Thomas B. K. Watkins

Neoantigen-targeted T-cell therapies require invasive tumor biopsies to identify neoantigens and reactive T cells, limiting their applicability and potentially underestimating tumor heterogeneity. We propose a novel strategy relying solely on peripheral blood to identify nonsynonymous mutations via cell-free DNA whole-exome sequencing and isolate neoantigen-specific CD4+ and CD8+ T cells based on PD-1 and CD39 coexpression. Our method identified most neoantigens and increased the number of T-cell reactivities detected by standard biopsy-based techniques in an initial cohort of eight patients with metastatic cancer. Critically, our approach uncovered additional neoantigens missed by tumor biopsy analysis, highlighting the potential for broader neoantigen targeting using liquid biopsies. Analysis of a cohort of 69 patients with metastatic cancer revealed that approximately half could be eligible for our blood-only approach. This proof-of-concept study demonstrates the potential of using blood as a surrogate or complement for tumor biopsies to develop neoantigen-reactive T-cell therapies against a broader spectrum of neoantigens. Significance: This study establishes a blood-based strategy for identifying neoantigens and reactive T cells. By integrating ctDNA exome sequencing with phenotypic selection of circulating T cells, it captures tumor heterogeneity and the systemic antitumor T-cell response, enabling personalized immunotherapy development without tumor biopsies, expanding the accessibility of neoantigen-targeted treatments.

Summary of key differences between ecDNA and eccDNA

Focal amplifications of oncogenes are important cancer drivers. They can occur on chromosomes or in the context of circular extrachromosomal DNA (ecDNA). Many key features of ecDNAs were described in the 1960s to 1980s, including their “unstable” nature and their ability to confer drug resistance. With the benefit of new technologies, our understanding of ecDNAs has advanced dramatically in the last decade, both in breadth and in depth, including the remarkable discovery that ecDNAs are present in 17% of all cancers and are associated with worse patient outcomes. In this study, we present a guide to ecDNA tools and biology.Significance:Focal amplifications on ecDNAs are commonly found in cancer and are associated with poor patient outcomes and distinct biology. In this review, we provide a guide to ecDNA biology and available tools as well as our perspective on this rapidly evolving field.

Focal amplifications of oncogenes are important cancer drivers. They can occur on chromosomes or in the context of circular extrachromosomal DNA (ecDNA). Many key features of ecDNAs were described in the 1960s to 1980s, including their “unstable” nature and their ability to confer drug resistance. With the benefit of new technologies, our understanding of ecDNAs has advanced dramatically in the last decade, both in breadth and in depth, including the remarkable discovery that ecDNAs are present in 17% of all cancers and are associated with worse patient outcomes. In this study, we present a guide to ecDNA tools and biology. Significance: Focal amplifications on ecDNAs are commonly found in cancer and are associated with poor patient outcomes and distinct biology. In this review, we provide a guide to ecDNA biology and available tools as well as our perspective on this rapidly evolving field.

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

Most computational methods that infer somatic copy number alterations (SCNAs) from bulk sequencing of DNA analyse tumour samples individually. However, the sequencing of multiple tumour samples from a patient’s disease is an increasingly common practice. We introduce Refphase, an algorithm that leverages this multi-sampling approach to infer haplotype-specific copy numbers through multi-sample reference phasing. We demonstrate Refphase’s ability to infer haplotype-specific SCNAs and characterise their intra-tumour heterogeneity, to uncover previously undetected allelic imbalance in low purity samples, and to identify parallel evolution in the context of whole genome doubling in a pan-cancer cohort of 336 samples from 99 tumours.

A large-scale meta-analysis of over 1000 CPI (immune checkpoint blockade) treated patients across multiple cancer types broadly categorised biomarkers into four categories: sources of antigen leading to T-cell responses, host-derived factors, immune evasion and infiltration mechanisms. Our analyses established tumour mutation burden (TMB) as the strongest predictor of CPI response, alongside clonal TMB and CXCL9 expression. However, over half of the patients in our cohort who responded to CPI treatment did not have high-TMB and showed no evidence of oncogenic viral infections, hence suggesting alternative sources of antigen could be driving the immune response. As well as this, data from the CPI1000 cohort suggested that the biomarkers identified in an extensive systematic review only accounted for ~60% of the variance in CPI response, promoting the search for non-classical sources of antigen. Extending the cohort to encompass 2500+ patients, using available genomic and transcriptomic data from checkpoint inhibitor trials and industry partners, the previously published multivariate predictor will be further validated in a larger patient cohort inclusive of more cancer types. The CPI1000 cohort utilised primarily whole exome-sequencing therefore, had limited ability to discern non-coding sources of tumour antigen and cell-type specific predictors of response. The CPI2500+ cohort will incorporate several additional cohorts as well as single-cell and T-cell reactivity data. The raw data will be harmonised across studies and processed using a robust bioinformatics pipeline. As well as this, alternative (non-classical) sources of tumour specific antigen will be studied. Alternative sources of antigen can originate from a diverse range of biological processes including retained introns, stop codon loss mutations and cancer associated bacterial/viral epitopes. Data from this exploratory analysis will be coupled with peptide reactivity assays from local UCL patient TIL (tumour infiltrating lymphocyte) and PMBC (peripheral blood mononuclear cells) samples to validate immunogenicity. Current analysis has identified a novel subgroup of CPI-responders with low-TMB who have significantly higher rates of microbial diversity, consistent with a diverse tumour microbiome providing a source of immunogenic antigens in the absence of high-TMB. Here we will present insights from CPI2500+ and highlight the importance of emerging non-classical sources of tumour specific antigen. Citation Format: Krupa Thakkar, Danwen Qian, Hongui Cha, Thomas B. Watkins, Charles Swanton, Kevin Litchfield. Non-classical sources of tumour specific antigen in checkpoint inhibitor response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 643.

Introduction: Cancer cachexia (CC) is a major contributor to morbidity and mortality in patients with non-small cell lung cancer (NSCLC). It is characterized by loss of skeletal muscle (SM) tissue with or without adipose tissue loss. This analysis reports on the characteristics and outcomes of patients recruited into the prospective TRACERx study, who presented with or subsequently developed features of CC during follow-up. Approach: Using longitudinal CT imaging, total, subcutaneous and visceral adipose tissue (TAT, SAT, VAT) and SM volumes were manually quantified at the 3rd lumbar vertebrae level. Body weight was measured every 3-6 months and grouped according to BMI-adjusted weight loss grades. Multi-region primary tumour tissue was collected at the time of surgical resection and subjected to whole exome and RNA sequencing. Results: Patients in the TRACERx 421 cohort who presented with low SAT volume at diagnosis, represented by the lower 20% percentile of the cohort, had significantly shorter lung-cancer specific survival (LCSS) and overall survival (OS) compared with patients in the 80% percentile (3-y LCSS 61% vs 81%, p<0.001; 3-y OS 57% vs 69%, p=0.02). Patients presenting with low VAT had a significantly shorter LCSS (3-y-LCSS 66% vs 79%, p=0.01), but not OS (3-y OS 60% vs 69%). Low SM volume was not associated with LCSS or OS. However, loss of SM volume of ≥20% between diagnosis and disease relapse was associated with significantly reduced LCSS and OS (3-y LCSS 30% vs 49%, p=0.02; 3-y OS 26% vs 45%, p=0.03). Based on a multivariable model, low SAT volume at diagnosis and SM loss were independent prognostic factors for LCSS, but not OS. In addition, BMI-adjusted weight loss was associated with shorter OS and LCSS (3-y OS 7% for patients with weight loss grade 4 vs 54% in patients with stable weight, p<0.001 [LCSS 8% vs 61%, p20% or weight loss grade 4, demonstrated distinct copy number alteration and differential gene expression profiles. Conclusion: In patients with early-stage NSCLC, both altered body composition and weight loss in keeping with CC was associated with poor survival outcomes. In particular, low SAT volume at diagnosis and loss of SM between diagnosis and relapse were independent prognostic factors for LCSS. Ongoing analyses in TRACERx will continue to investigate the potential tumour-intrinsic mediators of CC. Citation Format: Othman Al-Sawaf, Marcin Skrzypski, Jakob Weiss, Takahiro Karasaki, Nicolai Juul Birkbak, Francisco Zambrana, Alexander Frankell, Thomas B. Watkins, Carlos Martinez Ruiz, Selvaraju Veeriah, Cristina Naceur-Lombardelli, TRACERx Consortium, Nicholas McGranahan, Hugo Aerts, Charles Swanton, Mariam Jamal-Hanjani. Features of cancer cachexia in non-small cell lung cancer: Insights from the prospective TRACERx study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5818.