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 .).

SummaryThe early detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a tumour-specific phylogenetic approach to ctDNA profiling in the first 100 TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies

SummaryImmune evasion is a hallmark of cancer. Losing the ability to present neoantigens through human leukocyte antigen (HLA) loss may facilitate immune evasion. However, the polymorphic nature of the locus has precluded accurate HLA copy-number analysis. Here, we present loss of heterozygosity in human leukocyte antigen (LOHHLA), a computational tool to determine HLA allele-specific copy number from sequencing data. Using LOHHLA, we find that HLA LOH occurs in 40% of non-small-cell lung cancers (NSCLCs) and is associated with a high subclonal neoantigen burden, APOBEC-mediated mutagenesis, upregulation of cytolytic activity, and PD-L1 positivity. The focal nature of HLA LOH alterations, their subclonal frequencies, enrichment in metastatic sites, and occurrence as parallel events suggests that HLA LOH is an immune escape mechanism that is subject to strong microenvironmental selection pressures later in tumor evolution. Characterizing HLA LOH with LOHHLA refines neoantigen prediction and may have implications for our understanding of resistance mechanisms and immunotherapeutic approaches targeting neoantigens.Video Abstract

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data with nuanced decision making. Cancer offers a unique context for medical decisions given not only its variegated forms with evolution of disease but also the need to take into account the individual condition of patients, their ability to receive treatment, and their responses to treatment. Challenges remain in the accurate detection, characterization, and monitoring of cancers despite improved technologies. Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses. In particular, artificial intelligence (AI) promises to make great strides in the qualitative interpretation of cancer imaging by expert clinicians, including volumetric delineation of tumors over time, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs. AI may automate processes in the initial interpretation of images and shift the clinical workflow of radiographic detection, management decisions on whether or not to administer an intervention, and subsequent observation to a yet to be envisioned paradigm. Here, the authors review the current state of AI as applied to medical imaging of cancer and describe advances in 4 tumor types (lung, brain, breast, and prostate) to illustrate how common clinical problems are being addressed. Although most studies evaluating AI applications in oncology to date have not been vigorously validated for reproducibility and generalizability, the results do highlight increasingly concerted efforts in pushing AI technology to clinical use and to impact future directions in cancer care.

A COVID19 lockdown in India posed signi cant challenges to the continuation of radiotherapy (RT) and systemic therapy services. While several COVID19 service guidelines have been promulgated, implementation data is yet unavailable. We performed a comprehensive audit of the implementation of services in a clinical oncology department. METHODS AND MATERIALS: A departmental protocol of priority-based treatment guidance was developed and a departmental staff rotation policy was implemented. Data was collected for the period of lockdown on outpatient visits, starting, and delivery of RT and systemic therapy. Adherence to protocol was audited, and factors affecting change from pre-COVID standards analyzed by multivariate logistic regression. RESULTS: Outpatient consults dropped by 58%. Planned RT starts were implemented in 90%, 100%, 92%, 90% and 75% of priority level 1-5 patients. While 17% had a deferred start, the median time to start of adjuvant RT and overall treatment times were maintained. Concurrent chemotherapy was administered in 89% of those eligible. Systemic therapy was administered to 84.5% of planned patients with 33% and 57% of curative and palliative patients receiving modi ed or deferred cycles. The patient's inability to come was the commonest reason for RT or ST deviation. Factors independently associated with a change from pre-COVID practice was priority level allocation for RT and age and palliative intent for systemic therapy. CONCLUSIONS: Despite signi cant access limitations a planned priority-based system of delivery of treatment could be implemented.

SummaryCD25 is expressed at high levels on regulatory T (Treg) cells and was initially proposed as a target for cancer immunotherapy. However, anti-CD25 antibodies have displayed limited activity against established tumors. We demonstrated that CD25 expression is largely restricted to tumor-infiltrating Treg cells in mice and humans. While existing anti-CD25 antibodies were observed to deplete Treg cells in the periphery, upregulation of the inhibitory Fc gamma receptor (FcγR) IIb at the tumor site prevented intra-tumoral Treg cell depletion, which may underlie the lack of anti-tumor activity previously observed in pre-clinical models. Use of an anti-CD25 antibody with enhanced binding to activating FcγRs led to effective depletion of tumor-infiltrating Treg cells, increased effector to Treg cell ratios, and improved control of established tumors. Combination with anti-programmed cell death protein-1 antibodies promoted complete tumor rejection, demonstrating the relevance of CD25 as a therapeutic target and promising substrate for future combination approaches in immune-oncology.

Circulating tumour DNA (ctDNA) refers to the fraction of cell-free DNA in a patient's blood that originates from a tumour. Advances in DNA sequencing technologies and our understanding of the molecular biology of tumours have resulted in increased interest in exploiting ctDNA as a tool to facilitate earlier detection of cancer and thereby improve therapeutic outcomes by enabling early intervention. ctDNA analysis might also have utility in the adjuvant therapeutic setting by enabling the identification of patients at a high risk of disease recurrence on the basis of the detection of post-surgical minimal (or molecular) residual disease (MRD). This approach could provide the capability to adapt clinical trials in the adjuvant setting in order to optimize risk stratification, and we argue that this objective is achievable with current technologies. Herein, we evaluate contemporary next-generation sequencing (NGS) approaches to ctDNA detection with a focus on non-small-cell lung cancer. We explain the technical and analytical challenges to low-frequency mutation detection using NGS-based ctDNA profiling and evaluate the feasibility of ctDNA profiling in both screening and MRD assessment contexts.

for noncommercial research purposes, and access will be granted upon review of a project proposal that will be evaluated by a TRACERx data access committee and entering into an appropriate data access agreement subject to any applicable ethical approvals.