CONIPHER: a computational framework for scalable phylogenetic reconstruction with error correction

Intratumor heterogeneity provides the fuel for the evolution and selection of subclonal tumor cell populations. However, accurate inference of tumor subclonal architecture and reconstruction of tumor evolutionary histories from bulk DNA sequencing data remains challenging. Frequently, sequencing and alignment artifacts are not fully filtered out from cancer somatic mutations, and errors in the identification of copy number alterations or complex evolutionary events (e.g., mutation losses) affect the estimated cellular prevalence of mutations. Together, such errors propagate into the analysis of mutation clustering and phylogenetic reconstruction. In this Protocol, we present a new computational framework, CONIPHER (COrrecting Noise In PHylogenetic Evaluation and Reconstruction), that accurately infers subclonal structure and phylogenetic relationships from multisample tumor sequencing, accounting for both copy number alterations and mutation errors. CONIPHER has been used to reconstruct subclonal architecture and tumor phylogeny from multisample tumors with high-depth whole-exome sequencing from the TRACERx421 dataset, as well as matched primary-metastatic cases. CONIPHER outperforms similar methods on simulated datasets, and in particular scales to a large number of tumor samples and clones, while completing in under 1.5 h on average. CONIPHER enables automated phylogenetic analysis that can be effectively applied to large sequencing datasets generated with different technologies. CONIPHER can be run with a basic knowledge of bioinformatics and R and bash scripting languages.

Abstract 4277: Measuring proliferation rates of distinct tumour clones using single-cell DNA sequencing

Background:

Tumour proliferation rate is a key phenotypic feature of cancer, with higher rates linked to poorer clinical outcomes. Thus far, proliferation rates have been measured using pathological or experimental techniques on bulk tumour samples. However, while tumours are heterogeneous compositions of distinct clones with varying levels of fitness, measuring the proliferation of individual clones has not been possible to date. We hypothesise that enabling the identification of the most proliferative clones would reveal genomic hallmarks of aggressive clones, or the prediction of their potential phenotype, e.g., metastatic potential.

Methods:

We have developed SPRINTER (Single-cell Proliferation Rate Inference in Neoplasms Through Evolutionary Routes), a novel computational method to measure proliferation rates in individual tumour clones using single-cell whole-genome DNA sequencing. To assess the accuracy and power of SPRINTER, we have also developed an experimental approach to DNA sequence >18,000 single cells, accurately separated in different DNA-replication phases. We have sequenced and applied SPRINTER to >10,000 non-small cell lung cancer cells from longitudinal and metastatic tumour samples within the TRACERx study and PEACE autopsy programme. We have further analysed published data from >10,000 breast cancer cells.

Results:

We demonstrate that SPRINTER can accurately identify subpopulations of cells with different proliferation rates using relatively small numbers of cells, in contrast to previous preliminary approaches. While our estimates are concordant with previous bulk experimental studies (5-40%), we importantly have identified clonal heterogeneity in proliferation rates. Using bulk analysis, we have identified patterns of dissemination of tumour clones in non-small cell lung cancer. Integrating this with single-cell data, our results indicate that more widely disseminating tumour clones have higher proliferation rates, suggesting a link between proliferation and dissemination potential. We additionally find that clones are more proliferative in the metastatic versus the primary setting. Furthermore, we have identified high proliferation clones that may have a selective advantage in a breast tumour, and have inferred that they likely arose recently in cancer evolution.

Conclusions:

We have developed a novel method that enables accurate identification of proliferation rates of individual tumour clones using single-cell DNA sequencing data, allowing the investigation of genomic hallmarks in highly proliferative clones that might lead to higher fitness.

Citation Format: Olivia Lucas, Sophie Ward, Rija Zaidi, Mark Hill, Emilia Lim, Haoran Zhai, Abigail Bunkum, Sonya Hessey, Michelle Dietzen, Andrew Rowan, Cristina Naceur-Lombardelli, Nnenna Kanu, Mariam Jamal-Hanjani, Charles Swanton, Simone Zaccaria. Measuring proliferation rates of distinct tumour clones using single-cell DNA sequencing. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4277.

The evolution of lung cancer and impact of subclonal selection in TRACERx

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource.

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. 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.