 stage or in cluster 1. The FUS, which was the potential biomarker related to PCa liquid–liquid phase separation, was preliminarily identified and verified. This study successfully developed three LLPS-related molecular subtypes and identified a novel LLPS related molecular signature, which performed well in predicting BCRFS of PCa.

Addressing the Reciprocal Crosstalk between the AR and the PI3K/AKT/mTOR Signaling Pathways for Prostate Cancer Treatment

The reduction in androgen synthesis and the blockade of the androgen receptor (AR) function by chemical castration and AR signaling inhibitors represent the main treatment lines for the initial stages of prostate cancer. Unfortunately, resistance mechanisms ultimately develop due to alterations in the AR pathway, such as gene amplification or mutations, and also the emergence of alternative pathways that render the tumor less or, more rarely, completely independent of androgen activation. An essential oncogenic axis activated in prostate cancer is the phosphatidylinositol-3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway, as evidenced by the frequent alterations of the negative regulator phosphatase and tensin homolog (PTEN) and by the activating mutations in PI3K subunits. Additionally, crosstalk and reciprocal feedback loops between androgen signaling and the PI3K/AKT/mTOR signaling cascade that activate pro-survival signals and play an essential role in disease recurrence and progression have been evidenced. Inhibitors addressing different players of the PI3K/AKT/mTOR pathway have been evaluated in the clinic. Only a limited benefit has been reported in prostate cancer up to now due to the associated side effects, so novel combination approaches and biomarkers predictive of patient response are urgently needed. Here, we reviewed recent data on the crosstalk between AR signaling and the PI3K/AKT/mTOR pathway, the selective inhibitors identified, and the most advanced clinical studies, with a focus on combination treatments. A deeper understanding of the complex molecular mechanisms involved in disease progression and treatment resistance is essential to further guide therapeutic approaches with improved outcomes.