Embracing cancer complexity: Hallmarks of systemic disease.

The last 50 years have witnessed extraordinary developments in understanding mechanisms of carcinogenesis, synthesized as the hallmarks of cancer. Despite this logical framework, our understanding of the molecular basis of systemic manifestations and the underlying causes of cancer-related death remains incomplete. Looking forward, elucidating how tumors interact with distant organs and how multifaceted environmental and physiological parameters impinge on tumors and their hosts will be crucial for advances in preventing and more effectively treating human cancers. In this perspective, we discuss complexities of cancer as a systemic disease, including tumor initiation and promotion, tumor micro- and immune macro-environments, aging, metabolism and obesity, cancer cachexia, circadian rhythms, nervous system interactions, tumor-related thrombosis, and the microbiome. Model systems incorporating human genetic variation will be essential to decipher the mechanistic basis of these phenomena and unravel gene-environment interactions, providing a modern synthesis of molecular oncology that is primed to prevent cancers and improve patient quality of life and cancer outcomes.

Cachexia: A systemic consequence of progressive, unresolved disease.

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.

Tracking Cancer Evolution Reveals Constrained Routes to Metastases: TRACERx Renal.

Clear-cell renal cell carcinoma (ccRCC) exhibits a broad range of metastatic phenotypes that have not been systematically studied to date. Here, we analyzed 575 primary and 335 metastatic biopsies across 100 patients with metastatic ccRCC, including two cases sampledat post-mortem. Metastatic competence was afforded by chromosome complexity, and we identify 9p loss as a highly selected event driving metastasis and ccRCC-related mortality (p = 0.0014). Distinct patterns of metastatic dissemination were observed, including rapid progression to multiple tissue sites seeded by primary tumors of monoclonal structure. By contrast, we observed attenuated progression in cases characterized by high primary tumor heterogeneity, with metastatic competence acquired gradually and initial progression to solitary metastasis. Finally, we observed early divergence of primitive ancestral clones and protracted latency of up to two decades as a feature of pancreatic metastases.

Genomic-transcriptomic evolution in lung cancer and metastasis.

Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic-transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary-metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis.

Antibodies against endogenous retroviruses promote lung cancer immunotherapy.

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS)1,2. Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive1,2. Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma3. We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response.

Using DNA sequencing data to quantify T cell fraction and therapy response.

The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy1,2. However, measurements of tumour infiltrating lymphocytes (TILs) are limited by a shortage of appropriate data. Whole-exome sequencing (WES) of DNA is frequently performed to calculate tumour mutational burden and identify actionable mutations. Here we develop T cell exome TREC tool (T cell ExTRECT), a method for estimation of T cell fraction from WES samples using a signal from T cell receptor excision circle (TREC) loss during V(D)J recombination of the T cell receptor-α gene (TCRA (also known as TRA)). TCRA T cell fraction correlates with orthogonal TIL estimates and is agnostic to sample type. Blood TCRA T cell fraction is higher in females than in males and correlates with both tumour immune infiltrate and presence of bacterial sequencing reads. Tumour TCRA T cell fraction is prognostic in lung adenocarcinoma. Using a meta-analysis of tumours treated with immunotherapy, we show that tumour TCRA T cell fraction predicts immunotherapy response, providing value beyond measuring tumour mutational burden. Applying T cell ExTRECT to a multi-sample pan-cancer cohort reveals a high diversity of the degree of immune infiltration within tumours. Subclonal loss of 12q24.31-32, encompassing SPPL3, is associated with reduced TCRA T cell fraction. T cell ExTRECT provides a cost-effective technique to characterize immune infiltrate alongside somatic changes.

Pervasive chromosomal instability and karyotype order in tumour evolution.

Chromosomal instability in cancer consists of dynamic changes to the number and structure of chromosomes1,2. The resulting diversity in somatic copy number alterations (SCNAs) may provide the variation necessary for tumour evolution1,3,4. Here we use multi-sample phasing and SCNA analysis of 1,421 samples from 394 tumours across 22 tumour types to show that continuous chromosomal instability results in pervasive SCNA heterogeneity. Parallel evolutionary events, which cause disruption in the same genes (such as BCL9, MCL1, ARNT (also known as HIF1B), TERT and MYC) within separate subclones, were present in 37% of tumours. Most recurrent losses probably occurred before whole-genome doubling, that was found as a clonal event in 49% of tumours. However, loss of heterozygosity at the human leukocyte antigen (HLA) locus and loss of chromosome 8p to a single haploid copy recurred at substantial subclonal frequencies, even in tumours with whole-genome doubling, indicating ongoing karyotype remodelling. Focal amplifications that affected chromosomes 1q21 (which encompasses BCL9, MCL1 and ARNT), 5p15.33 (TERT), 11q13.3 (CCND1), 19q12 (CCNE1) and 8q24.1 (MYC) were frequently subclonal yet appeared to be clonal within single samples. Analysis of an independent series of 1,024 metastatic samples revealed that 13 focal SCNAs were enriched in metastatic samples, including gains in chromosome 8q24.1 (encompassing MYC) in clear cell renal cell carcinoma and chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. Chromosomal instability may enable the continuous selection of SCNAs, which are established as ordered events that often occur in parallel, throughout tumour evolution.

Research autopsy programmes in oncology: shared experience from 14 centres across the world.

While there is a great clinical need to understand the biology of metastatic cancer in order to treat it more effectively, research is hampered by limited sample availability. Research autopsy programmes can crucially advance the field through synchronous, extensive, and high-volume sample collection. However, it remains an underused strategy in translational research. Via an extensive questionnaire, we collected information on the study design, enrolment strategy, study conduct, sample and data management, and challenges and opportunities of research autopsy programmes in oncology worldwide. Fourteen programmes participated in this study. Eight programmes operated 24 h/7 days, resulting in a lower median postmortem interval (time between death and start of the autopsy, 4 h) compared with those operating during working hours (9 h). Most programmes (n = 10) succeeded in collecting all samples within a median of 12 h after death. A large number of tumour sites were sampled during each autopsy (median 15.5 per patient). The median number of samples collected per patient was 58, including different processing methods for tumour samples but also non-tumour tissues and liquid biopsies. Unique biological insights derived from these samples included metastatic progression, treatment resistance, disease heterogeneity, tumour dormancy, interactions with the tumour micro-environment, and tumour representation in liquid biopsies. Tumour patient-derived xenograft (PDX) or organoid (PDO) models were additionally established, allowing for drug discovery and treatment sensitivity assays. Apart from the opportunities and achievements, we also present the challenges related with postmortem sample collections and strategies to overcome them, based on the shared experience of these 14 programmes. Through this work, we hope to increase the transparency of postmortem tissue donation, to encourage and aid the creation of new programmes, and to foster collaborations on these unique sample collections. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Neoantigen-directed immune escape in lung cancer evolution.

The interplay between an evolving cancer and a dynamic immune microenvironment remains unclear. Here we analyse 258 regions from 88 early-stage, untreated non-small-cell lung cancers using RNA sequencing and histopathology-assessed tumour-infiltrating lymphocyte estimates. Immune infiltration varied both between and within tumours, with different mechanisms of neoantigen presentation dysfunction enriched in distinct immune microenvironments. Sparsely infiltrated tumours exhibited a waning of neoantigen editing during tumour evolution, indicative of historical immune editing, or copy-number loss of previously clonal neoantigens. Immune-infiltrated tumour regions exhibited ongoing immunoediting, with either loss of heterozygosity in human leukocyte antigens or depletion of expressed neoantigens. We identified promoter hypermethylation of genes that contain neoantigenic mutations as an epigenetic mechanism of immunoediting. Our results suggest that the immune microenvironment exerts a strong selection pressure in early-stage, untreated non-small-cell lung cancers that produces multiple routes to immune evasion, which are clinically relevant and forecast poor disease-free survival.

Corrigendum: Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

This corrects the article DOI: 10.1038/nature22364.

IFN-γ-dependent interactions between tissue-intrinsic γδ T cells and tissue-infiltrating CD8 T cells limit allergic contact dermatitis.

BACKGROUND: Elicitation of allergic contact dermatitis (ACD), an inflammatory type 4 hypersensitivity disease, induces skin infiltration by polyclonal effector CD8 αß T cells and precursors of tissue-resident memory T (TRM) cells. Because TRM have long-term potential to contribute to body-surface immunoprotection and immunopathology, their local regulation needs a fuller understanding. OBJECTIVE: We sought to investigate how TRM-cell maturation might be influenced by innate-like T cells pre-existing within many epithelia. METHODS: This study examined CD8+ TRM-cell maturation following hapten-induced ACD in wild-type mice and in strains harboring altered compartments of dendritic intraepidermal γδ T cells (DETCs), a prototypic tissue-intrinsic, innate-like T-cell compartment that reportedly regulates ACD, but by no elucidated mechanism. RESULTS: In addition to eliciting CD8 TRM, ACD induced DETC activation and an intimate coregulatory association of the 2 cell types. This depended on DETC sensing IFN-γ produced by CD8 cells and involved programmed death-ligand 1 (PD-L1). Thus, in mice lacking DETC or lacking IFN-γ receptor solely on γδ cells, ACD-elicited CD8 T cells showed enhanced proliferative and effector potentials and reduced motility, collectively associated with exaggerated ACD pathology. Comparable dysregulation was elicited by PD-L1 blockade in vitro, and IFN-γ-regulated PD-L1 expression was a trait of human skin-homing and intraepithelial γδ T cells. CONCLUSIONS: The size and quality of the tissue-infiltrating CD8 T-cell response during ACD can be profoundly regulated by local innate-like T cells responding to IFN-γ and involving PD-L1. Thus, interindividual and tissue-specific variations in tissue-intrinsic lymphocytes may influence responses to allergens and other challenges and may underpin inflammatory pathologies such as those repeatedly observed in γδ T-cell-deficient settings.

Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies.

Large cell neuroendocrine lung carcinoma: consensus statement from The British Thoracic Oncology Group and the Association of Pulmonary Pathologists.

Over the past 10 years, lung cancer clinical and translational research has been characterised by exponential progress, exemplified by the introduction of molecularly targeted therapies, immunotherapy and chemo-immunotherapy combinations to stage III and IV non-small cell lung cancer. Along with squamous and small cell lung cancers, large cell neuroendocrine carcinoma (LCNEC) now represents an area of unmet need, particularly hampered by the lack of an encompassing pathological definition that can facilitate real-world and clinical trial progress. The steps we have proposed in this article represent an iterative and rational path forward towards clinical breakthroughs that can be modelled on success in other lung cancer pathologies.

Transcriptome analysis of IPF fibroblastic foci identifies key pathways involved in fibrogenesis.

INTRODUCTION: Fibroblastic foci represent the cardinal pathogenic lesion in idiopathic pulmonary fibrosis (IPF) and comprise activated fibroblasts and myofibroblasts, the key effector cells responsible for dysregulated extracellular matrix deposition in multiple fibrotic conditions. The aim of this study was to define the major transcriptional programmes involved in fibrogenesis in IPF by profiling unmanipulated myofibroblasts within fibrotic foci in situ by laser capture microdissection. METHODS: The challenges associated with deriving gene calls from low amounts of RNA and the absence of a meaningful comparator cell type were overcome by adopting novel data mining strategies and by using weighted gene co-expression network analysis (WGCNA), as well as an eigengene-based approach to identify transcriptional signatures, which correlate with fibrillar collagen gene expression. RESULTS: WGCNA identified prominent clusters of genes associated with cell cycle, inflammation/differentiation, translation and cytoskeleton/cell adhesion. Collagen eigengene analysis revealed that transforming growth factor ß1 (TGF-ß1), RhoA kinase and the TSC2/RHEB axis formed major signalling clusters associated with collagen gene expression. Functional studies using CRISPR-Cas9 gene-edited cells demonstrated a key role for the TSC2/RHEB axis in regulating TGF-ß1-induced mechanistic target of rapamycin complex 1 activation and collagen I deposition in mesenchymal cells reflecting IPF and other disease settings, including cancer-associated fibroblasts. CONCLUSION: These data provide strong support for the human tissue-based and bioinformatics approaches adopted to identify critical transcriptional nodes associated with the key pathogenic cell responsible for fibrogenesis in situ and further identify the TSC2/RHEB axis as a potential novel target for interfering with excessive matrix deposition in IPF and other fibrotic conditions.

Tracking the Evolution of Non-Small-Cell Lung Cancer.

BACKGROUND: Among patients with non-small-cell lung cancer (NSCLC), data on intratumor heterogeneity and cancer genome evolution have been limited to small retrospective cohorts. We wanted to prospectively investigate intratumor heterogeneity in relation to clinical outcome and to determine the clonal nature of driver events and evolutionary processes in early-stage NSCLC. METHODS: In this prospective cohort study, we performed multiregion whole-exome sequencing on 100 early-stage NSCLC tumors that had been resected before systemic therapy. We sequenced and analyzed 327 tumor regions to define evolutionary histories, obtain a census of clonal and subclonal events, and assess the relationship between intratumor heterogeneity and recurrence-free survival. RESULTS: We observed widespread intratumor heterogeneity for both somatic copy-number alterations and mutations. Driver mutations in EGFR, MET, BRAF, and TP53 were almost always clonal. However, heterogeneous driver alterations that occurred later in evolution were found in more than 75% of the tumors and were common in PIK3CA and NF1 and in genes that are involved in chromatin modification and DNA damage response and repair. Genome doubling and ongoing dynamic chromosomal instability were associated with intratumor heterogeneity and resulted in parallel evolution of driver somatic copy-number alterations, including amplifications in CDK4, FOXA1, and BCL11A. Elevated copy-number heterogeneity was associated with an increased risk of recurrence or death (hazard ratio, 4.9; P=4.4×10-4), which remained significant in multivariate analysis. CONCLUSIONS: Intratumor heterogeneity mediated through chromosome instability was associated with an increased risk of recurrence or death, a finding that supports the potential value of chromosome instability as a prognostic predictor. (Funded by Cancer Research UK and others; TRACERx ClinicalTrials.gov number, NCT01888601 .).

Tracking genomic cancer evolution for precision medicine: the lung TRACERx study.

The importance of intratumour genetic and functional heterogeneity is increasingly recognised as a driver of cancer progression and survival outcome. Understanding how tumour clonal heterogeneity impacts upon therapeutic outcome, however, is still an area of unmet clinical and scientific need. TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy [Rx]), a prospective study of patients with primary non-small cell lung cancer (NSCLC), aims to define the evolutionary trajectories of lung cancer in both space and time through multiregion and longitudinal tumour sampling and genetic analysis. By following cancers from diagnosis to relapse, tracking the evolutionary trajectories of tumours in relation to therapeutic interventions, and determining the impact of clonal heterogeneity on clinical outcomes, TRACERx may help to identify novel therapeutic targets for NSCLC and may also serve as a model applicable to other cancer types.

Implications of intratumour heterogeneity for treatment stratification.

Despite advances in the diagnosis and treatment of cancer, the majority of advanced metastatic solid tumours remain incurable. Differential gene expression, somatic mutational status, tumour-specific genetic signatures and micro-environmental selection pressures within individual tumours have implications for the success of predictive assays to guide therapeutic intervention. In this review we discuss the evidence for genetic and phenotypic heterogeneity and its potential implications for clinical decision making. We highlight areas of research that could be improved in order to better stratify patient treatment. We also discuss the predictive potential of patient-derived models of tumour response, including xenograft and cell line-based systems within the context of intratumour heterogeneity.

Expression of regulators of mitotic fidelity are associated with intercellular heterogeneity and chromosomal instability in primary breast cancer.

Regulators of transition through mitosis such as SURVIVIN and Aurora kinase A (AURKA) have been previously implicated in the initiation of chromosomal instability (CIN), a driver of intratumour heterogeneity. We investigate the relationship between protein expression of these genes and directly quantified CIN, and their prognostic utility in breast cancer. The expression of SURVIVIN and AURKA was determined by immunohistochemistry in a cohort of 426 patients with primary breast cancer. The association between protein expression and histopathological characteristics, clinical outcome and CIN status, as determined by centromeric FISH and defined by modal centromere deviation, was analysed. Significantly poorer clinical outcome was observed in patients with high AURKA expression levels. Expression of SURVIVIN was elevated in ER-negative relative to ER-positive breast cancer. Both AURKA and SURVIVIN increased expression were significantly associated with breast cancer grade. There was a significant association between increased CIN and both increased AURKA and SURVIVIN expression. AURKA gene amplification was also associated with increased CIN. To our knowledge this is the largest study assessing CIN status in parallel with the expression of the mitotic regulators AURKA and SURVIVIN. These data suggest that elevated expression of AURKA and SURVIVIN, together with AURKA gene amplification, are associated with increased CIN in breast cancer, and may be used as a proxy for CIN in breast cancer samples in the absence of more advanced molecular measurements.

Why do patients with cancer die?

Cancer is a major cause of global mortality, both in affluent countries and increasingly in developing nations. Many patients with cancer experience reduced life expectancy and have metastatic disease at the time of death. However, the more precise causes of mortality and patient deterioration before death remain poorly understood. This scarcity of information, particularly the lack of mechanistic insights, presents a challenge for the development of novel treatment strategies to improve the quality of, and potentially extend, life for patients with late-stage cancer. In addition, earlier deployment of existing strategies to prolong quality of life is highly desirable. In this Roadmap, we review the proximal causes of mortality in patients with cancer and discuss current knowledge about the interconnections between mechanisms that contribute to mortality, before finally proposing new and improved avenues for data collection, research and the development of treatment strategies that may improve quality of life for patients.

The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma.

The introduction of the International Association for the Study of Lung Cancer grading system has furthered interest in histopathological grading for risk stratification in lung adenocarcinoma. Complex morphology and high intratumoral heterogeneity present challenges to pathologists, prompting the development of artificial intelligence (AI) methods. Here we developed ANORAK (pyrAmid pooliNg crOss stReam Attention networK), encoding multiresolution inputs with an attention mechanism, to delineate growth patterns from hematoxylin and eosin-stained slides. In 1,372 lung adenocarcinomas across four independent cohorts, AI-based grading was prognostic of disease-free survival, and further assisted pathologists by consistently improving prognostication in stage I tumors. Tumors with discrepant patterns between AI and pathologists had notably higher intratumoral heterogeneity. Furthermore, ANORAK facilitates the morphological and spatial assessment of the acinar pattern, capturing acinus variations with pattern transition. Collectively, our AI method enabled the precision quantification and morphology investigation of growth patterns, reflecting intratumoral histological transitions in lung adenocarcinoma.