CD8 + T cells are central to effective antitumor immunity, yet in cancer, they often undergo progressive transcriptional, epigenetic, and metabolic reprogramming that leads to an exhausted state and limits current immunotherapy. A deeper understanding of the molecular mechanisms that govern CD8 + T cell differentiation and function within the tumor microenvironment is essential to overcome this barrier. This review outlines the current knowledge of the transcriptional and epigenetic programs that shape T cell heterogeneity in cancer and chronic infection, with a focus on the formation and maintenance of exhausted T cell subsets. We highlight how T cell–intrinsic factors such as transcription factors and chromatin regulators and extrinsic factors such as nutrient availability converge to influence T cell fate decisions and function, as well as how these are affected in cancer. Finally, we discuss emerging therapeutic strategies aimed at reprogramming the epigenome to restore T cell function, offering new avenues to enhance the efficacy and durability of cancer immunotherapy.

Cancer dormancy refers to an asymptomatic stage in cancer progression that contains residual disease. Cancer cells can disseminate from early tumors even before they are detectable, from advanced tumors, and from other metastases. Thus, cancer dormancy is a collective phenomenon, composed of single dormant cells that stopped dividing, tumor mass dormancy where cell proliferation is balanced by cell death, and active micrometastases. Dormancy evolves with complex spatiotemporal dynamics across length scales (from cell-intrinsic to cell-extrinsic interactions and microenvironmental regulation up to the body-wide systemic level) and across timescales (from single dormant cells to dormant tumor masses and active micrometastases), each responding differently to fluctuating microenvironments. Here we review biological in vivo and clinical observations of breast cancer dormancy across scales in length and time. Next, we outline 3D bioengineered models in which these different spatial and temporal scales are considered. Finally, we discuss challenges and opportunities of incorporating patient-derived cells. Collective cell behavior is an important aspect in cancer progression and, as such, modeling dormancy across scales in length and time could open new avenues to help us understand and predict the transition to active metastatic growth.

The Tracking Cancer Evolution Through Therapy (TRACERx) program represents the most comprehensive effort to characterize tumor evolution in real time. Through longitudinal, multiregion, and multiomic profiling of tumors—and particularly of non-small-cell lung cancer and clear cell renal cell carcinoma—TRACERx has illuminated the dynamic interplay between genetic, nongenetic, and (micro)environmental factors that drive cancer progression, immune evasion, and therapeutic resistance. A central insight from TRACERx has been that not all tumor evolution is genomic: Transcriptomic diversity, epigenetic alterations, RNA editing, and changes in cell–cell interactions also drive adaptation. Methodological innovations—including tumor-informed and ultrasensitive circulating tumor DNA assays, representative sequencing, and integrative immune–genomic analyses—have yielded biomarkers resistant to sampling bias and/or predictive of recurrence, metastasis, and treatment response. By demonstrating that intratumor heterogeneity is a key determinant of clinical outcome and revealing its molecular, transcriptional, and ecosystem-level drivers, TRACERx has established a framework for linking evolutionary dynamics to patient care. As both a scientific framework and a clinical paradigm, TRACERx demonstrates how adaptive, iterative research can refine evolutionary models, improve patient risk stratification, and inspire next-generation cancer evolution studies across malignancies.

The concept of targeted delivery of anticancer agents using tumor-selective antibodies led to the evolution of antibody–drug conjugates (ADCs). Early efforts using traditional chemotherapy agents as ADC payloads were unsuccessful. The selectivity of antibodies was then leveraged to deliver potent cytotoxic agents that could not be administered systemically. The first two decades of exploration and approvals were with ADCs comprised of payloads that induce DNA damage (calicheamicins) or disrupt microtubule function (auristatins, maytansinoids) for treatment of both hematologic and solid tumor malignancies. More recently, ADCs with topoisomerase 1 inhibitor payloads have been successful for treating breast cancer and other solid tumors. Because ADCs show more toxicities than first anticipated, different approaches are under exploration for optimization of the antibody, linker, and drug components, with the goal of maintaining or increasing clinical activity while reducing associated toxicities. This review covers the history of ADC development, currently approved ADCs, and future efforts to improve ADC properties.

The 1982 discovery of mutationally activated RAS genes in human cancers launched a decades-long search for anti-RAS therapies for cancer treatment. Despite the repeated emergence of new knowledge that initiated fresh directions for drug discovery, strategy after strategy culminated in disappointment. At last, the 2013 discovery of a druggable pocket in RAS renewed efforts to directly target RAS and led, only 8 short years later, to the first clinically effective anti-RAS drug. Approved to treat one KRAS mutant (glycine-12-cysteine) in one cancer (non-small-cell lung cancer), this first step created new hope that the RAS-driven cancer dragon could be slayed. Here, we revisit past efforts to drug RAS and discuss important lessons learned from each misstep and unexpected finding, provide a snapshot of the current state of the art in RAS drug discovery, and describe important challenges ahead as the field seeks to build on recent successes and advance more clinically effective therapies.

Imaging biological samples in three dimensions across scales is essential for capturing the complex spatial relationships that govern cancer initiation, invasion, and therapeutic response. As biological inquiry shifts from isolated molecular measurements toward spatially contextualized, multiomic profiling, new strategies have emerged to reconstruct tissue architecture at the whole-organ scale and subcellular resolution. These advances offer more anatomically faithful representations of tissue organization and open doors to integrating morphology with deep multiomic profiling in spatially resolved formats. As a result, we are improving our understanding of inter- and intratumoral heterogeneity and the key role of rare events and minority cell populations in tumor progression. The primary techniques used for 3D imaging of tumors include intact tissue imaging for targeted visualization of biological processes and serial sectioning for integration of diverse, multiomic platforms. In this review, we survey the major technologies used to image tumors in three dimensions, highlighting key methodologies, trade-offs, and recent innovations that make these approaches increasingly central to modern cancer research.

The human cancer genome contains a substantial proportion of nonconserved regions that are transcribed into long noncoding RNAs (lncRNAs) and hosted in areas recurrently implicated in cancer. Due to its high responsiveness to extracellular cues, the aberrant lncRNA transcriptome represents a major source of molecular innovation for cancer cells, which are subjected to intense evolutionary pressure during progression and therapy resistance. As such, lncRNAs contribute to the aberrant rewiring of the molecular networks in cancer cells by functioning as molecular sponges and scaffolds, modulating the activity and localization of other biomolecules. This largely untapped reservoir of regulatory elements holds significant potential for addressing the current clinical challenges of cancer progression and therapy resistance. This review synthesizes current insights into the molecular strategies by which lncRNAs subvert homeostatic regulation across diverse cellular compartments and within the extracellular milieu. Further, it explores their multifaceted contributions to cancer therapy resistance, underscoring their emerging prominence as both actionable therapeutic targets and informative biomarkers.

Mitochondrial oxidative phosphorylation (OXPHOS) is an ancient metabolic process that is increasingly recognized as an important player in cancer onset, progression, and treatment resistance. In this review, we highlight the diverse biological roles of OXPHOS beyond ATP synthesis, discuss ways in which these roles interface with tumorigenesis, and consider methods to measure and manipulate OXPHOS in cancer studies. Instead of the traditional view of OXPHOS as a linear pathway with a single, defined output (i.e., ATP), we propose a more granular model of OXPHOS as a collection of interrelated functional modules that are coupled to various extents in a context-dependent manner. As a case study, we apply this modular framework to examine links between OXPHOS function and cancer metastasis. This conceptual model of OXPHOS function will support ongoing work to dissect the complex—but ultimately understandable—contributions of OXPHOS to cancer phenotypes.

Genome editing technologies have given us the ability to manipulate a genome with unprecedented accuracy. In cancer research, these technologies have enabled precise cancer modeling in cells and in vivo and facilitated systematic efforts to identify cancer drivers and dependencies. This review examines the current landscape of genome editing technologies, with an emphasis on next-generation methods to engineer complex nucleotide and chromosomal alterations. We highlight key examples that illustrate how these technologies have provided fundamental insights into this disease, and we discuss new approaches that integrate genome editing with multiomic methods. Finally, we discuss recent efforts to translate these technologies into the clinic.

The field of cancer glycobiology aims to understand how aberrant glycosylation contributes to the development of cancer. While the significance of glycosylation to normal and pathological cellular functions is widely appreciated, the comprehensive identification of specific aberrant glycan epitopes in cancer and mechanistic understanding of their impact remain limited. In this review, we begin with a brief general background on glycosylation to orient cancer researchers to the field. We next focus on research showcasing the roles that glycosylation plays in cancer, with an emphasis on studies that draw evidence from both clinical samples and mouse models. Finally, we conclude with a brief discussion of the clinical implications of glycosylation research toward improving the diagnosis and treatment of cancer.