Metastatic disease is responsible for the majority of cancer-related deaths
. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively ...recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy
. 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 study
. 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.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy
. 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.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
APOBEC3 enzymes are cytosine deaminases implicated in cancer. Precisely when
expression is induced during cancer development remains to be defined. Here we show that specific
genes are upregulated in ...breast ductal carcinoma
, and in preinvasive lung cancer lesions coincident with cellular proliferation. We observe evidence of APOBEC3-mediated subclonal mutagenesis propagated from TRACERx preinvasive to invasive non-small cell lung cancer (NSCLC) lesions. We find that APOBEC3B exacerbates DNA replication stress and chromosomal instability through incomplete replication of genomic DNA, manifested by accumulation of mitotic ultrafine bridges and 53BP1 nuclear bodies in the G
phase of the cell cycle. Analysis of TRACERx NSCLC clinical samples and mouse lung cancer models revealed
expression driving replication stress and chromosome missegregation. We propose that APOBEC3 is functionally implicated in the onset of chromosomal instability and somatic mutational heterogeneity in preinvasive disease, providing fuel for selection early in cancer evolution. SIGNIFICANCE: This study reveals the dynamics and drivers of
gene expression in preinvasive disease and the exacerbation of cellular diversity by APOBEC3B through DNA replication stress to promote chromosomal instability early in cancer evolution.
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Lung adenocarcinomas (LUADs) display a broad histological spectrum from low-grade lepidic tumors through to mid-grade acinar and papillary and high-grade solid, cribriform and micropapillary tumors. ...How morphology reflects tumor evolution and disease progression is poorly understood. Whole-exome sequencing data generated from 805 primary tumor regions and 121 paired metastatic samples across 248 LUADs from the TRACERx 421 cohort, together with RNA-sequencing data from 463 primary tumor regions, were integrated with detailed whole-tumor and regional histopathological analysis. Tumors with predominantly high-grade patterns showed increased chromosomal complexity, with higher burden of loss of heterozygosity and subclonal somatic copy number alterations. Individual regions in predominantly high-grade pattern tumors exhibited higher proliferation and lower clonal diversity, potentially reflecting large recent subclonal expansions. Co-occurrence of truncal loss of chromosomes 3p and 3q was enriched in predominantly low-/mid-grade tumors, while purely undifferentiated solid-pattern tumors had a higher frequency of truncal arm or focal 3q gains and SMARCA4 gene alterations compared with mixed-pattern tumors with a solid component, suggesting distinct evolutionary trajectories. Clonal evolution analysis revealed that tumors tend to evolve toward higher-grade patterns. The presence of micropapillary pattern and 'tumor spread through air spaces' were associated with intrathoracic recurrence, in contrast to the presence of solid/cribriform patterns, necrosis and preoperative circulating tumor DNA detection, which were associated with extra-thoracic recurrence. These data provide insights into the relationship between LUAD morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
Cancer-associated cachexia (CAC) is a major contributor to morbidity and mortality in individuals with non-small cell lung cancer. Key features of CAC include alterations in body composition and body ...weight. Here, we explore the association between body composition and body weight with survival and delineate potential biological processes and mediators that contribute to the development of CAC. Computed tomography-based body composition analysis of 651 individuals in the TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study suggested that individuals in the bottom 20th percentile of the distribution of skeletal muscle or adipose tissue area at the time of lung cancer diagnosis, had significantly shorter lung cancer-specific survival and overall survival. This finding was validated in 420 individuals in the independent Boston Lung Cancer Study. Individuals classified as having developed CAC according to one or more features at relapse encompassing loss of adipose or muscle tissue, or body mass index-adjusted weight loss were found to have distinct tumor genomic and transcriptomic profiles compared with individuals who did not develop such features. Primary non-small cell lung cancers from individuals who developed CAC were characterized by enrichment of inflammatory signaling and epithelial-mesenchymal transitional pathways, and differentially expressed genes upregulated in these tumors included cancer-testis antigen MAGEA6 and matrix metalloproteinases, such as ADAMTS3. In an exploratory proteomic analysis of circulating putative mediators of cachexia performed in a subset of 110 individuals from TRACERx, a significant association between circulating GDF15 and loss of body weight, skeletal muscle and adipose tissue was identified at relapse, supporting the potential therapeutic relevance of targeting GDF15 in the management of CAC.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
B-cell non-Hodgkin lymphomas (NHLs) are lymphoproliferative disorders that can arise at different stages of B-cell development. Even though molecular classification of NHL has allowed for more ...accurate recognition of distinct aggressive lymphoma subtypes, many patients still fail to respond to standard therapy. As such, there is a need to identify biomarkers and therapeutic targets that can lead to more specific treatments for each NHL patient's disease. MicroRNAs (miRNAs) are small, 17–25 nt RNA molecules that regulate gene expression at the posttranscriptional level. miRNA expression and function is often coordinately dysregulated in NHL, and consequently results in each NHL disease type harboring a distinct miRNA expression signature. miRNA dysregulation may be a consequence of several mechanisms, ranging from dysregulation of the DNA sequences encoding the miRNA to transcriptional regulation of miRNA loci, to dysregulation of the miRNA biogenesis pathway or dysregulation of messenger RNA (mRNA) targets. This coordinated dysregulation of miRNA expression systematically results in the activation of several oncogenic pathways, and consequently the reprogramming of B-cell NHL transcriptomes. The widespread dysregulation of miRNAs suggests that miRNAs may be used as a diagnostic and prognostic tool, and also as actionable drug targets. In this review, we summarize the miRNA profiles of the most common B-cell NHLs, discuss the causes and consequences of miRNA dysregulation, and consider the prospects of miRNA-based biomarkers and therapeutic targets in NHL.
Patient-derived xenograft (PDX) models are widely used in cancer research. To investigate the genomic fidelity of non-small cell lung cancer PDX models, we established 48 PDX models from 22 patients ...enrolled in the TRACERx study. Multi-region tumor sampling increased successful PDX engraftment and most models were histologically similar to their parent tumor. Whole-exome sequencing enabled comparison of tumors and PDX models and we provide an adapted mouse reference genome for improved removal of NOD scid gamma (NSG) mouse-derived reads from sequencing data. PDX model establishment caused a genomic bottleneck, with models often representing a single tumor subclone. While distinct tumor subclones were represented in independent models from the same tumor, individual PDX models did not fully recapitulate intratumor heterogeneity. On-going genomic evolution in mice contributed modestly to the genomic distance between tumors and PDX models. Our study highlights the importance of considering primary tumor heterogeneity when using PDX models and emphasizes the benefit of comprehensive tumor sampling.
Tumour mutational burden (TMB) predicts immunotherapy outcome in non-small cell lung cancer (NSCLC), consistent with immune recognition of tumour neoantigens. However, persistent antigen exposure is ...detrimental for T cell function. How TMB affects CD4 and CD8 T cell differentiation in untreated tumours, and whether this affects patient outcomes is unknown. Here we paired high-dimensional flow cytometry, exome, single-cell and bulk RNA sequencing from patients with resected, untreated NSCLC to examine these relationships. TMB was associated with compartment-wide T cell differentiation skewing, characterized by loss of TCF7-expressing progenitor-like CD4 T cells, and an increased abundance of dysfunctional CD8 and CD4 T cell subsets, with significant phenotypic and transcriptional similarity to neoantigen-reactive CD8 T cells. A gene signature of redistribution from progenitor-like to dysfunctional states associated with poor survival in lung and other cancer cohorts. Single-cell characterization of these populations informs potential strategies for therapeutic manipulation in NSCLC.
Abstract
At the point of cancer diagnosis, molecular biomarkers aim to stratify patients into precise disease subtypes predictive of outcome independent of standard clinical parameters such as tumour ...stage. Although prognostic gene expression signatures have been derived for many cancer types, seldom have they been shown to improve therapeutic decision making, limiting their clinical use. While intra-tumour transcriptomic heterogeneity (RNA-ITH) has been shown to bias existing biomarkers, efforts to control for this biological parameter have not been considered in biomarker development. Here, we analyse multi-region RNA-seq and whole-exome data for 156 tumour regions from 48 TRACERx patients to explore RNA-ITH in NSCLC. We show that chromosomal instability is a major driver of RNA-ITH, through the generation of heterogeneous copy number events within tumours, and that existing prognostic gene expression signatures are vulnerable to sampling bias. To address this issue, we develop the Outcome Risk Associated Clonal Lung Expression (ORACLE) assay, comprised of genes expressed homogeneously within individual tumours but heterogeneously between patients. These genes are enriched in modules associated with cell proliferation, such as mitosis and nucleosome assembly, that are often selected for through copy number gain events occurring early in tumour evolution. Our approach to identify “clonal” transcriptomic biomarkers in NSCLC overcomes tumour sampling bias, improves survival risk forecasting over current clinicopathological risk factors, and may be generalised to other cancer types, whilst revealing the early evolutionary selection of high risk DNA copy number events driving poor clinical outcome.
Citation Format: Dhruva Biswas, Nicolai J. Birkbak, Rachel Rosenthal, Crispin T. Hiley, Emilia L. Lim, Krisztian Papp, Marcin Krzystanek, Dijana Djureinovic, Yin Wu, David A. Moore, Marcin Skrypski, Christopher Abbosh, Maise Al Bakir, Thomas B. Watkins, Selvaraju Veeriah, Gareth A. Wilson, Mariam Jamal-Hanjani, Arul M. Chinnaiyan, Patrick Micke, Jiri Bartek, Istvan Csabai, Zoltan Szallasi, Javier Herrero, Nicholas McGranahan, Charles Swanton. A clonal expression biomarker improves prognostic accuracy: TRACERx lung abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2678.
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