The Hallmarks of Precancer.

Research on precancers, as defined as at-risk tissues and early lesions, is of high significance given the effectiveness of early intervention. We discuss the need for risk stratification to prevent overtreatment, an emphasis on the role of genetic and epigenetic aging when considering risk, and the importance of integrating macroenvironmental risk factors with molecules and cells in lesions and at-risk normal tissues for developing effective intervention and health policy strategies.

Metabolic targeting of cancer associated fibroblasts overcomes T-cell exclusion and chemoresistance in soft-tissue sarcomas.

T cell-based immunotherapies have exhibited promising outcomes in tumor control; however, their efficacy is limited in immune-excluded tumors. Cancer-associated fibroblasts (CAFs) play a pivotal role in shaping the tumor microenvironment and modulating immune infiltration. Despite the identification of distinct CAF subtypes using single-cell RNA-sequencing (scRNA-seq), their functional impact on hindering T-cell infiltration remains unclear, particularly in soft-tissue sarcomas (STS) characterized by low response rates to T cell-based therapies. In this study, we characterize the STS microenvironment using murine models (in female mice) with distinct immune composition by scRNA-seq, and identify a subset of CAFs we termed glycolytic cancer-associated fibroblasts (glyCAF). GlyCAF rely on GLUT1-dependent expression of CXCL16 to impede cytotoxic T-cell infiltration into the tumor parenchyma. Targeting glycolysis decreases T-cell restrictive glyCAF accumulation at the tumor margin, thereby enhancing T-cell infiltration and augmenting the efficacy of chemotherapy. These findings highlight avenues for combinatorial therapeutic interventions in sarcomas and possibly other solid tumors. Further investigations and clinical trials are needed to validate these potential strategies and translate them into clinical practice.

Discoidin Domain Receptor-Driven Gene Signatures as Markers of Patient Response to Anti-PD-L1 Immune Checkpoint Therapy.

BACKGROUND: Anti-programmed cell death 1 (anti-PD-1) and PD ligand 1 (PD-L1) immune checkpoint therapies (ICTs) provided durable responses only in a subset of cancer patients. Thus, biomarkers are needed to predict nonresponders and offer them alternative treatments. We recently implicated discoidin domain receptor tyrosine kinase 2 (DDR2) as a contributor to anti-PD-1 resistance in animal models; therefore, we sought to investigate whether this gene family may provide ICT response prediction. METHODS: We assessed mRNA expression of DDR2 and its family member DDR1. Transcriptome analysis of bladder cancer (BCa) models in which DDR1 and 2 were perturbed was used to derive DDR1- and DDR2-driven signature scores. DDR mRNA expression and gene signature scores were evaluated using BCa-The Cancer Genome Atlas (n = 259) and IMvigor210 (n = 298) datasets, and their relationship to BCa subtypes, pathway enrichment, and immune deconvolution analyses was performed. The potential of DDR-driven signatures to predict ICT response was evaluated and independently validated through a statistical framework in bladder and lung cancer cohorts. All statistical tests were 2-sided. RESULTS: DDR1 and DDR2 showed mutually exclusive gene expression patterns in human tumors. DDR2high BCa exhibited activation of immune pathways and a high immune score, indicative of a T-cell-inflamed phenotype, whereas DDR1high BCa exhibited a non-T-cell-inflamed phenotype. In IMvigor210 cohort, tumors with high DDR1 (hazard ratio [HR] = 1.53, 95% confidence interval [CI] = 1.16 to 2.06; P = .003) or DDR2 (HR = 1.42, 95% CI = 1.01 to 1.92; P = .04) scores had poor overall survival. Of note, DDR2high tumors from IMvigor210 and CheckMate 275 (n = 73) cohorts exhibited poorer overall survival (HR = 1.56, 95% CI = 1.20 to 2.06; P < .001) and progression-free survival (HR = 1.77 95%, CI = 1.05 to 3.00; P = .047), respectively. This result was validated in independent cancer datasets. CONCLUSIONS: These findings implicate DDR1 and DDR2 driven signature scores in predicting ICT response.

Cell death-induced immunogenicity enhances chemoimmunotherapeutic response by converting immune-excluded into T-cell inflamed bladder tumors.

Chemoimmunotherapy has recently failed to demonstrate significant clinical benefit in advanced bladder cancer patients; and the mechanism(s) underlying such suboptimal response remain elusive. To date, most studies have focused on tumor-intrinsic properties that render them "immune-excluded". Here, we explore an alternative, drug-induced mechanism that impedes therapeutic response via disrupting the onset of immunogenic cell death. Using two immune-excluded syngeneic mouse models of muscle-invasive bladder cancer (MIBC), we show that platinum-based chemotherapy diminishes CD8+ T cell tumor infiltration and constraines their antitumoral activity, despite expression of activation markers IFNγ and granzyme B. Mechanistically, chemotherapy induces the release of prostaglandin E2 (PGE2) from dying cancer cells, which is an inhibitory damage-associated molecular pattern (iDAMP) that hinderes dendritic cell maturation. Upon pharmaceutical blockade of PGE2 release, CD8+ T cells become tumoricidal and display an intraepithelial-infiltrating (or inflamed) pattern. This "iDAMP blockade" approach synergizes with chemotherapy and sensitizes bladder tumors towards anti-PD1 immune checkpoint inhibitor therapy. These findings provide a compelling rationale to evaluate this drug combination in future clinical trials.

Toll-Like Receptors Induce Signal-Specific Reprogramming of the Macrophage Lipidome.

Macrophages reprogram their lipid metabolism in response to activation signals. However, a systems-level understanding of how different pro-inflammatory stimuli reshape the macrophage lipidome is lacking. Here, we use complementary "shotgun" and isotope tracer mass spectrometry approaches to define the changes in lipid biosynthesis, import, and composition of macrophages induced by various Toll-like receptors (TLRs) and inflammatory cytokines. "Shotgun" lipidomics data revealed that different TLRs and cytokines induce macrophages to acquire distinct lipidomes, indicating their specificity in reshaping lipid composition. Mechanistic studies showed that differential reprogramming of lipid composition is mediated by the opposing effects of MyD88- and TRIF-interferon-signaling pathways. Finally, we applied these insights to show that perturbing reprogramming of lipid composition can enhance inflammation and promote host defense to bacterial challenge. These studies provide a framework for understanding how inflammatory stimuli reprogram lipid composition of macrophages while providing a knowledge platform to exploit differential lipidomics to influence immunity.

Development and Application of FASA, a Model for Quantifying Fatty Acid Metabolism Using Stable Isotope Labeling.

It is well understood that fatty acids can be synthesized, imported, and modified to meet requisite demands in cells. However, following the movement of fatty acids through the multiplicity of these metabolic steps has remained difficult. To better address this problem, we developed Fatty Acid Source Analysis (FASA), a model that defines the contribution of synthesis, import, and elongation pathways to fatty acid homeostasis in saturated, monounsaturated, and polyunsaturated fatty acid pools. Application of FASA demonstrated that elongation can be a major contributor to cellular fatty acid content and showed that distinct pro-inflammatory stimuli (e.g., Toll-like receptors 2, 3, or 4) specifically reprogram homeostasis of fatty acids by differential utilization of synthetic and elongation pathways in macrophages. In sum, this modeling approach significantly advances our ability to interrogate cellular fatty acid metabolism and provides insight into how cells dynamically reshape their lipidomes in response to metabolic or inflammatory signals.