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Mitochondria are critical to the governance of metabolism and bioenergetics in cancer cells 1 . The mitochondria form highly organized networks, in which their outer and inner membrane structures define their bioenergetic capacity 2 , 3 . However, in vivo studies delineating the relationship between the structural organization of mitochondrial networks and their bioenergetic activity have been limited. Here we present an in vivo structural and functional analysis of mitochondrial networks and bioenergetic phenotypes in non-small cell lung cancer (NSCLC) using an integrated platform consisting of positron emission tomography imaging, respirometry and three-dimensional scanning block-face electron microscopy. The diverse bioenergetic phenotypes and metabolic dependencies we identified in NSCLC tumours align with distinct structural organization of mitochondrial networks present. Further, we discovered that mitochondrial networks are organized into distinct compartments within tumour cells. In tumours with high rates of oxidative phosphorylation (OXPHOS HI ) and fatty acid oxidation, we identified peri-droplet mitochondrial networks wherein mitochondria contact and surround lipid droplets. By contrast, we discovered that in tumours with low rates of OXPHOS (OXPHOS LO ), high glucose flux regulated perinuclear localization of mitochondria, structural remodelling of cristae and mitochondrial respiratory capacity. Our findings suggest that in NSCLC, mitochondrial networks are compartmentalized into distinct subpopulations that govern the bioenergetic capacity of tumours. A study describing an approach that combines imaging and profiling techniques to structurally and functionally analyse lung cancer in vivo, revealing heterogeneous mitochondrial networks and an association between bioenergetic phenotypes and mitochondrial organization and function.

Understanding the cellular processes that underlie early lung adenocarcinoma (LUAD) development is needed to devise intervention strategies 1 . Here we studied 246,102 single epithelial cells from 16 early-stage LUADs and 47 matched normal lung samples. Epithelial cells comprised diverse normal and cancer cell states, and diversity among cancer cells was strongly linked to LUAD-specific oncogenic drivers. KRAS mutant cancer cells showed distinct transcriptional features, reduced differentiation and low levels of aneuploidy. Non-malignant areas surrounding human LUAD samples were enriched with alveolar intermediate cells that displayed elevated KRT8 expression (termed KRT8 + alveolar intermediate cells (KACs) here), reduced differentiation, increased plasticity and driver KRAS mutations. Expression profiles of KACs were enriched in lung precancer cells and in LUAD cells and signified poor survival. In mice exposed to tobacco carcinogen, KACs emerged before lung tumours and persisted for months after cessation of carcinogen exposure. Moreover, they acquired Kras mutations and conveyed sensitivity to targeted KRAS inhibition in KAC-enriched organoids derived from alveolar type 2 (AT2) cells. Last, lineage-labelling of AT2 cells or KRT8 + cells following carcinogen exposure showed that KACs are possible intermediates in AT2-to-tumour cell transformation. This study provides new insights into epithelial cell states at the root of LUAD development, and such states could harbour potential targets for prevention or intervention. Analyses of single epithelial cells from early-stage lung adenocarcinoma and normal lung identifies a population of intermediate cells that may have an increased likelihood of transforming to tumour cells after injury such as tobacco exposure.

Mitochondria are essential regulators of cellular energy and metabolism, and have a crucial role in sustaining the growth and survival of cancer cells. A central function of mitochondria is the synthesis of ATP by oxidative phosphorylation, known as mitochondrial bioenergetics. Mitochondria maintain oxidative phosphorylation by creating a membrane potential gradient that is generated by the electron transport chain to drive the synthesis of ATP 1 . Mitochondria are essential for tumour initiation and maintaining tumour cell growth in cell culture and xenografts 2 , 3 . However, our understanding of oxidative mitochondrial metabolism in cancer is limited because most studies have been performed in vitro in cell culture models. This highlights a need for in vivo studies to better understand how oxidative metabolism supports tumour growth. Here we measure mitochondrial membrane potential in non-small-cell lung cancer in vivo using a voltage-sensitive, positron emission tomography (PET) radiotracer known as 4-[ 18 F]fluorobenzyl-triphenylphosphonium ( 18 F-BnTP) 4 . By using PET imaging of 18 F-BnTP, we profile mitochondrial membrane potential in autochthonous mouse models of lung cancer, and find distinct functional mitochondrial heterogeneity within subtypes of lung tumours. The use of 18 F-BnTP PET imaging enabled us to functionally profile mitochondrial membrane potential in live tumours. A positron emission tomography imaging tracer is developed to image mitochondrial function in vivo, and application of this tracer to a mouse model of lung cancer identifies distinct functional mitochondrial heterogeneity between tumour cells.

Early cancer detection by cell-free DNA faces multiple challenges: low fraction of tumor cell-free DNA, molecular heterogeneity of cancer, and sample sizes that are not sufficient to reflect diverse patient populations. Here, we develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of the cell-free DNA methylome (with > 12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our approach to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, allowing us to learn new features and expand to other cancer types as training cohorts grow. Early cancer detection by cell-free DNA (cfDNA) is challenged by the low amount of tumour DNA in cfDNA, tumour heterogeneity and the small patient cohorts. Here, the authors develop a method, cfMethyl-Seq, for cost-effective methylome profiling of cfDNA and for detecting and locating cancer.

Bronchial premalignant lesions (PMLs) are precursors of lung squamous cell carcinoma, but have variable outcome, and we lack tools to identify and treat PMLs at risk for progression to cancer. Here we report the identification of four molecular subtypes of PMLs with distinct differences in epithelial and immune processes based on RNA-Seq profiling of endobronchial biopsies from high-risk smokers. The Proliferative subtype is enriched with bronchial dysplasia and exhibits up-regulation of metabolic and cell cycle pathways. A Proliferative subtype-associated gene signature identifies subjects with Proliferative PMLs from normal-appearing uninvolved large airway brushings with high specificity. In progressive/persistent Proliferative lesions expression of interferon signaling and antigen processing/presentation pathways decrease and immunofluorescence indicates a depletion of innate and adaptive immune cells compared with regressive lesions. Molecular biomarkers measured in PMLs or the uninvolved airway can enhance histopathological grading and suggest immunoprevention strategies for intercepting the progression of PMLs to lung cancer. Bronchial premalignant lesions can potentially progress to lung squamous cell carcinoma. Here, the authors profile bronchial biopsies from high-risk smokers by RNA sequencing and identify four molecular subtypes of premalignant lesions and an immune molecular signature that associates with lesion progression.

Cell-free DNA (cfDNA) is attractive for many applications, including detecting cancer, identifying the tissue of origin, and monitoring. A fundamental task underlying these applications is SNV calling from cfDNA, which is hindered by the very low tumor content. Thus sensitive and accurate detection of low-frequency mutations (<5%) remains challenging for existing SNV callers. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of tumor clonal landscape, cfSNV can profile mutations in subclones. In both simulated and real patient data, cfSNV outperforms existing tools in sensitivity while maintaining high precision. cfSNV enhances the clinical utilities of cfDNA by improving mutation detection performance in medium-depth sequencing data, therefore making Whole-Exome Sequencing a viable option. As an example, we demonstrate that the tumor mutation profile from cfDNA WES data can provide an effective biomarker to predict immunotherapy outcomes. It is possible to call single-nucleotide variant (SNV) in cell-free DNA (cfDNA), but the accuracy of detection is often affected by low tumour cfDNA content. Here, the authors develop a method, cfSNV, and show that it can be used even for medium-coverage whole exome sequencing of cfDNA.

Lung cancer is the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for over 85% of all cases. Until recently, chemotherapy – characterized by some benefit but only rare durable responses – was the only treatment option for patients with NSCLC whose tumors lacked targetable mutations. By contrast, immune checkpoint inhibitors have demonstrated distinctly durable responses and represent the advent of a new treatment approach for patients with NSCLC. Three immune checkpoint inhibitors, pembrolizumab, nivolumab and atezolizumab, are now approved for use in first- and/or second-line settings for selected patients with advanced NSCLC, with promising benefit also seen in patients with stage III NSCLC. Additionally, durvalumab following chemoradiation has been approved for use in patients with locally advanced disease. Due to the distinct features of cancer immunotherapy, and rapid progress in the field, clinical guidance is needed on the use of these agents, including appropriate patient selection, sequencing of therapies, response monitoring, adverse event management, and biomarker testing. The Society for Immunotherapy of Cancer (SITC) convened an expert Task Force charged with developing consensus recommendations on these key issues. Following a systematic process as outlined by the National Academy of Medicine, a literature search and panel voting were used to rate the strength of evidence for each recommendation. This consensus statement provides evidence-based recommendations to help clinicians integrate immune checkpoint inhibitors into the treatment plan for patients with NSCLC. This guidance will be updated following relevant advances in the field.

Loss of function of the von Hippel-Lindau (VHL) tumor suppressor gene is a hallmark of clear cell renal cell carcinoma (ccRCC). The importance of heterogeneity in the loss of this tumor suppressor has been under reported. To study the impact of intratumoral VHL heterogeneity observed in human ccRCC, we engineered VHL gene deletion in four RCC models, including a new primary tumor cell line derived from an aggressive metastatic case. The VHL gene-deleted (VHL-KO) cells underwent epithelial-to-mesenchymal transition (EMT) and exhibited increased motility but diminished proliferation and tumorigenicity compared to the parental VHL-expressing (VHL + ) cells. Renal tumors with either VHL + or VHL-KO cells alone exhibit minimal metastatic potential. Combined tumors displayed rampant lung metastases, highlighting a novel cooperative metastatic mechanism. The poorly proliferative VHL-KO cells stimulated the proliferation, EMT, and motility of neighboring VHL + cells. Periostin (POSTN), a soluble protein overexpressed and secreted by VHL non-expressing (VHL − ) cells, promoted metastasis by enhancing the motility of VHL-WT cells and facilitating tumor cell vascular escape. Genetic deletion or antibody blockade of POSTN dramatically suppressed lung metastases in our preclinical models. This work supports a new strategy to halt the progression of ccRCC by disrupting the critical metastatic crosstalk between heterogeneous cell populations within a tumor.

Background Machine learning models in biomedical research are often hindered by demographic imbalances in clinical datasets, leading to biased predictions that disadvantage minority populations. Existing bias-correction methods face limitations in handling the heterogeneity of biomedical data and the complexity of demographic influences. Results We present DeBias , a computational framework for mitigating demographic biases in high-dimensional biomedical datasets. DeBias identifies and removes bias-associated subspaces from the feature space using control samples, enabling global correction of demographic distortions while preserving disease-specific signals. To evaluate its effectiveness, we apply DeBias to cell-free DNA methylation data for cancer detection. DeBias achieves a significant reduction in the number of features exhibiting demographic bias and outperforms existing methods in improving cancer detection performance for minority populations. Performance gains are validated in independent cohorts, highlighting the robustness of the approach. Conclusions DeBias offers an effective and generalizable strategy for correcting demographic biases in biomedical machine learning. It represents a step toward more equitable machine learning models that can deliver reliable and unbiased predictions across diverse patient populations.