Transcriptional phenocopies of deleterious KEAP1 mutations correlate with survival outcomes in lung cancer treated with immunotherapy.

PURPOSE: Co-occurring mutations in KEAP1 and STK11KRAS have emerged as determinants of survival outcomes in non-small cell lung cancer (NSCLC) patients treated with immunotherapy. However, these mutational contexts identify a fraction of non-responders to immune checkpoint inhibitors. We hypothesized that KEAP1 wild-type tumors recapitulate the transcriptional footprint of KEAP1 mutations, and that this KEAPness phenotype can determine immune responsiveness with higher precision compared to mutation-based models. EXPERIMENTAL DESIGN: The TCGA was used to infer the KEAPness phenotype and explore its immunological correlates at the pan-cancer level. The association between KEAPness and survival outcomes was tested in two independent cohorts of advanced NSCLC patients treated with immunotherapy and profiled by RNA-Seq (SU2C n=153; OAK/POPLAR n=439). The NSCLC TRACERx421 multi-region sequencing study (tumor regions n=947) was used to investigate evolutionary trajectories. RESULTS: KEAPness-dominant tumors represented 50% of all NSCLCs and were associated with shorter progression-free survival (PFS) and overall survival (OS) compared to KEAPness-free cases in independent cohorts of NSCLC patients treated with immunotherapy (SU2C PFS P=0.042, OS P=0.008; OAK/POPLAR PFS P=0.0014, OS P<0.001). Patients with KEAPness tumors had survival outcomes comparable to those with KEAP1-mutant tumors. In the TRACERx421, KEAPness exhibited limited transcriptional intratumoral heterogeneity and immune exclusion, resembling the KEAP1-mutant disease. This phenotypic state occurred across genetically divergent tumors, exhibiting shared and private cancer genes under positive selection when compared to KEAP1-mutant tumors. CONCLUSIONS: We identified a KEAPness phenotype across evolutionary divergent tumors. KEAPness outperforms mutation-based classifiers as a biomarker of inferior survival outcomes in NSCLC patients treated with immunotherapy.

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.

Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models.

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.

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer.

Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis. SIGNIFICANCE: This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.

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.

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.

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.

Physical function endpoints in cancer cachexia clinical trials: Systematic Review 1 of the cachexia endpoints series.

In cancer cachexia trials, measures of physical function are commonly used as endpoints. For drug trials to obtain regulatory approval, efficacy in physical function endpoints may be needed alongside other measures. However, it is not clear which physical function endpoints should be used. The aim of this systematic review was to assess the frequency and diversity of physical function endpoints in cancer cachexia trials. Following a comprehensive electronic literature search of MEDLINE, Embase and Cochrane (1990-2021), records were retrieved. Eligible trials met the following criteria: adults (≥18 years), controlled design, more than 40 participants, use of a cachexia intervention for more than 14 days and use of a physical function endpoint. Physical function measures were classified as an objective measure (hand grip strength [HGS], stair climb power [SCP], timed up and go [TUG] test, 6-min walking test [6MWT] and short physical performance battery [SPPB]), clinician assessment of function (Karnofsky Performance Status [KPS] or Eastern Cooperative Oncology Group-Performance Status [ECOG-PS]) or patient-reported outcomes (physical function subscale of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaires [EORTC QLQ-C30 or C15]). Data extraction was performed using Covidence and followed PRISMA guidance (PROSPERO registration: CRD42022276710). A total of 5975 potential studies were examined and 71 were eligible. Pharmacological interventions were assessed in 38 trials (54%). Of these, 11 (29%, n = 1184) examined megestrol and 5 (13%, n = 1928) examined anamorelin; nutritional interventions were assessed in 21 trials (30%); and exercise-based interventions were assessed in 6 trials (8%). The remaining six trials (8%) assessed multimodal interventions. Among the objective measures of physical function (assessed as primary or secondary endpoints), HGS was most commonly examined (33 trials, n = 5081) and demonstrated a statistically significant finding in 12 (36%) trials (n = 2091). The 6MWT was assessed in 12 trials (n = 1074) and was statistically significant in 4 (33%) trials (n = 403), whereas SCP, TUG and SPPB were each assessed in 3 trials. KPS was more commonly assessed than the newer ECOG-PS (16 vs. 9 trials), and patient-reported EORTC QLQ-C30 physical function was reported in 25 trials. HGS is the most commonly used physical function endpoint in cancer cachexia clinical trials. However, heterogeneity in study design, populations, intervention and endpoint selection make it difficult to comment on the optimal endpoint and how to measure this. We offer several recommendations/considerations to improve the design of future clinical trials in cancer cachexia.

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.

Copy number architectures define treatment-mediated selection of lethal prostate cancer clones.

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient evolutionary relationships of metastases that evade treatment, we perform genome-wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 167 metastatic regions from 11 organs harvested post-mortem from 10 men who died from prostate cancer. We identify diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number changes, we confirm a common clone of origin across metastases and diagnostic biopsies, and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. These autosome-defined clusters are characterized by cluster-specific AR gene architectures, and in two index cases are topologically more congruent than by chance (p-values 3.07 × 10-8 and 6.4 × 10-4). Integration with anatomical sites suggests patterns of spread and points of genomic divergence. Here, we show that copy number boundaries identify treatment-selected clones with putatively distinct lethal trajectories.

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.

Body composition and lung cancer-associated cachexia in TRACERx.

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.

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.

Insights into the metastatic cascade through research autopsies.

Metastasis is a complex process and the leading cause of cancer-related death globally. Recent studies have demonstrated that genomic sequencing data from paired primary and metastatic tumours can be used to trace the evolutionary origins of cells responsible for metastasis. This approach has yielded new insights into the genomic alterations that engender metastatic potential, and the mechanisms by which cancer spreads. Given that the reliability of these approaches is contingent upon how representative the samples are of primary and metastatic tumour heterogeneity, we review insights from studies that have reconstructed the evolution of metastasis within the context of their cohorts and designs. We discuss the role of research autopsies in achieving the comprehensive sampling necessary to advance the current understanding of metastasis.

Spatial Positioning of Immune Hotspots Reflects the Interplay between B and T Cells in Lung Squamous Cell Carcinoma.

Beyond tertiary lymphoid structures, a significant number of immune-rich areas without germinal center-like structures are observed in non-small cell lung cancer. Here, we integrated transcriptomic data and digital pathology images to study the prognostic implications, spatial locations, and constitution of immune rich areas (immune hotspots) in a cohort of 935 patients with lung cancer from The Cancer Genome Atlas. A high intratumoral immune hotspot score, which measures the proportion of immune hotspots interfacing with tumor islands, was correlated with poor overall survival in lung squamous cell carcinoma but not in lung adenocarcinoma. Lung squamous cell carcinomas with high intratumoral immune hotspot scores were characterized by consistent upregulation of B-cell signatures. Spatial statistical analyses conducted on serial multiplex IHC slides further revealed that only 4.87% of peritumoral immune hotspots and 0.26% of intratumoral immune hotspots were tertiary lymphoid structures. Significantly lower densities of CD20+CXCR5+ and CD79b+ B cells and less diverse immune cell interactions were found in intratumoral immune hotspots compared with peritumoral immune hotspots. Furthermore, there was a negative correlation between the percentages of CD8+ T cells and T regulatory cells in intratumoral but not in peritumoral immune hotspots, with tertiary lymphoid structures excluded. These findings suggest that the intratumoral immune hotspots reflect an immunosuppressive niche compared with peritumoral immune hotspots, independent of the distribution of tertiary lymphoid structures. A balance toward increased intratumoral immune hotspots is indicative of a compromised antitumor immune response and poor outcome in lung squamous cell carcinoma. SIGNIFICANCE: Intratumoral immune hotspots beyond tertiary lymphoid structures reflect an immunosuppressive microenvironment, different from peritumoral immune hotspots, warranting further study in the context of immunotherapies.

Targeted profiling of human extrachromosomal DNA by CRISPR-CATCH.

Extrachromosomal DNA (ecDNA) is a common mode of oncogene amplification but is challenging to analyze. Here, we adapt CRISPR-CATCH, in vitro CRISPR-Cas9 treatment and pulsed field gel electrophoresis of agarose-entrapped genomic DNA, previously developed for bacterial chromosome segments, to isolate megabase-sized human ecDNAs. We demonstrate strong enrichment of ecDNA molecules containing EGFR, FGFR2 and MYC from human cancer cells and NRAS ecDNA from human metastatic melanoma with acquired therapeutic resistance. Targeted enrichment of ecDNA versus chromosomal DNA enabled phasing of genetic variants, identified the presence of an EGFRvIII mutation exclusively on ecDNAs and supported an excision model of ecDNA genesis in a glioblastoma model. CRISPR-CATCH followed by nanopore sequencing enabled single-molecule ecDNA methylation profiling and revealed hypomethylation of the EGFR promoter on ecDNAs. We distinguished heterogeneous ecDNA species within the same sample by size and sequence with base-pair resolution and discovered functionally specialized ecDNAs that amplify select enhancers or oncogene-coding sequences.

Spatiotemporal genomic analysis reveals distinct molecular features in recurrent stage I non-small cell lung cancers.

Stage I non-small cell lung cancer (NSCLC) presents diverse outcomes. To identify molecular features leading to tumor recurrence in early-stage NSCLC, we perform multiregional whole-exome sequencing (WES), RNA sequencing, and plasma-targeted circulating tumor DNA (ctDNA) detection analysis between recurrent and recurrent-free stage I NSCLC patients (CHN-P cohort) who had undergone R0 resection with a median 5-year follow-up time. Integrated analysis indicates that the multidimensional clinical and genomic model can stratify the prognosis of stage I NSCLC in both CHN-P and EUR-T cohorts and correlates with positive pre-surgical deep next generation sequencing (NGS) ctDNA detection. Increased genomic instability related to DNA interstrand crosslinks and double-strand break repair processes is significantly associated with early tumor relapse. This study reveals important molecular insights into stage I NSCLC and may inform clinical postoperative treatment and follow-up strategies.

Allele-informed copy number evaluation of plasma DNA samples from metastatic prostate cancer patients: the PCF_SELECT consortium assay.

Sequencing of cell-free DNA (cfDNA) in cancer patients' plasma offers a minimally-invasive solution to detect tumor cell genomic alterations to aid real-time clinical decision-making. The reliability of copy number detection decreases at lower cfDNA tumor fractions, limiting utility at earlier stages of the disease. To test a novel strategy for detection of allelic imbalance, we developed a prostate cancer bespoke assay, PCF_SELECT, that includes an innovative sequencing panel covering ∼25 000 high minor allele frequency SNPs and tailored analytical solutions to enable allele-informed evaluation. First, we assessed it on plasma samples from 50 advanced prostate cancer patients. We then confirmed improved detection of genomic alterations in samples with <10% tumor fractions when compared against an independent assay. Finally, we applied PCF_SELECT to serial plasma samples intensively collected from three patients previously characterized as harboring alterations involving DNA repair genes and consequently offered PARP inhibition. We identified more extensive pan-genome allelic imbalance than previously recognized in prostate cancer. We confirmed high sensitivity detection of BRCA2 allelic imbalance with decreasing tumor fractions resultant from treatment and identified complex ATM genomic states that may be incongruent with protein losses. Overall, we present a framework for sensitive detection of allele-specific copy number changes in cfDNA.