Paired mapping of single-cell gene expression and electrophysiology is essential to understand gene-to-function relationships in electrogenic tissues. Here, we developed in situ electro-sequencing (electro-seq) that combines flexible bioelectronics with in situ RNA sequencing to stably map millisecond-timescale electrical activity and profile single-cell gene expression from the same cells across intact biological networks, including cardiac and neural patches. When applied to human-induced pluripotent stem-cell-derived cardiomyocyte patches, in situ electro-seq enabled multimodal in situ analysis of cardiomyocyte electrophysiology and gene expression at the cellular level, jointly defining cell states and developmental trajectories. Using machine-learning-based cross-modal analysis, in situ electro-seq identified gene-to-electrophysiology relationships throughout cardiomyocyte development and accurately reconstructed the evolution of gene expression profiles based on long-term stable electrical measurements. In situ electro-seq could be applicable to create spatiotemporal multimodal maps in electrogenic tissues, potentiating the discovery of cell types and gene programs responsible for electrophysiological function and dysfunction.

Functional genomic strategies have become fundamental for annotating gene function and regulatory networks. Here, we combined functional genomics with proteomics by quantifying protein abundances in a genome-scale knockout library in Saccharomyces cerevisiae, using data-independent acquisition mass spectrometry. We find that global protein expression is driven by a complex interplay of (1) general biological properties, including translation rate, protein turnover, the formation of protein complexes, growth rate, and genome architecture, followed by (2) functional properties, such as the connectivity of a protein in genetic, metabolic, and physical interaction networks. Moreover, we show that functional proteomics complements current gene annotation strategies through the assessment of proteome profile similarity, protein covariation, and reverse proteome profiling. Thus, our study reveals principles that govern protein expression and provides a genome-spanning resource for functional annotation.

Cachexia, a systemic wasting condition, is considered a late consequence of diseases, including cancer, organ failure, or infections, and contributes to significant morbidity and mortality. The induction process and mechanistic progression of cachexia are incompletely understood. Refocusing academic efforts away from advanced cachexia to the etiology of cachexia may enable discoveries of new therapeutic approaches. Here, we review drivers, mechanisms, organismal predispositions, evidence for multi-organ interaction, model systems, clinical research, trials, and care provision from early onset to late cachexia. Evidence is emerging that distinct inflammatory, metabolic, and neuro-modulatory drivers can initiate processes that ultimately converge on advanced cachexia.

The spectrin-based membrane skeleton is a ubiquitous membrane-associated two-dimensional cytoskeleton underneath the lipid membrane of metazoan cells. Mutations of skeleton proteins impair the mechanical strength and functions of the membrane, leading to several different types of human diseases. Here, we report the cryo-EM structures of the native spectrin-actin junctional complex (from porcine erythrocytes), which is a specialized short F-actin acting as the central organizational unit of the membrane skeleton. While an α-/β-adducin hetero-tetramer binds to the barbed end of F-actin as a flexible cap, tropomodulin and SH3BGRL2 together create an absolute cap at the pointed end. The junctional complex is strengthened by ring-like structures of dematin in the middle actin layers and by patterned periodic interactions with tropomyosin over its entire length. This work serves as a structural framework for understanding the assembly and dynamics of membrane skeleton and offers insights into mechanisms of various ubiquitous F-actin-binding factors in other F-actin systems.

Over the past few years, numerous anti-phage defense systems have been discovered in bacteria. Although the mechanism of defense for some of these systems is understood, a major unanswered question is how these systems sense phage infection. To systematically address this question, we isolated 177 phage mutants that escape 15 different defense systems. In many cases, these escaper phages were mutated in the gene sensed by the defense system, enabling us to map the phage determinants that confer sensitivity to bacterial immunity. Our data identify specificity determinants of diverse retron systems and reveal phage-encoded triggers for multiple abortive infection systems. We find general themes in phage sensing and demonstrate that mechanistically diverse systems have converged to sense either the core replication machinery of the phage, phage structural components, or host takeover mechanisms. Combining our data with previous findings, we formulate key principles on how bacterial immune systems sense phage invaders.

Cortical circuits are composed predominantly of pyramidal-to-pyramidal neuron connections, yet their assembly during embryonic development is not well understood. We show that mouse embryonic Rbp4-Cre cortical neurons, transcriptomically closest to layer 5 pyramidal neurons, display two phases of circuit assembly in vivo. At E14.5, they form a multi-layered circuit motif, composed of only embryonic near-projecting-type neurons. By E17.5, this transitions to a second motif involving all three embryonic types, analogous to the three adult layer 5 types. In vivo patch clamp recordings and two-photon calcium imaging of embryonic Rbp4-Cre neurons reveal active somas and neurites, tetrodotoxin-sensitive voltage-gated conductances, and functional glutamatergic synapses, from E14.5 onwards. Embryonic Rbp4-Cre neurons strongly express autism-associated genes and perturbing these genes interferes with the switch between the two motifs. Hence, pyramidal neurons form active, transient, multi-layered pyramidal-to-pyramidal circuits at the inception of neocortex, and studying these circuits could yield insights into the etiology of autism.

Farmed mammals may act as hosts for zoonotic viruses that can cause disease outbreaks in humans. This SnapShot shows which farmed mammals, and to what extent, are of particular risk of harboring and spreading viruses from viral families that are commonly associated with zoonotic disease. It also discusses genome surveillance methods and biosafety measures. To view this SnapShot, open or download the PDF.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers. Significant efforts have largely defined major genetic factors driving PDAC pathogenesis and progression. Pancreatic tumors are characterized by a complex microenvironment that orchestrates metabolic alterations and supports a milieu of interactions among various cell types within this niche. In this review, we highlight the foundational studies that have driven our understanding of these processes. We further discuss the recent technological advances that continue to expand our understanding of PDAC complexity. We posit that the clinical translation of these research endeavors will enhance the currently dismal survival rate of this recalcitrant disease.

The uptake and metabolism of nutrients support fundamental cellular process from bioenergetics to biomass production and cell fate regulation. While many studies of cell metabolism focus on cancer cells, the principles of metabolism elucidated in cancer cells apply to a wide range of mammalian cells. The goal of this review is to discuss how the field of cancer metabolism provides a framework for revealing principles of cell metabolism and for dissecting the metabolic networks that allow cells to meet their specific demands. Understanding context-specific metabolic preferences and liabilities will unlock new approaches to target cancer cells to improve patient care.

Breast cancer remains a leading cause of cancer-related mortality in women, reflecting profound disease heterogeneity, metastasis, and therapeutic resistance. Over the last decade, genomic and transcriptomic data have been integrated on an unprecedented scale and revealed distinct cancer subtypes, critical molecular drivers, clonal evolutionary trajectories, and prognostic signatures. Furthermore, multi-dimensional integration of high-resolution single-cell and spatial technologies has highlighted the importance of the entire breast cancer ecosystem and the presence of distinct cellular "neighborhoods." Clinically, a plethora of new targeted therapies has emerged, now being rapidly incorporated into routine care. Resistance to therapy, however, remains a crucial challenge for the field.

Most cancer-associated deaths occur due to metastasis, yet our understanding of metastasis as an evolving, heterogeneous, systemic disease and of how to effectively treat it is still emerging. Metastasis requires the acquisition of a succession of traits to disseminate, variably enter and exit dormancy, and colonize distant organs. The success of these events is driven by clonal selection, the potential of metastatic cells to dynamically transition into distinct states, and their ability to co-opt the immune environment. Here, we review the main principles of metastasis and highlight emerging opportunities to develop more effective therapies for metastatic cancer.

Immune checkpoint therapy (ICT) has dramatically altered clinical outcomes for cancer patients and conferred durable clinical benefits, including cure in a subset of patients. Varying response rates across tumor types and the need for predictive biomarkers to optimize patient selection to maximize efficacy and minimize toxicities prompted efforts to unravel immune and non-immune factors regulating the responses to ICT. This review highlights the biology of anti-tumor immunity underlying response and resistance to ICT, discusses efforts to address the current challenges with ICT, and outlines strategies to guide the development of subsequent clinical trials and combinatorial efforts with ICT.

The nervous system governs both ontogeny and oncology. Regulating organogenesis during development, maintaining homeostasis, and promoting plasticity throughout life, the nervous system plays parallel roles in the regulation of cancers. Foundational discoveries have elucidated direct paracrine and electrochemical communication between neurons and cancer cells, as well as indirect interactions through neural effects on the immune system and stromal cells in the tumor microenvironment in a wide range of malignancies. Nervous system-cancer interactions can regulate oncogenesis, growth, invasion and metastatic spread, treatment resistance, stimulation of tumor-promoting inflammation, and impairment of anti-cancer immunity. Progress in cancer neuroscience may create an important new pillar of cancer therapy.

Macrophages are versatile and heterogeneous innate immune cells undertaking central functions in balancing immune responses and tissue repair to maintain homeostasis. This plasticity, once co-opted by malignant outgrowth, orchestrates manifold reciprocal interactions within the tumor microenvironment, fueling the evolution of the cancer ecosystem. Here, we review the multilayered sources of influence that jointly underpin and longitudinally shape tumor-associated macrophage (TAM) phenotypic states in solid neoplasms. We discuss how, in response to these signals, TAMs steer tumor evolution in the context of natural selection, biological dispersion, and treatment resistance. A number of research frontiers to be tackled are laid down in this review to therapeutically exploit the complex roles of TAMs in cancer. Building upon knowledge obtained from currently applied TAM-targeting strategies and using next generation technologies, we propose conceptual advances and novel therapeutic avenues to rewire TAM multifaceted regulation of the co-evolving cancer ecosystem.

Intercellular communication is a key feature of cancer progression and metastasis. Extracellular vesicles (EVs) are generated by all cells, including cancer cells, and recent studies have identified EVs as key mediators of cell-cell communication via packaging and transfer of bioactive constituents to impact the biology and function of cancer cells and cells of the tumor microenvironment. Here, we review recent advances in understanding the functional contribution of EVs to cancer progression and metastasis, as cancer biomarkers, and the development of cancer therapeutics.

Tumor cells do not exist in isolation in vivo, and carcinogenesis depends on the surrounding tumor microenvironment (TME), composed of a myriad of cell types and biophysical and biochemical components. Fibroblasts are integral in maintaining tissue homeostasis. However, even before a tumor develops, pro-tumorigenic fibroblasts in close proximity can provide the fertile 'soil' to the cancer 'seed' and are known as cancer-associated fibroblasts (CAFs). In response to intrinsic and extrinsic stressors, CAFs reorganize the TME enabling metastasis, therapeutic resistance, dormancy and reactivation by secreting cellular and acellular factors. In this review, we summarize the recent discoveries on CAF-mediated cancer progression with a particular focus on fibroblast heterogeneity and plasticity.

Therapeutic modalities that engage the immune system to recognize and eliminate cancer, known as cancer immunotherapy, has emerged as a distinct pillar of cancer therapy. Among the most promising treatment approaches are therapeutic vaccines, immune checkpoint blockade, bispecific T-cell engagers (BiTEs) and adoptive cell therapies. These approaches share a common mechanism of action, which is elicitation of a T-cell-based immune response, either endogenous or engineered, against tumor antigens, but interactions between the innate immune system, particularly antigen-presenting cells, and immune effectors also underlie the efficacy of cancer immunotherapies and approaches engaging these cells are also under development. To view this SnapShot, open or download the PDF.

Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict patient outcomes, and inform treatment planning. Here, we review recent applications of ML across the clinical oncology workflow. We review how these techniques are applied to medical imaging and to molecular data obtained from liquid and solid tumor biopsies for cancer diagnosis, prognosis, and treatment design. We discuss key considerations in developing ML for the distinct challenges posed by imaging and molecular data. Finally, we examine ML models approved for cancer-related patient usage by regulatory agencies and discuss approaches to improve the clinical usefulness of ML.

Recent identification of oncogenic cells within healthy tissues and the prevalence of indolent cancers found incidentally at autopsies reveal a greater complexity in tumor initiation than previously appreciated. The human body contains roughly 40 trillion cells of 200 different types that are organized within a complex three-dimensional matrix, necessitating exquisite mechanisms to restrain aberrant outgrowth of malignant cells that have the capacity to kill the host. Understanding how this defense is overcome to trigger tumorigenesis and why cancer is so extraordinarily rare at the cellular level is vital to future prevention therapies. In this review, we discuss how early initiated cells are protected from further tumorigenesis and the non-mutagenic pathways by which cancer risk factors promote tumor growth. By nature, the absence of permanent genomic alterations potentially renders these tumor-promoting mechanisms clinically targetable. Finally, we consider existing strategies for early cancer interception with perspectives on the next steps for molecular cancer prevention.

A core mission of cancer genomics is to comprehensively chart molecular underpinnings of cancer-driving events and to provide personalized therapeutic strategies. Primarily focused on cancer cells, cancer genomics studies have successfully uncovered many drivers for major cancer types. Since the emergence of cancer immune evasion as a critical cancer hallmark, the paradigm has been elevated to the holistic tumor ecosystem, with distinct cellular components and their functional states elucidated. We highlight the milestones of cancer genomics, depict the evolving path of the field, and discuss future directions in completing the understanding of the tumor ecosystem and in advancing therapeutic strategies.

Decades of oncologic clinical use have demonstrated that cancer immunotherapy provides unprecedented therapeutic benefits. Tragically, only a minority of patients respond to existing immunotherapies. RNA lipid nanoparticles have recently emerged as modular tools for immune stimulation. Here, we discuss advancements in RNA-based cancer immunotherapies and opportunities for improvement.

My patient was in his late 20s and dying of an advanced sarcoma. He came to our institution seeking a miracle-a cure for his incurable cancer. Despite second and third opinions, he never relinquished his hope that science would cure him. In this story, I explore how hope allowed my patient, and others like him, to reclaim their narratives and maintain their personhood in the face of serious illness.

Despite many advances, metastatic disease remains essentially uncurable. Thus, there is an urgent need to better understand mechanisms that promote metastasis, drive tumor evolution, and underlie innate and acquired drug resistance. Sophisticated preclinical models that recapitulate the complex tumor ecosystem are key to this process. We begin with syngeneic and patient-derived mouse models that are the backbone of most preclinical studies. Second, we present some unique advantages of fish and fly models. Third, we consider the strengths of 3D culture models for resolving remaining knowledge gaps. Finally, we provide vignettes on multiplexed technologies to advance our understanding of metastatic disease.

Selpercatinib is a small molecule that binds at the RET kinase active site. It inhibits activity of constitutively dimerized RET fusion proteins and activated point mutants, thereby blocking downstream signals for proliferation and survival. It is the first selective RET inhibitor to be FDA approved for tumor agnostic targeting of oncogenic RET fusion proteins. To view this Bench to Bedside, open or download the PDF.

Solid tumors are composed of a complex and dynamic collection of cell types. Here I discuss the important relationships between cancer cells and bacterial members of the intratumoral microbiota that may provide a fitness advantage within the tumor ecological niche.

The high and increasing prices of cancer drugs are a public health challenge. To disrupt the cancer premium and improve patient access to cancer drugs, different action steps are indicated: more transparency on the price determination process and actual prices, value-based pricing, and "price with evidence development."