A developmental constraint model of cancer cell states and tumor heterogeneity.

Cancer is a disease that stems from a fundamental liability inherent to multicellular life forms in which an individual cell is capable of reneging on the interests of the collective organism. Although cancer is commonly described as an evolutionary process, a less appreciated aspect of tumorigenesis may be the constraints imposed by the organism's developmental programs. Recent work from single-cell transcriptomic analyses across a range of cancer types has revealed the recurrence, plasticity, and co-option of distinct cellular states among cancer cell populations. Here, we note that across diverse cancer types, the observed cell states are proximate within the developmental hierarchy of the cell of origin. We thus posit a model by which cancer cell states are directly constrained by the organism's "developmental map." According to this model, a population of cancer cells traverses the developmental map, thereby generating a heterogeneous set of states whose interactions underpin emergent tumor behavior.

Human microglial state dynamics in Alzheimer's disease progression.

Altered microglial states affect neuroinflammation, neurodegeneration, and disease but remain poorly understood. Here, we report 194,000 single-nucleus microglial transcriptomes and epigenomes across 443 human subjects and diverse Alzheimer's disease (AD) pathological phenotypes. We annotate 12 microglial transcriptional states, including AD-dysregulated homeostatic, inflammatory, and lipid-processing states. We identify 1,542 AD-differentially-expressed genes, including both microglia-state-specific and disease-stage-specific alterations. By integrating epigenomic, transcriptomic, and motif information, we infer upstream regulators of microglial cell states, gene-regulatory networks, enhancer-gene links, and transcription-factor-driven microglial state transitions. We demonstrate that ectopic expression of our predicted homeostatic-state activators induces homeostatic features in human iPSC-derived microglia-like cells, while inhibiting activators of inflammation can block inflammatory progression. Lastly, we pinpoint the expression of AD-risk genes in microglial states and differential expression of AD-risk genes and their regulators during AD progression. Overall, we provide insights underlying microglial states, including state-specific and AD-stage-specific microglial alterations at unprecedented resolution.

Brain-wide representations of behavior spanning multiple timescales and states in C. elegans.

Changes in an animal's behavior and internal state are accompanied by widespread changes in activity across its brain. However, how neurons across the brain encode behavior and how this is impacted by state is poorly understood. We recorded brain-wide activity and the diverse motor programs of freely moving C. elegans and built probabilistic models that explain how each neuron encodes quantitative behavioral features. By determining the identities of the recorded neurons, we created an atlas of how the defined neuron classes in the C. elegans connectome encode behavior. Many neuron classes have conjunctive representations of multiple behaviors. Moreover, although many neurons encode current motor actions, others integrate recent actions. Changes in behavioral state are accompanied by widespread changes in how neurons encode behavior, and we identify these flexible nodes in the connectome. Our results provide a global map of how the cell types across an animal's brain encode its behavior.

Atlas of clinically distinct cell states and ecosystems across human solid tumors.

Determining how cells vary with their local signaling environment and organize into distinct cellular communities is critical for understanding processes as diverse as development, aging, and cancer. Here we introduce EcoTyper, a machine learning framework for large-scale identification and validation of cell states and multicellular communities from bulk, single-cell, and spatially resolved gene expression data. When applied to 12 major cell lineages across 16 types of human carcinoma, EcoTyper identified 69 transcriptionally defined cell states. Most states were specific to neoplastic tissue, ubiquitous across tumor types, and significantly prognostic. By analyzing cell-state co-occurrence patterns, we discovered ten clinically distinct multicellular communities with unexpectedly strong conservation, including three with myeloid and stromal elements linked to adverse survival, one enriched in normal tissue, and two associated with early cancer development. This study elucidates fundamental units of cellular organization in human carcinoma and provides a framework for large-scale profiling of cellular ecosystems in any tissue.

Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer.

Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.

ASICs Mediate Food Responses in an Enteric Serotonergic Neuron that Controls Foraging Behaviors.

Animals must respond to the ingestion of food by generating adaptive behaviors, but the role of gut-brain signaling in behavioral regulation is poorly understood. Here, we identify conserved ion channels in an enteric serotonergic neuron that mediate its responses to food ingestion and decipher how these responses drive changes in foraging behavior. We show that the C. elegans serotonergic neuron NSM acts as an enteric sensory neuron that acutely detects food ingestion. We identify the novel and conserved acid-sensing ion channels (ASICs) DEL-7 and DEL-3 as NSM-enriched channels required for feeding-dependent NSM activity, which in turn drives slow locomotion while animals feed. Point mutations that alter the DEL-7 channel change NSM dynamics and associated behavioral dynamics of the organism. This study provides causal links between food ingestion, molecular and physiological properties of an enteric serotonergic neuron, and adaptive feeding behaviors, yielding a new view of how enteric neurons control behavior.

Glia Accumulate Evidence that Actions Are Futile and Suppress Unsuccessful Behavior.

When a behavior repeatedly fails to achieve its goal, animals often give up and become passive, which can be strategic for preserving energy or regrouping between attempts. It is unknown how the brain identifies behavioral failures and mediates this behavioral-state switch. In larval zebrafish swimming in virtual reality, visual feedback can be withheld so that swim attempts fail to trigger expected visual flow. After tens of seconds of such motor futility, animals became passive for similar durations. Whole-brain calcium imaging revealed noradrenergic neurons that responded specifically to failed swim attempts and radial astrocytes whose calcium levels accumulated with increasing numbers of failed attempts. Using cell ablation and optogenetic or chemogenetic activation, we found that noradrenergic neurons progressively activated brainstem radial astrocytes, which then suppressed swimming. Thus, radial astrocytes perform a computation critical for behavior: they accumulate evidence that current actions are ineffective and consequently drive changes in behavioral states. VIDEO ABSTRACT.

Multi-omics analysis of innate and adaptive responses to BCG vaccination reveals epigenetic cell states that predict trained immunity.

Immune responses are tightly regulated yet highly variable between individuals. To investigate human population variation of trained immunity, we immunized healthy individuals with Bacillus Calmette-Guérin (BCG). This live-attenuated vaccine induces not only an adaptive immune response against tuberculosis but also triggers innate immune activation and memory that are indicative of trained immunity. We established personal immune profiles and chromatin accessibility maps over a 90-day time course of BCG vaccination in 323 individuals. Our analysis uncovered genetic and epigenetic predictors of baseline immunity and immune response. BCG vaccination enhanced the innate immune response specifically in individuals with a dormant immune state at baseline, rather than providing a general boost of innate immunity. This study advances our understanding of BCG's heterologous immune-stimulatory effects and trained immunity in humans. Furthermore, it highlights the value of epigenetic cell states for connecting immune function with genotype and the environment.

Screening for lung cancer: 2023 guideline update from the American Cancer Society.

Lung cancer is the leading cause of mortality and person-years of life lost from cancer among US men and women. Early detection has been shown to be associated with reduced lung cancer mortality. Our objective was to update the American Cancer Society (ACS) 2013 lung cancer screening (LCS) guideline for adults at high risk for lung cancer. The guideline is intended to provide guidance for screening to health care providers and their patients who are at high risk for lung cancer due to a history of smoking. The ACS Guideline Development Group (GDG) utilized a systematic review of the LCS literature commissioned for the US Preventive Services Task Force 2021 LCS recommendation update; a second systematic review of lung cancer risk associated with years since quitting smoking (YSQ); literature published since 2021; two Cancer Intervention and Surveillance Modeling Network-validated lung cancer models to assess the benefits and harms of screening; an epidemiologic and modeling analysis examining the effect of YSQ and aging on lung cancer risk; and an updated analysis of benefit-to-radiation-risk ratios from LCS and follow-up examinations. The GDG also examined disease burden data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms. The GDG judged that the overall evidence was moderate and sufficient to support a strong recommendation for screening individuals who meet the eligibility criteria. LCS in men and women aged 50-80 years is associated with a reduction in lung cancer deaths across a range of study designs, and inferential evidence supports LCS for men and women older than 80 years who are in good health. The ACS recommends annual LCS with low-dose computed tomography for asymptomatic individuals aged 50-80 years who currently smoke or formerly smoked and have a ≥20 pack-year smoking history (strong recommendation, moderate quality of evidence). Before the decision is made to initiate LCS, individuals should engage in a shared decision-making discussion with a qualified health professional. For individuals who formerly smoked, the number of YSQ is not an eligibility criterion to begin or to stop screening. Individuals who currently smoke should receive counseling to quit and be connected to cessation resources. Individuals with comorbid conditions that substantially limit life expectancy should not be screened. These recommendations should be considered by health care providers and adults at high risk for lung cancer in discussions about LCS. If fully implemented, these recommendations have a high likelihood of significantly reducing death and suffering from lung cancer in the United States.

Social determinants of health and US cancer screening interventions: A systematic review.

There remains a need to synthesize linkages between social determinants of health (SDOH) and cancer screening to reduce persistent inequities contributing to the US cancer burden. The authors conducted a systematic review of US-based breast, cervical, colorectal, and lung cancer screening intervention studies to summarize how SDOH have been considered in interventions and relationships between SDOH and screening. Five databases were searched for peer-reviewed research articles published in English between 2010 and 2021. The Covidence software platform was used to screen articles and extract data using a standardized template. Data items included study and intervention characteristics, SDOH intervention components and measures, and screening outcomes. The findings were summarized using descriptive statistics and narratives. The review included 144 studies among diverse population groups. SDOH interventions increased screening rates overall by a median of 8.4 percentage points (interquartile interval, 1.8-18.8 percentage points). The objective of most interventions was to increase community demand (90.3%) and access (84.0%) to screening. SDOH interventions related to health care access and quality were most prevalent (227 unique intervention components). Other SDOH, including educational, social/community, environmental, and economic factors, were less common (90, 52, 21, and zero intervention components, respectively). Studies that included analyses of health policy, access to care, and lower costs yielded the largest proportions of favorable associations with screening outcomes. SDOH were predominantly measured at the individual level. This review describes how SDOH have been considered in the design and evaluation of cancer screening interventions and effect sizes for SDOH interventions. Findings may guide future intervention and implementation research aiming to reduce US screening inequities.

Subconductance states add complexity to Piezo1 gating model.

Piezos are force-gated ion channels that detect and communicate membrane tension to the cell. Recent work from Ullah, Nosyreva, and colleagues characterizes partial channel openings, known as subconductance states, and develops a new gating model of Piezo1 function.

CRISPR Tools for Physiology and Cell State Changes: Potential of Transcriptional Engineering and Epigenome Editing.

Given the large amount of genome-wide data that have been collected during the last decades, a good understanding of how and why cells change during development, homeostasis, and disease might be expected. Unfortunately, the opposite is true; triggers that cause cellular state changes remain elusive, and the underlying molecular mechanisms are poorly understood. Although genes with the potential to influence cell states are known, the historic dependency on methods that manipulate gene expression outside the endogenous chromatin context has prevented us from understanding how cells organize, interpret, and protect cellular programs. Fortunately, recent methodological innovations are now providing options to answer these outstanding questions, by allowing to target and manipulate individual genomic and epigenomic loci. In particular, three experimental approaches are now feasible due to DNA targeting tools, namely, activation and/or repression of master transcription factors in their endogenous chromatin context; targeting transcription factors to endogenous, alternative, or inaccessible sites; and finally, functional manipulation of the chromatin context. In this article, we discuss the molecular basis of DNA targeting tools and review the potential of these new technologies before we summarize how these have already been used for the manipulation of cellular states and hypothesize about future applications.

Early-stage lung cancer is driven by a transitional cell state dependent on a KRAS-ITGA3-SRC axis.

Glycine-12 mutations in the GTPase KRAS (KRASG12) are an initiating event for development of lung adenocarcinoma (LUAD). KRASG12 mutations promote cell-intrinsic rewiring of alveolar type-II progenitor (AT2) cells, but to what extent such changes interplay with lung homeostasis and cell fate pathways is unclear. Here, we generated single-cell RNA-seq (scRNA-seq) profiles from AT2-mesenchyme organoid co-cultures, mice, and stage-IA LUAD patients, identifying conserved regulators of AT2 transcriptional dynamics and defining the impact of KRASG12D mutation with temporal resolution. In AT2WT organoids, we found a transient injury/plasticity state preceding AT2 self-renewal and AT1 differentiation. Early-stage AT2KRAS cells exhibited perturbed gene expression dynamics, most notably retention of the injury/plasticity state. The injury state in AT2KRAS cells of patients, mice, and organoids was distinguishable from AT2WT states via altered receptor expression, including co-expression of ITGA3 and SRC. The combination of clinically relevant KRASG12D and SRC inhibitors impaired AT2KRAS organoid growth. Together, our data show that an injury/plasticity state essential for lung repair is co-opted during AT2 self-renewal and LUAD initiation, suggesting that early-stage LUAD may be susceptible to interventions that target specifically the oncogenic nature of this cell state.

Brain and other central nervous system tumor statistics, 2021.

Brain and other central nervous system (CNS) tumors are among the most fatal cancers and account for substantial morbidity and mortality in the United States. Population-based data from the Central Brain Tumor Registry of the United States (a combined data set of the National Program of Cancer Registries [NPCR] and Surveillance, Epidemiology, and End Results [SEER] registries), NPCR, National Vital Statistics System and SEER program were analyzed to assess the contemporary burden of malignant and nonmalignant brain and other CNS tumors (hereafter brain) by histology, anatomic site, age, sex, and race/ethnicity. Malignant brain tumor incidence rates declined by 0.8% annually from 2008 to 2017 for all ages combined but increased 0.5% to 0.7% per year among children and adolescents. Malignant brain tumor incidence is highest in males and non-Hispanic White individuals, whereas the rates for nonmalignant tumors are highest in females and non-Hispanic Black individuals. Five-year relative survival for all malignant brain tumors combined increased between 1975 to 1977 and 2009 to 2015 from 23% to 36%, with larger gains among younger age groups. Less improvement among older age groups largely reflects a higher burden of glioblastoma, for which there have been few major advances in prevention, early detection, and treatment the past 4 decades. Specifically, 5-year glioblastoma survival only increased from 4% to 7% during the same time period. In addition, important survival disparities by race/ethnicity remain for childhood tumors, with the largest Black-White disparities for diffuse astrocytomas (75% vs 86% for patients diagnosed during 2009-2015) and embryonal tumors (59% vs 67%). Increased resources for the collection and reporting of timely consistent data are critical for advancing research to elucidate the causes of sex, age, and racial/ethnic differences in brain tumor occurrence, especially for rarer subtypes and among understudied populations.

High-Resolution Ribosome Profiling Defines Discrete Ribosome Elongation States and Translational Regulation during Cellular Stress.

Ribosomes undergo substantial conformational changes during translation elongation to accommodate incoming aminoacyl-tRNAs and translocate along the mRNA template. We used multiple elongation inhibitors and chemical probing to define ribosome conformational states corresponding to differently sized ribosome-protected mRNA fragments (RPFs) generated by ribosome profiling. We show, using various genetic and environmental perturbations, that short 20-22 or classical 27-29 nucleotide RPFs correspond to ribosomes with open or occupied ribosomal A sites, respectively. These distinct states of translation elongation are readily discerned by ribosome profiling in all eukaryotes we tested, including fungi, worms, and mammals. This high-resolution ribosome profiling approach reveals mechanisms of translation-elongation arrest during distinct stress conditions. Hyperosmotic stress inhibits translocation through Rck2-dependent eEF2 phosphorylation, whereas oxidative stress traps ribosomes in a pre-translocation state, independent of Rck2-driven eEF2 phosphorylation. These results provide insights and approaches for defining the molecular events that impact translation elongation throughout biology.

Declining Chinese attitudes toward the United States amid COVID-19.

In this paper, we present findings from four separate studies using different data sources and methods to examine Chinese attitudes toward the United States amid the COVID-19 pandemic. The empirical results consistently indicate a marked and significant decline in Chinese attitudes toward the US between late 2019 and the end of 2022. Using a quasi-experimental design and granular survey data that exploit daily variations in public opinion, we offer additional evidence that the decline in Chinese attitudes toward the United States followed a distinct pattern not true for Chinese attitudes toward other countries. Specifically, the rise in Chinese unfavorability toward the United States closely corresponded to the heightened Chinese attention to the pandemic's progression in the United States. These results collectively suggest a causal effect of COVID-19, shedding light on how public health crises, international relations, and media jointly shape the increasing enmity between the two great powers.

Single-cell analysis of treatment-resistant prostate cancer: Implications of cell state changes for cell surface antigen-targeted therapies.

Targeting cell surface molecules using radioligand and antibody-based therapies has yielded considerable success across cancers. However, it remains unclear how the expression of putative lineage markers, particularly cell surface molecules, varies in the process of lineage plasticity, wherein tumor cells alter their identity and acquire new oncogenic properties. A notable example of lineage plasticity is the transformation of prostate adenocarcinoma (PRAD) to neuroendocrine prostate cancer (NEPC)-a growing resistance mechanism that results in the loss of responsiveness to androgen blockade and portends dismal patient survival. To understand how lineage markers vary across the evolution of lineage plasticity in prostate cancer, we applied single-cell analyses to 21 human prostate tumor biopsies and two genetically engineered mouse models, together with tissue microarray analysis on 131 tumor samples. Not only did we observe a higher degree of phenotypic heterogeneity in castrate-resistant PRAD and NEPC than previously anticipated but also found that the expression of molecules targeted therapeutically, namely PSMA, STEAP1, STEAP2, TROP2, CEACAM5, and DLL3, varied within a subset of gene-regulatory networks (GRNs). We also noted that NEPC and small cell lung cancer subtypes shared a set of GRNs, indicative of conserved biologic pathways that may be exploited therapeutically across tumor types. While this extreme level of transcriptional heterogeneity, particularly in cell surface marker expression, may mitigate the durability of clinical responses to current and future antigen-directed therapies, its delineation may yield signatures for patient selection in clinical trials, potentially across distinct cancer types.

Quantum acoustics unravels Planckian resistivity.

Strange metals exhibit universal linear-in-temperature resistivity described by a Planckian scattering rate, the origin of which remains elusive. By employing an approach inspired by quantum optics, we arrive at the coherent state representation of lattice vibrations: quantum acoustics. Utilizing this nonperturbative framework, we demonstrate that lattice vibrations could serve as active drivers in the Planckian resistivity phenomenon, challenging prevailing theories. By treating charge carriers as quantum wave packets negotiating the dynamic acoustic field, we find that a competition ensues between localization and delocalization giving rise to the previously conjectured universal quantum bound of diffusion, [Formula: see text], independent of temperature or any other material parameters. This leads to the enigmatic T-linear resistivity over hundreds of degrees, except at very low temperatures. Quantum diffusion also explains why strange metals have much higher electrical resistivity than typical metals. Our work elucidates the critical role of phonons in Planckian resistivity from a unique perspective and reconsiders their significance in the transport properties of strange metals.

Deportation threat predicts Latino US citizens and noncitizens' psychological distress, 2011 to 2018.

The national context of deportation threat, defined as the federal government's approach to deportation and/or deportation's salience to the US public, fluctuated between 2011 and 2018. US Latinos across citizenship statuses may have experienced growing psychological distress associated with these changes, given their disproportionate personal or proximal vulnerabilities to deportation. Drawing on 8 y of public- and restricted-access data from the National Health Interview Survey (2011 to 2018), this article examines trends in psychological distress among Latinos who are US-born citizens, naturalized citizens, and noncitizens. It then seeks to explain these trends by considering two theoretical pathways through which the national context of deportation threat could distress Latinos: 1) through discrete dramatic societal events that independently signal a change to the country's approach to deportation and/or that render deportation temporarily more salient to the public or 2) through more gradual changes to the country's everyday institutional (i.e., quotidian efforts to detain and deport noncitizens) and social (i.e., deportation's ongoing salience to a concerned public) environment of deportation threat. We find that, though both pathways matter to some degree, there is more consistent evidence that the gradual changes are associated with Latino US citizens and noncitizens' overall experiences of psychological distress. The article highlights how, even absent observable spillover effects of dramatic societal events bearing on deportation threat, the institutional and social environment in which they occur implicates Latinos' well-being.

Uncovering underlying physical principles and driving forces of cell differentiation and reprogramming from single-cell transcriptomics.

Recent advances in single-cell sequencing technology have revolutionized our ability to acquire whole transcriptome data. However, uncovering the underlying transcriptional drivers and nonequilibrium driving forces of cell function directly from these data remains challenging. We address this by learning cell state vector fields from discrete single-cell RNA velocity to quantify the single-cell global nonequilibrium driving forces as landscape and flux. From single-cell data, we quantified the Waddington landscape, showing that optimal paths for differentiation and reprogramming deviate from the naively expected landscape gradient paths and may not pass through landscape saddles at finite fluctuations, challenging conventional transition state estimation of kinetic rate for cell fate decisions due to the presence of the flux. A key insight from our study is that stem/progenitor cells necessitate greater energy dissipation for rapid cell cycles and self-renewal, maintaining pluripotency. We predict optimal developmental pathways and elucidate the nucleation mechanism of cell fate decisions, with transition states as nucleation sites and pioneer genes as nucleation seeds. The concept of loop flux quantifies the contributions of each cycle flux to cell state transitions, facilitating the understanding of cell dynamics and thermodynamic cost, and providing insights into optimizing biological functions. We also infer cell-cell interactions and cell-type-specific gene regulatory networks, encompassing feedback mechanisms and interaction intensities, predicting genetic perturbation effects on cell fate decisions from single-cell omics data. Essentially, our methodology validates the landscape and flux theory, along with its associated quantifications, offering a framework for exploring the physical principles underlying cellular differentiation and reprogramming and broader biological processes through high-throughput single-cell sequencing experiments.