Blockade of LAG-3 and PD-1 leads to co-expression of cytotoxic and exhaustion gene modules in CD8+ T cells to promote antitumor immunity.

Relatlimab (rela; anti-LAG-3) plus nivolumab (nivo; anti-PD-1) is safe and effective for treatment of advanced melanoma. We designed a trial (NCT03743766) where advanced melanoma patients received rela, nivo, or rela+nivo to interrogate the immunologic mechanisms of rela+nivo. Analysis of biospecimens from this ongoing trial demonstrated that rela+nivo led to enhanced capacity for CD8+ T cell receptor signaling and altered CD8+ T cell differentiation, leading to heightened cytotoxicity despite the retention of an exhaustion profile. Co-expression of cytotoxic and exhaustion signatures was driven by PRDM1, BATF, ETV7, and TOX. Effector function was upregulated in clonally expanded CD8+ T cells that emerged after rela+nivo. A rela+nivo intratumoral CD8+ T cell signature was associated with a favorable prognosis. This intratumoral rela+nivo signature was validated in peripheral blood as an elevated frequency of CD38+TIM3+CD8+ T cells. Overall, we demonstrated that cytotoxicity can be enhanced despite the retention of exhaustion signatures, which will inform future therapeutic strategies.

Global identification of SWI/SNF targets reveals compensation by EP400.

Mammalian SWI/SNF chromatin remodeling complexes move and evict nucleosomes at gene promoters and enhancers to modulate DNA access. Although SWI/SNF subunits are commonly mutated in disease, therapeutic options are limited by our inability to predict SWI/SNF gene targets and conflicting studies on functional significance. Here, we leverage a fast-acting inhibitor of SWI/SNF remodeling to elucidate direct targets and effects of SWI/SNF. Blocking SWI/SNF activity causes a rapid and global loss of chromatin accessibility and transcription. Whereas repression persists at most enhancers, we uncover a compensatory role for the EP400/TIP60 remodeler, which reestablishes accessibility at most promoters during prolonged loss of SWI/SNF. Indeed, we observe synthetic lethality between EP400 and SWI/SNF in cancer cell lines and human cancer patient data. Our data define a set of molecular genomic features that accurately predict gene sensitivity to SWI/SNF inhibition in diverse cancer cell lines, thereby improving the therapeutic potential of SWI/SNF inhibitors.

Targeting Pin1 renders pancreatic cancer eradicable by synergizing with immunochemotherapy.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by notorious resistance to current therapies attributed to inherent tumor heterogeneity and highly desmoplastic and immunosuppressive tumor microenvironment (TME). Unique proline isomerase Pin1 regulates multiple cancer pathways, but its role in the TME and cancer immunotherapy is unknown. Here, we find that Pin1 is overexpressed both in cancer cells and cancer-associated fibroblasts (CAFs) and correlates with poor survival in PDAC patients. Targeting Pin1 using clinically available drugs induces complete elimination or sustained remissions of aggressive PDAC by synergizing with anti-PD-1 and gemcitabine in diverse model systems. Mechanistically, Pin1 drives the desmoplastic and immunosuppressive TME by acting on CAFs and induces lysosomal degradation of the PD-1 ligand PD-L1 and the gemcitabine transporter ENT1 in cancer cells, besides activating multiple cancer pathways. Thus, Pin1 inhibition simultaneously blocks multiple cancer pathways, disrupts the desmoplastic and immunosuppressive TME, and upregulates PD-L1 and ENT1, rendering PDAC eradicable by immunochemotherapy.

Oncogenic Signaling Pathways in The Cancer Genome Atlas.

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFß signaling, p53 and ß-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these pathways, and 57% percent of tumors had at least one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy.

A Fine-Scale Functional Logic to Convergence from Retina to Thalamus.

Numerous well-defined classes of retinal ganglion cells innervate the thalamus to guide image-forming vision, yet the rules governing their convergence and divergence remain unknown. Using two-photon calcium imaging in awake mouse thalamus, we observed a functional arrangement of retinal ganglion cell axonal boutons in which coarse-scale retinotopic ordering gives way to fine-scale organization based on shared preferences for other visual features. Specifically, at the ∼6 µm scale, clusters of boutons from different axons often showed similar preferences for either one or multiple features, including axis and direction of motion, spatial frequency, and changes in luminance. Conversely, individual axons could "de-multiplex" information channels by participating in multiple, functionally distinct bouton clusters. Finally, ultrastructural analyses demonstrated that retinal axonal boutons in a local cluster often target the same dendritic domain. These data suggest that functionally specific convergence and divergence of retinal axons may impart diverse, robust, and often novel feature selectivity to visual thalamus.

Combination Cancer Therapy Can Confer Benefit via Patient-to-Patient Variability without Drug Additivity or Synergy.

Combination cancer therapies aim to improve the probability and magnitude of therapeutic responses and reduce the likelihood of acquired resistance in an individual patient. However, drugs are tested in clinical trials on genetically diverse patient populations. We show here that patient-to-patient variability and independent drug action are sufficient to explain the superiority of many FDA-approved drug combinations in the absence of drug synergy or additivity. This is also true for combinations tested in patient-derived tumor xenografts. In a combination exhibiting independent drug action, each patient benefits solely from the drug to which his or her tumor is most sensitive, with no added benefit from other drugs. Even when drug combinations exhibit additivity or synergy in pre-clinical models, patient-to-patient variability and low cross-resistance make independent action the dominant mechanism in clinical populations. This insight represents a different way to interpret trial data and a different way to design combination therapies.

MED12 and BRD4 cooperate to sustain cancer growth upon loss of mediator kinase.

Mediator kinases (CDK8/19) are transcriptional regulators broadly implicated in cancer. Despite their central role in fine-tuning gene-expression programs, we find complete loss of CDK8/19 is tolerated in colorectal cancer (CRC) cells. Using orthogonal functional genomic and pharmacological screens, we identify BET protein inhibition as a distinct vulnerability in CDK8/19-depleted cells. Combined CDK8/19 and BET inhibition led to synergistic growth retardation in human and mouse models of CRC. Strikingly, depletion of CDK8/19 in these cells led to global repression of RNA polymerase II (Pol II) promoter occupancy and transcription. Concurrently, loss of Mediator kinase led to a profound increase in MED12 and BRD4 co-occupancy at enhancer elements and increased dependence on BET proteins for the transcriptional output of cell-essential genes. In total, this work demonstrates a synthetic lethal interaction between Mediator kinase and BET proteins and exposes a therapeutic vulnerability that can be targeted using combination therapies.

Antibodies to Costimulatory Receptor 4-1BB Enhance Anti-tumor Immunity via T Regulatory Cell Depletion and Promotion of CD8 T Cell Effector Function.

The costimulatory receptor 4-1BB is expressed on activated immune cells, including activated T cells. Antibodies targeting 4-1BB enhance the proliferation and survival of antigen-stimulated T cells in vitro and promote CD8 T cell-dependent anti-tumor immunity in pre-clinical cancer models. We found that T regulatory (Treg) cells infiltrating human or murine tumors expressed high amounts of 4-1BB. Intra-tumoral Treg cells were preferentially depleted by anti-4-1BB mAbs in vivo. Anti-4-1BB mAbs also promoted effector T cell agonism to promote tumor rejection. These distinct mechanisms were competitive and dependent on antibody isotype and FcγR availability. Administration of anti-4-1BB IgG2a, which preferentially depletes Treg cells, followed by either agonistic anti-4-1BB IgG1 or anti-PD-1 mAb augmented anti-tumor responses in multiple solid tumor models. An antibody engineered to optimize both FcγR-dependent Treg cell depleting capacity and FcγR-independent agonism delivered enhanced anti-tumor therapy. These insights into the effector mechanisms of anti-4-1BB mAbs lay the groundwork for translation into the clinic.

Metabolomics-Driven Exploration of the Chemical Drug Space to Predict Combination Antimicrobial Therapies.

Alternative to the conventional search for single-target, single-compound treatments, combination therapies can open entirely new opportunities to fight antibiotic resistance. However, combinatorial complexity prohibits experimental testing of drug combinations on a large scale, and methods to rationally design combination therapies are lagging behind. Here, we developed a combined experimental-computational approach to predict drug-drug interactions using high-throughput metabolomics. The approach was tested on 1,279 pharmacologically diverse drugs applied to the gram-negative bacterium Escherichia coli. Combining our metabolic profiling of drug response with previously generated metabolic and chemogenomic profiles of 3,807 single-gene deletion strains revealed an unexpectedly large space of inhibited gene functions and enabled rational design of drug combinations. This approach is applicable to other therapeutic areas and can unveil unprecedented insights into drug tolerance, side effects, and repurposing. The compendium of drug-associated metabolome profiles is available at https://zampierigroup.shinyapps.io/EcoPrestMet, providing a valuable resource for the microbiological and pharmacological communities.

IKKα Kinase Regulates the DNA Damage Response and Drives Chemo-resistance in Cancer.

Phosphorylated IKKα(p45) is a nuclear active form of the IKKα kinase that is induced by the MAP kinases BRAF and TAK1 and promotes tumor growth independent of canonical NF-κB signaling. Insights into the sources of IKKα(p45) activation and its downstream substrates in the nucleus remain to be defined. Here, we discover that IKKα(p45) is rapidly activated by DNA damage independent of ATM-ATR, but dependent on BRAF-TAK1-p38-MAPK, and is required for robust ATM activation and efficient DNA repair. Abolishing BRAF or IKKα activity attenuates ATM, Chk1, MDC1, Kap1, and 53BP1 phosphorylation, compromises 53BP1 and RIF1 co-recruitment to sites of DNA lesions, and inhibits 53BP1-dependent fusion of dysfunctional telomeres. Furthermore, IKKα or BRAF inhibition synergistically enhances the therapeutic potential of 5-FU and irinotecan to eradicate chemotherapy-resistant metastatic human tumors in vivo. Our results implicate BRAF and IKKα kinases in the DDR and reveal a combination strategy for cancer treatment.

How small changes to one eye's retinal image can transform the perceived shape of a very familiar object.

Vision can provide useful cues about the geometric properties of an object, like its size, distance, pose, and shape. But how the brain merges these properties into a complete sensory representation of a three-dimensional object is poorly understood. To address this gap, we investigated a visual illusion in which humans misperceive the shape of an object due to a small change in one eye's retinal image. We first show that this illusion affects percepts of a highly familiar object under completely natural viewing conditions. Specifically, people perceived their own rectangular mobile phone to have a trapezoidal shape. We then investigate the perceptual underpinnings of this illusion by asking people to report both the perceived shape and pose of controlled stimuli. Our results suggest that the shape illusion results from distorted cues to object pose. In addition to yielding insights into object perception, this work informs our understanding of how the brain combines information from multiple visual cues in natural settings. The shape illusion can occur when people wear everyday prescription spectacles; thus, these findings also provide insight into the cue combination challenges that some spectacle wearers experience on a regular basis.

Development of an aptamer capable of multidrug resistance reversal for tumor combination chemotherapy.

Multidrug resistance (MDR) is a major factor in the failure of many forms of tumor chemotherapy. Development of a specific ligand for MDR-reversal would enhance the intracellular accumulation of therapeutic agents and effectively improve the tumor treatments. Here, an aptamer was screened against a doxorubicin (DOX)-resistant human hepatocellular carcinoma cell line (HepG2/DOX) via cell-based systematic evolution of ligands by exponential enrichment. A 50 nt truncated sequence termed d3 was obtained with high affinity and specificity for HepG2/DOX cells. Multidrug resistance protein 1 (MDR1) is determined to be a possible recognition target of the selected aptamer. Aptamer d3 binding was revealed to block the MDR of the tumor cells and increase the accumulation of intracellular anticancer drugs, including DOX, vincristine, and paclitaxel, which led to a boost to the cell killing of the anticancer drugs and lowering their survival of the tumor cells. The aptamer d3-mediated MDR-reversal for effective chemotherapy was further verified in an in vivo animal model, and combination of aptamer d3 with DOX significantly improved the suppression of tumor growth by treating a xenograft HepG2/DOX tumor in vivo. This work demonstrates the feasibility of a therapeutic DNA aptamer as a tumor MDR-reversal agent, and combination of the selected aptamer with chemotherapeutic drugs shows great potential for liver cancer treatments.

Single-cell dissection of tumor microenvironmental response and resistance to cancer therapy.

Cancer treatment strategies have evolved significantly over the years, with chemotherapy, targeted therapy, and immunotherapy as major pillars. Each modality leads to unique treatment outcomes by interacting with the tumor microenvironment (TME), which imposes a fundamental selective pressure on cancer progression. The advent of single-cell profiling technologies has revolutionized our understanding of the intricate and heterogeneous nature of the TME at an unprecedented resolution. This review delves into the commonalities and differential manifestations of how cancer therapies reshape the microenvironment in diverse cancer types. We highlight how groundbreaking immune checkpoint blockade (ICB) strategies alone or in combination with tumor-targeting treatments are endowed with comprehensive mechanistic insights when decoded at the single-cell level, aiming to drive forward future research directions on personalized treatments.

Emerging Therapies in Hypothyroidism.

Levothyroxine (LT4) is effective for most patients with hypothyroidism. However, a minority of the patients remain symptomatic despite the normalization of serum thyrotropin levels. Randomized clinical trials including all types of patients with hypothyroidism revealed that combination levothyroxine and liothyronine (LT4+LT3) therapy is safe and is the preferred choice of patients versus LT4 alone. Many patients who do not fully benefit from LT4 experience improved quality of life and cognition after switching to LT4+LT3. For these patients, new slow-release LT3 formulations that provide stable serum T3 levels are being tested. In addition, progress in regenerative technology has led to the development of human thyroid organoids that restore euthyroidism after being transplanted into hypothyroid mice. Finally, there is a new understanding that, under certain conditions, T3 signaling may be compromised in a tissue-specific fashion while systemic thyroid function is preserved. This is seen, for example, in patients with metabolic (dysfunction)-associated fatty liver disease, for whom liver-selective T3-like molecules have been utilized successfully in clinical trials.

A high-dimensional omnibus test for set-based association analysis.

Set-based association analysis is a valuable tool in studying the etiology of complex diseases in genome-wide association studies, as it allows for the joint testing of variants in a region or group. Two common types of single nucleotide polymorphism (SNP)-disease functional models are recognized when evaluating the joint function of a set of SNP: the cumulative weak signal model, in which multiple functional variants with small effects contribute to disease risk, and the dominating strong signal model, in which a few functional variants with large effects contribute to disease risk. However, existing methods have two main limitations that reduce their power. Firstly, they typically only consider one disease-SNP association model, which can result in significant power loss if the model is misspecified. Secondly, they do not account for the high-dimensional nature of SNPs, leading to low power or high false positives. In this study, we propose a solution to these challenges by using a high-dimensional inference procedure that involves simultaneously fitting many SNPs in a regression model. We also propose an omnibus testing procedure that employs a robust and powerful P-value combination method to enhance the power of SNP-set association. Our results from extensive simulation studies and a real data analysis demonstrate that our set-based high-dimensional inference strategy is both flexible and computationally efficient and can substantially improve the power of SNP-set association analysis. Application to a real dataset further demonstrates the utility of the testing strategy.

SynergyX: a multi-modality mutual attention network for interpretable drug synergy prediction.

Discovering effective anti-tumor drug combinations is crucial for advancing cancer therapy. Taking full account of intricate biological interactions is highly important in accurately predicting drug synergy. However, the extremely limited prior knowledge poses great challenges in developing current computational methods. To address this, we introduce SynergyX, a multi-modality mutual attention network to improve anti-tumor drug synergy prediction. It dynamically captures cross-modal interactions, allowing for the modeling of complex biological networks and drug interactions. A convolution-augmented attention structure is adopted to integrate multi-omic data in this framework effectively. Compared with other state-of-the-art models, SynergyX demonstrates superior predictive accuracy in both the General Test and Blind Test and cross-dataset validation. By exhaustively screening combinations of approved drugs, SynergyX reveals its ability to identify promising drug combination candidates for potential lung cancer treatment. Another notable advantage lies in its multidimensional interpretability. Taking Sorafenib and Vorinostat as an example, SynergyX serves as a powerful tool for uncovering drug-gene interactions and deciphering cell selectivity mechanisms. In summary, SynergyX provides an illuminating and interpretable framework, poised to catalyze the expedition of drug synergy discovery and deepen our comprehension of rational combination therapy.

The phosphatase inhibitor LB-100 creates neoantigens in colon cancer cells through perturbation of mRNA splicing.

Perturbation of protein phosphorylation represents an attractive approach to cancer treatment. Besides kinase inhibitors, protein phosphatase inhibitors have been shown to have anti-cancer activity. A prime example is the small molecule LB-100, an inhibitor of protein phosphatases 2A/5 (PP2A/PP5), enzymes that affect cellular physiology. LB-100 has proven effective in pre-clinical models in combination with immunotherapy, but the molecular underpinnings of this synergy remain understood poorly. We report here a sensitivity of the mRNA splicing machinery to phosphorylation changes in response to LB-100 in colorectal adenocarcinoma. We observe enrichment for differentially phosphorylated sites within cancer-critical splicing nodes of U2 snRNP, SRSF and hnRNP proteins. Altered phosphorylation endows LB-100-treated colorectal adenocarcinoma cells with differential splicing patterns. In PP2A-inhibited cells, over 1000 events of exon skipping and intron retention affect regulators of genomic integrity. Finally, we show that LB-100-evoked alternative splicing leads to neoantigens that are presented by MHC class 1 at the cell surface. Our findings provide a potential explanation for the pre-clinical and clinical observations that LB-100 sensitizes cancer cells to immune checkpoint blockade.

Nuclear VCP drives colorectal cancer progression by promoting fatty acid oxidation.

Fatty acid oxidation (FAO) fuels many cancers. However, knowledge of pathways that drive FAO in cancer remains unclear. Here, we revealed that valosin-containing protein (VCP) upregulates FAO to promote colorectal cancer growth. Mechanistically, nuclear VCP binds to histone deacetylase 1 (HDAC1) and facilitates its degradation, thus promoting the transcription of FAO genes, including the rate-limiting enzyme carnitine palmitoyltransferase 1A (CPT1A). FAO is an alternative fuel for cancer cells in environments exhibiting limited glucose availability. We observed that a VCP inhibitor blocked the upregulation of FAO activity and CPT1A expression triggered by metformin in colorectal cancer (CRC) cells. Combined VCP inhibitor and metformin prove more effective than either agent alone in culture and in vivo. Our study illustrates the molecular mechanism underlying the regulation of FAO by nuclear VCP and demonstrates the potential therapeutic utility of VCP inhibitor and metformin combination treatment for colorectal cancer.

NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding the mechanisms of gene expression regulation. Although deep convolutional neural networks (CNNs) have achieved great success in predicting cis-regulatory elements, the discovery of motifs and their combinatorial patterns from these CNN models has remained difficult. We show that the main difficulty is due to the problem of multifaceted neurons which respond to multiple types of sequence patterns. Since existing interpretation methods were mainly designed to visualize the class of sequences that can activate the neuron, the resulting visualization will correspond to a mixture of patterns. Such a mixture is usually difficult to interpret without resolving the mixed patterns. We propose the NeuronMotif algorithm to interpret such neurons. Given any convolutional neuron (CN) in the network, NeuronMotif first generates a large sample of sequences capable of activating the CN, which typically consists of a mixture of patterns. Then, the sequences are "demixed" in a layer-wise manner by backward clustering of the feature maps of the involved convolutional layers. NeuronMotif can output the sequence motifs, and the syntax rules governing their combinations are depicted by position weight matrices organized in tree structures. Compared to existing methods, the motifs found by NeuronMotif have more matches to known motifs in the JASPAR database. The higher-order patterns uncovered for deep CNs are supported by the literature and ATAC-seq footprinting. Overall, NeuronMotif enables the deciphering of cis-regulatory codes from deep CNs and enhances the utility of CNN in genome interpretation.

The impact of multifactorial stress combination on reproductive tissues and grain yield of a crop plant.

Global warming, climate change, and industrial pollution are altering our environment subjecting plants, microbiomes, and ecosystems to an increasing number and complexity of abiotic stress conditions, concurrently or sequentially. These conditions, termed, "multifactorial stress combination" (MFSC), can cause a significant decline in plant growth and survival. However, the impacts of MFSC on reproductive tissues and yield of major crop plants are largely unknown. We subjected soybean (Glycine max) plants to a MFSC of up to five different stresses (water deficit, salinity, low phosphate, acidity, and cadmium), in an increasing level of complexity, and conducted integrative transcriptomic-phenotypic analysis of their reproductive and vegetative tissues. We reveal that MFSC has a negative cumulative effect on soybean yield, that each set of MFSC condition elicits a unique transcriptomic response (that is different between flowers and leaves), and that selected genes expressed in leaves or flowers of soybean are linked to the effects of MFSC on different vegetative, physiological, and/or reproductive parameters. Our study identified networks and pathways associated with reactive oxygen species, ascorbic acid and aldarate, and iron/copper signaling/metabolism as promising targets for future biotechnological efforts to augment the resilience of reproductive tissues of major crop plants to MFSC. In addition, we provide unique phenotypic and transcriptomic datasets for dissecting the mechanistic effects of MFSC on the vegetative, physiological, and reproductive processes of a crop plant.