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

Understanding the role of the tumour microenvironment (TME) in lung cancer is critical to improving patient outcome. We identified four histology-independent archetype TMEs in treatment-naive early-stage lung cancer using imaging mass cytometry in the TRACERx study (n=81 patients/198 samples/2.3million 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, characterised by sparse lymphocytes and high tumour-associated neutrophil (TAN) infiltration, had tumour cells spatially separated from vasculature and exhibited low spatial intratumour heterogeneity. TAN-High LUSC had frequent PIK3CA mutations. TAN-High tumours harboured 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.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

Short oral regimens for pulmonary rifampicin-resistant tuberculosis (TB-PRACTECAL): an open-label, randomised, controlled, phase 2B-3, multi-arm, multicentre, non-inferiority trial

BACKGROUND

Around 500 000 people worldwide develop rifampicin-resistant tuberculosis each year. The proportion of successful treatment outcomes remains low and new treatments are needed. Following an interim analysis, we report the final safety and efficacy outcomes of the TB-PRACTECAL trial, evaluating the safety and efficacy of oral regimens for the treatment of rifampicin-resistant tuberculosis.

METHODS

This open-label, randomised, controlled, multi-arm, multicentre, non-inferiority trial was conducted at seven hospital and community sites in Uzbekistan, Belarus, and South Africa, and enrolled participants aged 15 years and older with pulmonary rifampicin-resistant tuberculosis. Participants were randomly assigned, in a 1:1:1:1 ratio using variable block randomisation and stratified by trial site, to receive 36-80 week standard care; 24-week oral bedaquiline, pretomanid, and linezolid (BPaL); BPaL plus clofazimine (BPaLC); or BPaL plus moxifloxacin (BPaLM) in stage one of the trial, and in a 1:1 ratio to receive standard care or BPaLM in stage two of the trial, the results of which are described here. Laboratory staff and trial sponsors were masked to group assignment and outcomes were assessed by unmasked investigators. The primary outcome was the percentage of participants with a composite unfavourable outcome (treatment failure, death, treatment discontinuation, disease recurrence, or loss to follow-up) at 72 weeks after randomisation in the modified intention-to-treat population (all participants with rifampicin-resistant disease who received at least one dose of study medication) and the per-protocol population (a subset of the modified intention-to-treat population excluding participants who did not complete a protocol-adherent course of treatment (other than because of treatment failure or death) and those who discontinued treatment early because they violated at least one of the inclusion or exclusion criteria). Safety was measured in the safety population. The non-inferiority margin was 12%. This trial is registered with ClinicalTrials.gov, NCT02589782, and is complete.

FINDINGS

Between Jan 16, 2017, and March 18, 2021, 680 patients were screened for eligibility, of whom 552 were enrolled and randomly assigned (152 to the standard care group, 151 to the BPaLM group, 126 to the BPaLC group, and 123 to the BPaL group). The standard care and BPaLM groups proceeded to stage two and are reported here, post-hoc analyses of the BPaLC and BPaL groups are also reported. 151 participants in the BPaLM group and 151 in the standard care group were included in the safety population, with 138 in the BPaLM group and 137 in the standard care group in the modified intention-to-treat population. In the modified intention-to-treat population, unfavourable outcomes were reported in 16 (12%) of 137 participants for whom outcome was assessable in the BPaLM group and 56 (41%) of 137 participants in the standard care group (risk difference -29·2 percentage points [96·6% CI -39·8 to -18·6]; non-inferiority and superiority p<0·0001). 34 (23%) of 151 participants receiving BPaLM had adverse events of grade 3 or higher or serious adverse events, compared with 72 (48%) of 151 participants receiving standard care (risk difference -25·2 percentage points [96·6% CI -36·4 to -13·9]). Five deaths were reported in the standard care group by week 72, of which one (COVID-19 pneumonia) was unrelated to treatment and four (acute pancreatitis, suicide, sudden death, and sudden cardiac death) were judged to be treatment-related.

INTERPRETATION

The 24-week, all-oral BPaLM regimen is safe and efficacious for the treatment of pulmonary rifampicin-resistant tuberculosis, and was added to the WHO guidance for treatment of this condition in 2022. These findings will be key to BPaLM becoming the preferred regimen for adolescents and adults with pulmonary rifampicin-resistant tuberculosis.

FUNDING

Médecins Sans Frontières.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Phenotyping of lymphoproliferative tumours generated in xenografts of non-small cell lung cancer

Background

Patient-derived xenograft (PDX) models involve the engraftment of tumour tissue in immunocompromised mice and represent an important pre-clinical oncology research method. A limitation of non-small cell lung cancer (NSCLC) PDX model derivation in NOD-scid IL2Rgammanull (NSG) mice is that a subset of initial engraftments are of lymphocytic, rather than tumour origin.

Methods

The immunophenotype of lymphoproliferations arising in the lung TRACERx PDX pipeline were characterised. To present the histology data herein, we developed a Python-based tool for generating patient-level pathology overview figures from whole-slide image files; PATHOverview is available on GitHub (https://github.com/EpiCENTR-Lab/PATHOverview).

Results

Lymphoproliferations occurred in 17.8% of lung adenocarcinoma and 10% of lung squamous cell carcinoma transplantations, despite none of these patients having a prior or subsequent clinical history of lymphoproliferative disease. Lymphoproliferations were predominantly human CD20+ B cells and had the immunophenotype expected for post-transplantation diffuse large B cell lymphoma with plasma cell features. All lymphoproliferations expressed Epstein-Barr-encoded RNAs (EBER). Analysis of immunoglobulin light chain gene rearrangements in three tumours where multiple tumour regions had resulted in lymphoproliferations suggested that each had independent clonal origins.

Discussion

Overall, these data suggest that B cell clones with lymphoproliferative potential are present within primary NSCLC tumours, and that these are under continuous immune surveillance. Since these cells can be expanded following transplantation into NSG mice, our data highlight the value of quality control measures to identify lymphoproliferations within xenograft pipelines and support the incorporation of strategies to minimise lymphoproliferations during the early stages of xenograft establishment pipelines.

Late-Stage Metastatic Melanoma Emerges through a Diversity of Evolutionary Pathways

Understanding the evolutionary pathways to metastasis and resistance to immune-checkpoint inhibitors (ICI) in melanoma is critical for improving outcomes. Here, we present the most comprehensive intrapatient metastatic melanoma dataset assembled to date as part of the Posthumous Evaluation of Advanced Cancer Environment (PEACE) research autopsy program, including 222 exome sequencing, 493 panel-sequenced, 161 RNA sequencing, and 22 single-cell whole-genome sequencing samples from 14 ICI-treated patients. We observed frequent whole-genome doubling and widespread loss of heterozygosity, often involving antigen-presentation machinery. We found KIT extrachromosomal DNA may have contributed to the lack of response to KIT inhibitors of a KIT-driven melanoma. At the lesion-level, MYC amplifications were enriched in ICI nonresponders. Single-cell sequencing revealed polyclonal seeding of metastases originating from clones with different ploidy in one patient. Finally, we observed that brain metastases that diverged early in molecular evolution emerge late in disease. Overall, our study illustrates the diverse evolutionary landscape of advanced melanoma.

SIGNIFICANCE

Despite treatment advances, melanoma remains a deadly disease at stage IV. Through research autopsy and dense sampling of metastases combined with extensive multiomic profiling, our study elucidates the many mechanisms that melanomas use to evade treatment and the immune system, whether through mutations, widespread copy-number alterations, or extrachromosomal DNA. See related commentary by Shain, p. 1294. This article is highlighted in the In This Issue feature, p. 1275.

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.

Abstract 2037: Tracking the emergence of immunotherapy resistance in lung cancer metastases

Metastatic non-small cell lung cancer (NSCLC) results from a complex evolutionary process in which cancer cells migrate from a primary tumour to a new anatomical site. Immunotherapy is frequently used to treat NSCLC, but drug resistance is frequent (&gt;50%) and metastasis remains the most common cause of death. Recent studies of primary and metastatic tumours suggest that anti-cancer treatments can impact cancer evolutionary dynamics by applying selective pressures that promote the development of treatment resistance in genetically distinct subpopulations of cancer cells, or tumour clones. However, the relationship between metastatic progression and the development of resistance to immunotherapy has not been fully explored. In particular, whether metastases become resistant to immunotherapy as a result of the migration of resistant cells or whether distinct metastatic sites converge in parallel toward an immunotherapy resistance phenotype irrespective of cell migration, is not known.

In this work, we investigate the role of metastatic cell migration in the development of immunotherapy resistance using DNA sequencing data from primary and metastatic tumour samples from twelve immunotherapy-treated patients with NSCLC co-recruited to the national TRACERx and PEACE studies. Using computational approaches, we identified distinct tumour clones in primary and metastatic tumours and used these to reconstruct tumour phylogenies for each patient. By evaluating tumour clonal dynamics in relation to treatment, we classified tumour clones as either sensitive or resistant to immunotherapy. We reconstructed the metastatic migration histories of these clones using existing computational methods based on somatic single nucleotide variants. Our results suggest that heterogeneous mechanisms of immune evasion develop in parallel at distinct metastatic sites. The ongoing analysis of the genetic changes that distinguish resistant from sensitive clones, and migrating from non-migrating clones, will provide further detail regarding the impact of metastatic migrations on immunotherapy resistance.

Using this approach to map the evolutionary history of metastatic NSCLC, we provide insight into the mechanism by which immunotherapy resistance develops at distinct metastatic sites.

Citation Format: Sonya Hessey, Ariana Huebner, Oriol Pich, Abi Bunkum, Wing Liu, David A. Moore, Cristina Naceur-Lombardelli, Selvaraju Veeriah, Sophie Ward, Roberto Salgado, Nicholas McGranahan, Simone Zaccaria, Charles Swanton, Mariam Jamal-Hanjani. Tracking the emergence of immunotherapy resistance in lung cancer metastases [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 2037.

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.

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.

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.

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.

Lung adenocarcinoma promotion by air pollutants

A complete understanding of how exposure to environmental substances promotes cancer formation is lacking. More than 70 years ago, tumorigenesis was proposed to occur in a two-step process: an initiating step that induces mutations in healthy cells, followed by a promoter step that triggers cancer development1. Here we propose that environmental particulate matter measuring ≤2.5 μm (PM2.5), known to be associated with lung cancer risk, promotes lung cancer by acting on cells that harbour pre-existing oncogenic mutations in healthy lung tissue. Focusing on EGFR-driven lung cancer, which is more common in never-smokers or light smokers, we found a significant association between PM2.5 levels and the incidence of lung cancer for 32,957 EGFR-driven lung cancer cases in four within-country cohorts. Functional mouse models revealed that air pollutants cause an influx of macrophages into the lung and release of interleukin-1β. This process results in a progenitor-like cell state within EGFR mutant lung alveolar type II epithelial cells that fuels tumorigenesis. Ultradeep mutational profiling of histologically normal lung tissue from 295 individuals across 3 clinical cohorts revealed oncogenic EGFR and KRAS driver mutations in 18% and 53% of healthy tissue samples, respectively. These findings collectively support a tumour-promoting role for  PM2.5 air pollutants  and provide impetus for public health policy initiatives to address air pollution to reduce disease burden.

Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

Circulating tumour DNA (ctDNA) can be used to detect and profile residual tumour cells persisting after curative intent therapy1. The study of large patient cohorts incorporating longitudinal plasma sampling and extended follow-up is required to determine the role of ctDNA as a phylogenetic biomarker of relapse in early-stage non-small-cell lung cancer (NSCLC). Here we developed ctDNA methods tracking a median of 200 mutations identified in resected NSCLC tissue across 1,069 plasma samples collected from 197 patients enrolled in the TRACERx study2. A lack of preoperative ctDNA detection distinguished biologically indolent lung adenocarcinoma with good clinical outcome. Postoperative plasma analyses were interpreted within the context of standard-of-care radiological surveillance and administration of cytotoxic adjuvant therapy. Landmark analyses of plasma samples collected within 120 days after surgery revealed ctDNA detection in 25% of patients, including 49% of all patients who experienced clinical relapse; 3 to 6 monthly ctDNA surveillance identified impending disease relapse in an additional 20% of landmark-negative patients. We developed a bioinformatic tool (ECLIPSE) for non-invasive tracking of subclonal architecture at low ctDNA levels. ECLIPSE identified patients with polyclonal metastatic dissemination, which was associated with a poor clinical outcome. By measuring subclone cancer cell fractions in preoperative plasma, we found that subclones seeding future metastases were significantly more expanded compared with non-metastatic subclones. Our findings will support (neo)adjuvant trial advances and provide insights into the process of metastatic dissemination using low-ctDNA-level liquid biopsy.

Evolutionary characterization of lung adenocarcinoma morphology in TRACERx

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.

Abstract 5055: Precise segmentation of growth patterns in TRACERx lung adenocarcinoma

Histologic growth patterns are associated with patient prognosis, thus recognized as an important part of the WHO classification in lung adenocarcinoma (Travis et al. 2015, Moreira et al., 2020). The wide spectrum of growth patterns proves challenging for reproducible and quantitative scoring. Currently, scoring is based on manual identification of the predominant pattern and percentages of patterns in routine diagnostic slides. The lack of an automated method also limits our ability to investigate the immune microenvironment of growth patterns.

To overcome the above challenges, we present a deep learning method, Pyramid Stream Networks, to precisely segment growth patterns at pixel level. Unlike existing methods, the proposed method captures different spatial scales of the histology information by novel attention strategies at different learning stages. This problem-oriented design yields precise boundaries for each pattern, enabling the investigation of growth pattern heterogeneity, and the relationship with tumor microenvironment components.

Experiments were conducted on 49 haematoxylin and eosin whole slide images (WSIs) from TRACERx 100 cohort (AbdulJabbar et al., 2020). Each WSI was sparsely annotated by 3 senior pathologists. A total of 2968 annotated patches were split into 5 folds for cross validation. We compared our method with two state-of-the-art methods applied in semantic segmentation, attention U-net (Oktay et al. 2018) and DeepLabV3+ (Chen et al. 2018). When evaluated at patch level, our method outperformed the better comparison method, DeepLabV3+, by 3.43% and 2.99% in pixel-wise Dice and overall precision (OP) (Dice: 60.34% vs. 56,91%, OP: 65.43% vs. 62.44%). When applied to WSIs, the model correctly predicted the predominant pattern for 38 out of 49 samples, achieving an accuracy of 77.55%. Interestingly, in the 11 discordant cases, 10 showed high intra-tumor heterogeneity of growth patterns, measured by Shannon diversity, highlighting the impact of intra-tumor heterogeneity on growth pattern assessment. Additionally, we combined the identified growth patterns with lymphocytic distribution measured in (AbdulJabbar et al., 2020) and revealed a significantly increased immune infiltration in proximity to the solid pattern as compared to others, which is in line with previous findings (Tavernari et al., 2021).

In summary, by leveraging image-analysis and artificial intelligence techniques, we propose a new method for precise growth pattern segmentation from routine histology samples of lung adenocarcinoma. It provides quantitative and reproducible scores of growth patterns, which can be developed into a decision support system for pathologists and clinicians. Furthermore, through pattern-specific spatial mapping, it enables future studies of intra-tumor heterogeneity, such as the preferential infiltration of lymphocyte subsets adjacent to diverse growth patterns.

Citation Format: Xiaoxi Pan, Hanyun Zhang, Anca-Ioana Grapa, Khalid AbdulJabbar, Shan E. Ahmed Raza, HO KWAN ALVIN CHEUNG, Takahiro Karasaki, John Le Quesne, David A. Moore, Charles Swanton, Yinyin Yuan. Precise segmentation of growth patterns in TRACERx lung adenocarcinoma [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 5055.

Abstract 3096: Multi-region patient-derived xenograft models from non-small cell lung cancer patients enrolled in lung TRACERx

Patient-derived xenograft (PDX) models have become important models in cancer biology. They are thought to mimic tumor biology more closely than traditional cell lines as a consequence of their in vivo heterocellularity and cell-matrix interactions, their 3D architecture and their relatively recent derivation. The genomic fidelity of PDXs is integral to their applications in both basic research and in translational medicine. We derived multi-region PDX models from patients enrolled in TRACERx - a study of the evolutionary dynamics of non-small cell lung cancer (NSCLC) that uses a multi-region deep whole-exome sequencing (WES) approach - using more extensive spatial sampling to better understand the histological and genomic fidelity of the PDX approach.

We transplanted regional NSCLC tumor tissue subcutaneously into immunocompromised NSG mice. 134 regions were attempted, resulting in 60 passagable xenografts (44.8%). Of these, 44 regional xenografts (32.8% of all regions) were NSCLC-derived, while 16 (11.9% of all regions) were B-cell lymphoproliferative disease. Multi-region sampling revealed heterogeneous success of PDX derivation between regions within individual patient tumors. There was correlation between PDX derivation and tumor purity by WES. Overall, NSCLC PDX models were established for 22 patients (50%; range 1-5 regional models per patient; Table 1). Histologically, broad similarity was observed between PDX models and corresponding patient tumor regions, although in a small number of models, variability was noted between the patient tumor and the corresponding PDX model, or during PDX passaging. PDXs were subjected to WES for comparison with matched patient tumor regions.

Overall, our study demonstrates the feasibility of systematic multi-region PDX derivation and suggests that multiple spatial sampling of tumors could improve PDX take rates and generate PDXs that represent the intratumor diversity of heterogenous NSCLCs.

Table 1. Engraftment rates of multiple spatial regions from non-small cell lung cancer tumors. Attempted NSCLC PDX B-Lymphoproliferations No Xenograft: Regions No Xenograft: Any Region LUAD 48 (21) 12 (7) 9 (7) 27 (10) LUSC 61 (17) 20 (11) 6 (5) 35 (4) Other 25 (6) 12 (4) 1 (1) 12 (1) TOTAL 134 (44) 44 (22) 16 (13) 74 (15)

Citation Format: Robert E. Hynds, David R. Pearce, Ayse U. Akarca, Sophia Ward, Ariana Huebner, Oriol Pich, Gareth A. Wilson, Kate H. Gowers, Rebecca Towns, Assma Ben Aissa, Selvaraju Veeriah, Sergio A. Quezada, Mariam Jamal-Hanjani, Sam M. Janes, Nicholas McGranahan, David A. Moore, Teresa Marafioti, Charles Swanton. Multi-region patient-derived xenograft models from non-small cell lung cancer patients enrolled in lung TRACERx [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 3096.

Abstract LB153: Clinical relevance of spatial intermixing of growth patterns and immune infiltration in lung adenocarcinoma-from TRACERx to LATTICe-A

Adenocarcinoma, the most common histologic variant of lung cancer, is morphologically diverse. The International Association for the Study of Lung Cancer (IASLC) grading system, based on the percentages of growth patterns within the tumour, is highly prognostic (Moreira et al. 2020). However, the clinicopathological significance of transitions between growth patterns, and the combinatorial effects of growth pattern and inflammatory cell infiltration are not yet known. We used a deep learning model to delineate six growth patterns (lepidic, acinar, papillary, micropapillary, solid, and cribriform) at pixel level on hematoxylin and eosin diagnostic whole slide images. The model was trained on 49 slides from the TRACERx cohort (AbdulJabbar et al. 2020), and subsequently applied to 4324 slides from 970 adenocarcinoma cases from the Leicester Archival Thoracic Tumor Investigatory Cohort (Moore et al. 2019). To examine how tumor growth patterns are spatially intermixed, we created a graph network of growth patterns. A linking criterion based on effective cell-cell communication distance was established, whereby adjacent compact tumor islands were linked together. Frequencies of 15 types of pairwise links were further evaluated. A higher intermixing score, measured as the Shannon diversity of link percentages, was associated with adverse relapse free survival (RFS) (p&lt;0.001, Hazard Ratio (HR)=1.5, 95% Confidence Interval (CI)=1.3-1.8, n=966), independently of automated IASLC grading (p=0.001, HR=1.4, 95% CI=1.1-1.7). The clinical relevance of intermixing profiles was investigated by clustering patients into 3 groups, based on the similarity between link percentages. The group dominated by links involving high grade patterns (solid, micropapillary, cribriform), showed the highest risk of relapse (p&lt;0.001, HR=1.7, 95% CI=1.4-2.2), followed by the group enriched with papillary-acinar links (p=0.006, HR=1.4, 95% CI=1.1-1.7). Although micropapillary subtype per se confers an unfavorable prognosis (Cao et al. 2016), its association with papillary morphology increased the risk of relapse (p=0.002, HR=4.2, 95% CI=1.6-11.0), independently of micropapillary burden. To investigate the immune microenvironment surrounding growth patterns, we quantified immune cells at the interface between growth patterns. We observed significantly reduced immune infiltration between micropapillary and papillary than between micropapillary and acinar, solid, and cribriform patterns (p&lt;0.001). In conclusion, we showed that tumor growth pattern spatial intermixing is associated with adverse prognosis and immune infiltration. These findings offer novel insights into the spatial interplay of histological phenotypes and its clinical relevance, which may have an impact on immune escape.

Citation Format: Anca-Ioana Grapa, Hanyun Zhang, Xiaoxi Pan, Khalid AbdulJabbar, Jose Coelho-Lima, Ho Kwan Alvin Cheung, Sarah J. Aitken, David A. Moore, Charles Swanton, John Le Quesne, Yinyin Yuan. Clinical relevance of spatial intermixing of growth patterns and immune infiltration in lung adenocarcinoma-from TRACERx to LATTICe-A [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 LB153.

Abstract 6080: The heterogeneity and evolution of lung neuroendocrine tumors within TRACERx

Introduction: Primary pulmonary neuroendocrine tumors (NETs) contribute to 20-25% of all lung cancer diagnoses and lie on a spectrum of malignant behavior, ranging from low grade classical carcinoid tumors to high grade, aggressive small cell carcinomas. The evolutionary relationships between NETs of different grades remain poorly understood, here we seek to use the TRACERx study to explore the genomic evolution of these lung cancers.

Methods: Tissue and blood samples were taken from a cohort of 20 patients with pulmonary NETs in a sub-study within TRACERx. Multi-region sampling (84 total regions) and whole exome sequencing was performed on fresh frozen tissue from each tumor. Histological classification of each tumor region was confirmed and scoring of tumor infiltrating lymphocytes (TILs) was performed. The data were then analyzed using the established TRACERx bioinformatics pipeline.

Results: Phylogenetic evolutionary histories were generated, illustrating the genomic divergence in each tumor and identifying points at which specific known drivers were acquired during tumor evolution. Lower grade classical and atypical carcinoids were characterized by a low mutational and copy number burden with a high fraction of subclonal mutations, with 5/12 cases having no apparent somatic mutational driver mutation. In contrast higher grade large cell neuroendocrine carcinomas and small cell carcinomas had higher mutational and copy number burden, as well as higher rates of genome instability and whole genome doubling. We identified no evolutionary link between subtypes such as commonly shared clonal drivers, suggesting that atypical or classical carcinoids later evolve into higher grade carcinomas. Dn/ds was used to investigate for evidence of selection in the carcinoid tumors; while there was no evidence for selection in known cancer driver genes associated with NETs or lung cancer, there was a high global dn/ds value suggesting the existence of unknown drivers for this cancer type. Furthermore, there was evidence of parallel evolution in one atypical carcinoid case with two distinct subclonal MEN1 frameshift mutations co-occurring with loss of the other allele. One small cell carcinoma patient was identified as having two genetically unrelated tumors. A germline predisposition for this tumor was suspected since we identified a variant in BRCA2 (rs11571833) that was maintained under loss of heterozygosity in one tumor with a corresponding somatic BRCA2 mutation in the other, suggesting two independent double hit events.

Conclusions: Genomic differences are identifiable between different members of the pulmonary NET family, with high grade tumors showing increased whole genome instability indices and phylogenetic divergence than low grade tumors. This work has shed light on the genomic landscape of pulmonary NETs and enabled the identification of distinct evolutionary trajectories in the different subtypes.

Citation Format: Robert Bentham, David A. Moore, Lorelle Brownlee, Raju Veeriah, Lizi Manzano, Fiona Blackhall, Colin R. Lindsay, TRACERx Consortium, Nicholas McGranahan, Charles Swanton, Mariam Jamal-Hanjani. The heterogeneity and evolution of lung neuroendocrine tumors within TRACERx [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 6080.

Abstract 6091: Evolutionary characterisation of lung adenocarcinoma pathological subtypes in TRACERx

Background: Lung adenocarcinoma (LUAD) is a morphologically and genetically diverse disease. The prognostic impact of LUAD histological patterns have been described, such as solid growth pattern and poor outcomes, though their underlying biology is poorly understood. Furthermore, the genomic characteristics and evolutionary constraints in relation to the inter- and intra- tumoral variance of histological patterns in primary and metastatic disease are unknown.

Methods: Pathological classification of 246 patients with LUAD from the TRACERx 421 cohort was performed at the whole tumor (diagnostic samples) and multi-regional sample level (matched for tumor whole exome sequencing and RNA sequencing). Circulating tumor DNA (ctDNA) data was also integrated to determine the relationship between pathological subtypes and ctDNA detection.

Results: Chromosomal instability, characterized by fraction of the genome affected by subclonal copy number alterations was significantly correlated with proportion of high-grade patterns, namely solid, cribriform and micropapillary (Spearman’s Rho 0.27, p&lt;0.001). Analysis of somatic copy number alterations (SCNAs) and driver mutation profiles showed that specific SCNAs were associated with a predominant growth pattern, such as 3q arm gains in predominantly cribriform and solid pattern tumors. Multiregional analysis of tumors with mixed patterns showed higher grade regions to be associated with a higher frequency of LOH and expression of proliferation-related pathway genes, suggesting intra-tumoral sequential evolution from low to high grade growth patterns. No recurrent subclonal mutations or SCNAs were found to associate with progression from low to high grade patterns. The growth pattern in metastatic tumors tended to show similar or a higher-grade pattern compared with primary tumor regions harboring metastasizing clones (seeding regions). The growth pattern of the seeding regions in the primary tumor was not necessarily higher grade compared with their non-seeding counterparts. Finally, the proportion of solid pattern in the primary tumor and the presence of necrosis were found to be strongly associated with pre-operative ctDNA detection, while histological ‘spread through air spaces’ (STAS) was identified in 92% (12/13) of pre-operative ctDNA-negative tumors that subsequently were associated with recurrence. Patients with both pre-operative detectable ctDNA and STAS had a particularly poor prognosis.

Conclusion: These data reveal insights into the association between morphological and molecular heterogeneity in LUAD, describe key features of tumor evolutionary tendencies and demonstrate the utility of detailed tumor morphological assessment integrated with molecular characterization and ctDNA detection.

Citation Format: Takahiro Karasaki, David A. Moore, Selvaraju Veeriah, Cristina Naceur-Lombardelli, Antonia Toncheva, Maise Al Bakir, Thomas B. Watkins, Oriol Pich, Alexander M. Frankell, Emilia Lim, Mark S. Hill, Kristiana Grigoriadis, Carlos Martinez-Ruiz, James R. Black, Clare Puttick, Dhruva Biswas, Ariana Huebner, Michelle Dietzen, Emma Colliver, Claudia Lee, Nnenna Kanu, Sadegh Mohammad Saghafinia, Francisco Gimeno Valiente, Christopher Abbosh, Crispin T. Hiley, Simone Zaccaria, Nicolai J. Birkbak, Allan Hackshaw, TRACERx Consortium, Teresa Marafioti, Roberto Salgado, John Le Quesne, Andrew G. Nicholson, Nicholas McGranahan, Charles Swanton, Mariam Jamal-Hanjani. Evolutionary characterisation of lung adenocarcinoma pathological subtypes in TRACERx [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 6091.

Abstract LB064: B cells synergize with T cell regulation at immune hotspots in lung squamous cell carcinoma

The interplay of immune cell subpopulations underpinning heterogeneous immune infiltration is poorly understood, hindering the establishment of robust prognostic markers and therapeutic targets.

To study the prognostic implications and constitution of immune cell aggregates in lung squamous cell carcinoma, we integrated transcriptomic data and deep-learning-based spatial analysis. With the automatically identified tumor and immune cells on hematoxylin and eosin (H&E) diagnostic whole slide images, we were able to map regions with lymphoid aggregates (immune hotspots - IHs) and tumor aggregates (cancer hotspots) using the Getis-Ord hotspot analysis (Getis and Ord, 1992; Nawaz et al., 2015), in 462 TCGA samples. IHs were further categorized into intratumoral (intra-IH) and peritumoral (peri-IH) based on whether they overlapped with cancer hotspots. The intra-IH score, quantifying the fraction of IHs at the cancer interface, was associated with poor overall survival independently of age, stage, and packs per year (p &lt; 0.01, Hazard Ratio (HR) = 2.1 [1.3-3.2]). The increased score was coupled with upregulated transcriptional signals of B cells and T regulatory cells, and expression of B cell-related genes CXCR5, MS4A1 (CD20), CD79b.

To investigate cellular compositions of IHs, we selected 10 TRACERX patients with high intra-IH score based on H&E and performed immunohistochemistry on two serial sections followed by a deep learning model to locate subpopulations of T cells (CD4+FOXP3-, CD4+FOXP3+, CD8+) and B cells (CD20+CXCR5-, CD20+CXCR5+, and CD79b+). By spatially aligning these IHC images with H&E, we observed higher abundances of CD20+CXCR5+ and CD79b+ B cells at peri-IHs than intra-IHs (p&lt;0.01; p&lt;0.05), whereas none of the T cell subtypes showed a difference in localization. Tertiary lymphoid structures (TLSs) accounted for a minor proportion of peri-IHs (5.04 +- 4.38%) and intra-IHs (0.43 +- 0.61%). Furthermore, percentages of CD20+CXCR5+ B cells were significantly higher at peri-IHs than intra-IHs when TLSs were excluded (p=0.007), suggesting that the enrichment of CD20+CXCR5+ B cells at peri-IHs was not fully explained by the presence of TLSs.

To test if IHs have a role in the regulation of anti-tumor activity of T cytotoxic cells, we further measured the ratio of CD8+ to CD4+FOXP3+ T cells infiltrating into the tumor nest. The ratio at tumor regions adjacent to intra-IH was lower than the rest of the tumor nest (p&lt;0.001), suggesting a suppressive effect of intra-IH on tumor-infiltrating CD8+ T cells.

Taken together, our results signified a protumor role of intratumoral lymphoid aggregates beyond TLSs, which may be attributed to the spatial interplay between CD8+ T cells, Tregs and B cells. Immune hotspots can serve as a prognostic indicator and potential therapeutic target in lung squamous cell carcinoma.

Citation Format: Hanyun Zhang, Khalid AbdulJabbar, David A. Moore, Ayse Akarca, Katey Enfield, Mariam Jamal-Hanjani, Shan E Ahmed Raza, Selvaraju Veeriah, Dhruva Biswas, Roberto Salgado, Nicholas McGranahan, TRACERx Consortium, John Le Quesne, Charles Swanton, Teresa Marafioti, Yinyin Yuan. B cells synergize with T cell regulation at immune hotspots in lung squamous cell carcinoma [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 LB064.

Abstract 3792: TRACERx: Mapping the evolution of metastases in non-small cell lung cancer

Background: Primary lung cancer is the leading cause of cancer-related mortality, with metastatic disease being responsible for the majority of deaths. To gain insight into the lethal process of metastasis, we report on the longitudinal evolutionary analysis of the TRACERx 421 paired primary-metastasis cohort.

Methods: 712 tumor samples, of which 485 were primary tumor and 227 were metastatic samples, from 129 metastatic non-small cell lung cancer (NSCLC) patients with detailed clinical annotation were collected from 18 UK hospital sites and whole exome sequenced. Mutations and copy number events were integrated to resolve the evolutionary history of each tumor.

Results: We observe that metastases generally diverge relatively late in molecular time, after the majority of mutations in the primary tumor have accumulated, with a substantial minority (33%) diverging prior to the last clonal sweep in the primary tumor. For this minority of cases, divergence is estimated to have occurred at tumor volumes below the limit of computed tomography (CT) detection. Our extensively sampled cohort reveals that sampling bias may result in erroneous inference of metastatic trajectories. 79% of metastases diverging after the last clonal sweep in the primary tumor would be misclassified as diverging prior to the last clonal sweep if only a single region of the primary tumor is considered.

Patterns of dissemination range from monoclonal, involving a single metastatic clone (68% - where metastatic potential is likely acquired once in the life-history of the tumor), to polyclonal and polyphyletic (17%), where metastatic potential may have arisen multiple times during lung cancer development, or at a single time point early in the development of the tumor. We find that thoracic lymph node disease resected at surgery was responsible for less than 20% of subsequent disease dissemination, suggesting that lymph nodes likely represent a hallmark of metastatic potential rather than a gateway to further metastases.

Furthermore, we observe that clones which seed the metastases are generally dominant within the primary, reflecting positive selection and acquisition of subclonal mutations in specific cancer genes (e.g. RB1, PIK3CA). In squamous cell carcinomas, we find that non-metastatic primary tumors show no significant evidence of positive subclonal selection. We find that 35% of metastases harbor driver mutations not identified in the primary tumor and identify somatic copy number alterations that are enriched in metastases (e.g. CCND1 gains in lung adenocarcinoma).

Conclusions: These data highlight the potential to apply evolutionary measures to primary tumors to predict metastatic risk, the limitations to current screening approaches particularly for early tumor divergence, and the importance of future precision adjuvant therapies to target disseminated micro-metastatic clones.

Citation Format: Ariana Huebner, Maise Al Bakir, Carlos Martinez Ruiz, Kristiana Grigoriadis, Thomas B. Watkins, Oriol Pich, David A. Moore, Selvaraju Veeriah, Sophia Ward, Joanne Laycock, Diana Johnson, Andrew Rowan, Maryam Razaq, Mita Akther, Cristina Naceur-Lombardelli, Sonya Hessey, Michelle Dietzen, Emma Colliver, Alexander M. Frankell, Emilia Lim, Takahiro Karasaki, Christopher Abbosh, Crispin T. Hiley, Mark S. Hill, Daniel Cook, Gareth Wilson, TRACERx consortium, Allan Hackshaw, Nicolai J. Birkbak, Simone Zaccaria, Mariam Jamal-Hanjani, Charles Swanton, Nicholas McGranahan. TRACERx: Mapping the evolution of metastases in non-small cell lung cancer [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 3792.

Abstract 6113: Spatially resolved biomarker detection on single cells in TRACERx using multiplex imaging

Introduction. Studying cell-to-cell variation within the tumour’s native context is crucial for fully understanding tumour heterogeneity and its impact on disease progression and therapy response. Tumour cells and their surrounding stromal cells can be spatially profiled using multiplex imaging with a growing number of detectable proteins. The methods currently used for identification of cell phenotypes from multiplex imaging data have been initially developed for cells in suspension. Therefore, more accurate and robust approaches are required to account for spatial signal overlap and to automatically detect the presence of biomarkers in spatial proteomics.

Methods. We performed imaging mass cytometry on 221 tumour and adjacent normal regions from 81 untreated, non-small cell lung cancer patients in the TRACERx study. Two antibody panels with 35 markers were applied to include a range of phenotypic, functional, and structural biomarkers. Single cells were segmented using deep learning-based approaches, and the measured biomarker intensities per cell were further used to identify cell types and functional states.

Results. We developed a computational approach optimised for spatial proteomics for identification of cell types and functional states and automated detection of the presence of biomarkers on single cells. First, we demonstrated that current approaches for cell phenotyping lack reproducibility with subsampling and can produce ambiguous clusters of cells from different cell types. Using a multi-tiered analytical approach in combination with statistical tools, we showed reproducibility between technical and biological replicates. We estimated the performance using orthogonal measurements from flow cytometry and immunohistochemistry from matched tumour samples. This approach has been automated with a scalable and portable Nextflow-based implementation.

Conclusions. We developed a streamlined approach that overcame limitations of current methods and quantified single-cell biomarker presence using multiplex imaging with TRACERx. Implemented as open-source, portable and customisable, this pipeline for spatially resolved TME characterisation will allow the study of drug targets expression within their spatial context for a better understanding of therapy efficacy.

Citation Format: Mihaela Angelova, Katey Enfield, Alastair Magness, Emma Colliver, Masako Shimato, Claudia Lee, David A. Moore, Febe Van Maldegem, Philip Hobson, Dina Levi, James L. Reading, Crispin T. Hiley, Julian Downward, Erik Sahai, Charles Swanton. Spatially resolved biomarker detection on single cells in TRACERx using multiplex imaging [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 6113.

Abstract 3626: Genomic evolutionary patterns in matched pre-invasive and invasive lung disease in TRACERx

Introduction: The genomic landscape of pre-invasive lung disease, including AAH/AIS/MIA (atypical adenomatous hyperplasia, adenocarcinoma in situ, minimally invasive carcinoma) and squamous CIS (carcinoma in situ) which are considered to be precursors to lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), has been profiled to a limited degree, due to the lack of matched samples within the same patient. Using TRACERx study we investigated the phylogenetic evolutionary patterns between matched pre-invasive and invasive lesions.

Methods: Post-operative pathology reports for 746 primary invasive tumors collected within TRACERx were screened to identify pre-invasive lesions that had been resected at the time of primary surgery. 50 pre-invasive lesions (21 AAH, 7 AIS, 6 MIA, 16 CIS) from 36 pts were subjected to whole exome sequencing with 119 matched tumor regions from 22 LUAD, 13 LUSC and 1 pleomorphic carcinoma. Phylogenetic relationships between pre-invasive and invasive lesions, timing of clonal divergence, mutational processes were investigated.

Results: Two major types of phylogenetic relationships were identified based on whether pre-invasive and invasive lesions shared a somatic common ancestor (SCA group; 7/22 LUAD, 11/13 LUSC) or not (non-SCA group; 15/22 LUAD, 2/13 LUSC, 1/1 pleomorphic carcinoma). Within SCA group, two evolutionary patterns were identified based on whether only clonal mutations or clonal and subclonal mutations were shared between pre-invasive and invasive lesions. 3/16 SCA pre-invasive lesions from ex-smokers were found to diverge from the invasive tumor years prior to diagnosis. Compared with non-SCA, SCA pre-invasive lesions harbored elevated mutational burden, APOBEC mutagenesis, chromosomal instability featured by increased loss of heterozygosity and somatic copy number alterations (SCNAs). Whole genome doubling was only detected in SCA pre-invasive lesions. In SCA LUAD, 3/7 exhibited clonal TP53 mutations, 3/7 exhibited clonal co-mutations of KEAP1 and STK11. In 5/15 non-SCA LUADs harboring a KRAS mutation, convergent KRAS mutation was detected in 4 matched pre-invasive and invasive lesions. Clonal focal gains on 3q21-29 (containing PIK3CA, ATR, SOX2) were detected in 10/11 SCA LUSC, suggesting that 3q gains may represent early events in tumor initiation. In the non-SCA group, convergent SCNAs encompassing oncogenes (PIK3CA, SOX2, FGFR3) or tumor suppressor genes (STK11, KEAP1, MGA) were detected.

Conclusions: We demonstrate that matched pre-invasive and invasive lesions fall in two distinct phylogenetic evolutionary groups: those that have a shared somatic common ancestor and those that do not. SCA pre-invasive lesions exhibit elevated APOBEC mutagenesis and chromosomal instability, shedding some light on the process of malignant transformation.

Citation Format: Haoran Zhai, Clare Puttick, David A. Moore, Michelle Dietzen, Sophia Ward, Maise Al Bakir, Thomas Watkins, Andrew Rowan, Selvaraju Veeriah, Robert Hynds, Oriol Pich, Nnennaya Kanu, TRACERx Consortium, Nicholas McGranahan, Charles Swanton, Mariam Jamal-Hanjani. Genomic evolutionary patterns in matched pre-invasive and invasive lung disease in TRACERx [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 3626.

Abstract LB504: Automated grading of growth patterns in lung adenocarcinoma-from TRACERx to LATTICe-A

Lung adenocarcinoma exhibits distinct growth patterns (WHO, 2021) and the International Association for the Study of Lung Cancer (IASLC) grading system, based on the nature and proportion of histologic subtypes, is highly prognostic (Moreira et al. 2020). However, both recognition and quantification of growth patterns suffer from high interobserver variability among pathologists. Here, we present a large-scale application to automate the segmentation of histologic patterns and reproduce the IASLC grading system to stratify patients and predict prognosis.

A deep learning model was trained to recognize and segment 6 histologic patterns (lepidic, acinar, papillary, micropapillary, solid, and cribriform) on 49 whole-slide images from TRACERx (AbdulJabbar et al. 2020). This model was directly applied to an independent cohort, consisting of 4324 hematoxylin and eosin-stained sections from 970 patients (the Leicester Archival Thoracic Tumor Investigatory Cohort, Moore et al. 2019).

Growth pattern segmentation performance was first evaluated against 2433 hand annotations covering 6 patterns from 9 images at a pixel level using Dice coefficient. The average Dice was 0.502. Predicted predominant pattern per tumor was then compared to a subspecialty pathologist, achieving an overall agreement (51%), comparable to the interobserver rate among pathologists (52%, Boland et al. 2017). Discordant cases were more heterogeneous (p=4.5e-10, Shannon diversity based on pathological scores), underscoring the challenges posed by intratumor heterogeneity.

Patients with a high proportion of micropapillary in the tumor, identified by deep learning, had significantly worse relapse-free survival (RFS) in multivariate analyses including clinical parameters (p=0.00127, Hazard Ratio (HR)=6.4, 95% confidence interval (CI)=2.07-19.8, n=827), consistent with previous publication (Cha et al. 2014). The Kaplan-Meier curve for RFS was significantly differentiated with both automated and pathological IASLC grading (p&lt;0.0001). Moreover, patients with predominantly high-grade patterns (solid, micropapillary, cribriform) identified by deep learning had significantly reduced RFS (p=6.22e-4, HR=1.5, 95% CI=1.18-1.8, n=970). The prognostic effect was stronger using IASLC grading (cutoff: 20%, p=5.56e-6, HR=1.7, 95% CI=1.36-2.2), comparable to the pathological score at IASLC grade 3 (cutoff: 20%, p=2.41e-5, HR=1.8, 95% CI=1.35-2.3). A similar performance was observed for overall survival regarding above analyses.

To the best of our knowledge, this study represents the largest application of deep learning to recognize tumor growth patterns in lung adenocarcinoma. Histologically heterogeneous growth patterns can be automatically identified using a method trained on an independent cohort. Automated tumor grading is significantly associated with patient outcomes, supporting its potential clinical utility.

Citation Format: Xiaoxi Pan, Khalid AbdulJabbar, Jose Coelho-Lima, Anca-Ioana Grapa, Hanyun Zhang, Ho Kwan Alvin Cheung, Sarah J. Aitken, David A. Moore, Charles Swanton, John Le Quesne, Yinyin Yuan. Automated grading of growth patterns in lung adenocarcinoma-from TRACERx to LATTICe-A [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 LB504.

Expanding Therapeutic Opportunities for Extrapulmonary Neuroendocrine Carcinoma

Poorly differentiated neuroendocrine carcinomas (PD-NEC) are rare cancers garnering interest as they become more commonly encountered in the clinic. This is due to improved diagnostic methods and the increasingly observed phenomenon of "NE lineage plasticity," whereby nonneuroendocrine (non-NE) epithelial cancers transition to aggressive NE phenotypes after targeted treatment. Effective treatment options for patients with PD-NEC are challenging for several reasons. This includes a lack of targetable, recurrent molecular drivers, a paucity of patient-relevant preclinical models to study biology and test novel therapeutics, and the absence of validated biomarkers to guide clinical management. Although advances have been made pertaining to molecular subtyping of small cell lung cancer (SCLC), a PD-NEC of lung origin, extrapulmonary (EP)-PD-NECs remain understudied. This review will address emerging SCLC-like, same-organ non-NE cancer-like and tumor-type-agnostic biological vulnerabilities of EP-PD-NECs, with the potential for therapeutic exploitation. The hypotheses surrounding the origin of these cancers and how "NE lineage plasticity" can be leveraged for therapeutic purposes are discussed. SCLC is herein proposed as a paradigm for supporting progress toward precision medicine in EP-PD-NECs. The aim of this review is to provide a thorough portrait of the current knowledge of EP-PD-NEC biology, with a view to informing new avenues for research and future therapeutic opportunities in these cancers of unmet need.

A case report of transmission and disease caused by Mycobacterium caprae and Mycobacterium bovis in Lima, Peru

BACKGROUND

The Tuberculosis (TB) burden in Peru is significant with respect to both disease morbidity and mortality. Furthermore the recent diversification of farming enterprise to include a wide range of animal species has necessitated the consideration of members of the Mycobacterium Tuberculosis Complex (MTBC) with the potential for zoonotic transmission. M. bovis and M. caprae, a lesser known member of the MTBC exhibit an exceptionally wide host spectrum in animals and are capable of causing disease in humans. M. bovis has a predictable resistance profile which includes resistance to pyrazinamide. Thus, failure to identify M. bovis as the causative agent in reported TB cases leads to higher levels of treatment failure and contributes to the transmission of drug-resistant TB.

CASE PRESENTATION

Reported here are the clinical presentations, investigations and treatment histories of two patients identified from a population level genotyping study in Lima, Peru that were at the time of treatment thought to be M. tuberculosis patients but in retrospect were spectated using whole genome sequencing as M. caprae and M. Bovis.

CONCLUSIONS

The cases reported here constitute convincing evidence that M. caprae and M. bovis are causative agents of TB infection in humans in Peru and underscore the importance of species-level MTBC member identification to effectively control and treat zoonotic TB. Furthermore these cases highlight the challenges of using clinical risk factors to identify cases of zoonotic TB in humans as their clinical presentation and transmission history is often difficult to distinguish from anthroponotic TB.

Determinants of anti-PD-1 response and resistance in clear cell renal cell carcinoma

ADAPTeR is a prospective, phase II study of nivolumab (anti-PD-1) in 15 treatment-naive patients (115 multiregion tumor samples) with metastatic clear cell renal cell carcinoma (ccRCC) aiming to understand the mechanism underpinning therapeutic response. Genomic analyses show no correlation between tumor molecular features and response, whereas ccRCC-specific human endogenous retrovirus expression indirectly correlates with clinical response. T cell receptor (TCR) analysis reveals a significantly higher number of expanded TCR clones pre-treatment in responders suggesting pre-existing immunity. Maintenance of highly similar clusters of TCRs post-treatment predict response, suggesting ongoing antigen engagement and survival of families of T cells likely recognizing the same antigens. In responders, nivolumab-bound CD8+ T cells are expanded and express GZMK/B. Our data suggest nivolumab drives both maintenance and replacement of previously expanded T cell clones, but only maintenance correlates with response. We hypothesize that maintenance and boosting of a pre-existing response is a key element of anti-PD-1 mode of action.

Optimising fusion detection through sequential DNA and RNA molecular profiling of non-small cell lung cancer

OBJECTIVES

There is an increasing number of driver fusions in NSCLC which are amenable to targeted therapy. Panel testing for fusions is increasingly appropriate but can be costly and requires adequate good quality biopsy material. In light of the typical mutual exclusivity of driver events in NSCLC, the objective of this study was to trial a novel testing pathway, supported by industrial collaboration, in which only patients negative for driver mutations on DNA-NGS were submitted for fusion panel analysis.

MATERIALS AND METHODS

Over 18 months, all patients from a single centre with non-squamous NSCLC were submitted for DNA-NGS, plus ALK and ROS1 immunohistochemistry +/- FISH. Those which were negative for a driver mutation were then recalled for RNA panel testing.

RESULTS

307 samples were referred for DNA-NGS mutation analysis, of which, 10% of cases were unsuitable for or failed DNA-NGS analysis. Driver mutations were detected in 61% (167/275) of all those successfully tested. Of those without a driver mutation and with some remaining tissue available, 28% had insufficient tissue/extracted RNA or failed RNA-NGS. Of those successfully tested, 24% (17/72) had a fusion gene detected involving either ALK, ROS, MET, RET, FGFR or EGFR. Overall, 66% (184/277) of patients had a driver event detected through the combination of DNA and RNA panels.

CONCLUSION

Sequential DNA and RNA based molecular profiling increased the efficacy of detecting fusion driven NSCLCs. Continued optimisation of tissue procurement, handling and the diagnostic pathways for gene fusion analysis is necessary to reduce analysis failure rates and improve detection rate for treatment with the next generation of small molecule inhibitors.

Using DNA sequencing data to quantify T cell fraction and therapy response

The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy1,2. 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.

Metastatic mandibular ameloblastoma of the lung ten years after primary resection: A rare case report

Ameloblastoma is a rare odontogenic neoplasm of the jaw. It usually behaves as a benign, slow growing tumour of the oral cavity with a high recurrence rate, especially when it is inadequately resected. A small proportion of ameloblastomas metastasize to distant organs, with lungs representing the most common site of metastatic spread. In this report, we present the case of a middle-aged man with two pulmonary nodules and a history of mandibular ameloblastoma excised 10 years prior to this radiological finding. Following resection and histopathological analysis of the lung lesion, a diagnosis of metastatic ameloblastoma was confirmed. No local recurrence of the primary tumour was identified. At 1-year follow-up, the patient had no evidence of local or metastatic disease.

Transcriptional perturbation of protein arginine methyltransferase-5 exhibits MTAP-selective oncosuppression

We hypothesized that small molecule transcriptional perturbation could be harnessed to target a cellular dependency involving protein arginine methyltransferase 5 (PRMT5) in the context of methylthioadenosine phosphorylase (MTAP) deletion, seen frequently in malignant pleural mesothelioma (MPM). Here we show, that MTAP deletion is negatively prognostic in MPM. In vitro, the off-patent antibiotic Quinacrine efficiently suppressed PRMT5 transcription, causing chromatin remodelling with reduced global histone H4 symmetrical demethylation. Quinacrine phenocopied PRMT5 RNA interference and small molecule PRMT5 inhibition, reducing clonogenicity in an MTAP-dependent manner. This activity required a functional PRMT5 methyltransferase as MTAP negative cells were rescued by exogenous wild type PRMT5, but not a PRMT5E444Q methyltransferase-dead mutant. We identified c-jun as an essential PRMT5 transcription factor and a probable target for Quinacrine. Our results therefore suggest that small molecule-based transcriptional perturbation of PRMT5 can leverage a mutation-selective vulnerability, that is therapeutically tractable, and has relevance to 9p21 deleted cancers including MPM.

Inclusion of multiple high-risk histopathological criteria improves the prediction of adjuvant chemotherapy efficacy in lung adenocarcinoma

Aims

The decision to consider adjuvant chemotherapy (AC) for non‐small cell lung cancer is currently governed by clinical stage. This study aims to assess other routinely collected pathological variables related to metastasis and survival for their ability to predict the efficacy of AC in lung adenocarcinoma.

Methods and results

A retrospective single‐centre series of 620 resected lung non‐mucinous adenocarcinoma cases from 2005 to 2015 was used. Digital images of all slides were subjected to central review, and data on tumour histopathology, AC treatment and patient survival were compiled. A statistical case matching approach was used to counter selection bias. Several high‐risk pathological criteria predict both pathological nodal involvement and early death: positive vascular invasion status (VI+) (HR = 2.10, P < 0.001), positive visceral pleural invasion status (VPI+) (HR = 2.16, P < 0.001), and solid/micropapillary‐predominant WHO tumour type (SPA/MPPA) (HR = 3.29, P < 0.001). Crucially, these criteria also identify patient groups benefiting from AC (VI + HR = 0.69, P = 0.167, VPI + HR = 0.44, P = 0.004, SPA/MPPA HR = 0.36, P = 0.006). Cases showing VI+/VPI+/SPA/MPPA histology in the absence of AC stage criteria were common (170 of 620 total), and 8 had actually received AC. This group showed much better outcomes than equivalent untreated cases in matched analysis (3‐year OS 100.0% versus 31.3%). Inclusion of patients with VI+/VPI+/SPA/MPPA histology would increase AC‐eligible patients from 51.0% to 84.0% of non‐mucinous tumours in our cohort.

Conclusions

Our data provide preliminary evidence that the consideration of AC in patients with additional high‐risk pathological indicators may significantly improve outcomes in operable lung adenocarcinoma, and that AC may be currently underused.

Describing motivation for health and treatment decisions and communication choices of calf-care workers on western United States dairies

On large dairy farms, animal health assessments and treatments are made by farm employees. Little is known about how employees make decisions about illness detection or treatment, information critical to improving antimicrobial stewardship. The objectives of this study were to describe calf-care employee motivations for decisions associated with preweaned calf health and treatments, describe on-farm worker communication networks, and determine information sources used by these employees to support their decisions. Personal interviews were conducted with 103 calf-care employees on 28 farms in the western United States. The interview consisted of 10 motivation source type (MST) questions and questions about training, communication and educational opportunities. A latent class analysis created a summary for MST and resulted in 4 classes. Forty-three percent of calf-care employees fell into a class where responses were a combination of internal and intrinsic (personal beliefs or values and task fulfillment, respectively) and 23% were a combination of internal and goal internal (aligned with organizational goals). This latter class aligned health decisions with internal motivation and treatment decisions with goal internal. A network analysis summarized dominant communication relationships and established that feeders and treaters perceived more communication with supervisors than was reciprocated by supervisors, and that there was less communication between workers and management for tasks relative to daily work. Employee training was primarily done by herdsman, calf manager, or coworkers, and information for skill improvement and problem solving was sought from these individuals. Although veterinarians were not often involved in employee training, when they were involved, employees were likely to use them as an information source for skill improvement and problem solving. Few participants had ever used social media, but almost all had a device that could access the internet; more than 60% indicated interest in a social media platform for work-related information. Work motivation for many calf caretakers appeared to be sourced from personal beliefs, values, and job fulfillment, particularly when deciding to treat a sick calf. Investigation and incorporation of beliefs and values in training programs could help with alignment of protocols with actual treatment and further efforts to implement judicious use of antimicrobials.

Pervasive chromosomal instability and karyotype order in tumour evolution

Chromosomal instability in cancer consists of dynamic changes to the number and structure of chromosomes1,2. The resulting diversity in somatic copy number alterations (SCNAs) may provide the variation necessary for tumour evolution1,3,4. Here we use multi-sample phasing and SCNA analysis of 1,421 samples from 394 tumours across 22 tumour types to show that continuous chromosomal instability results in pervasive SCNA heterogeneity. Parallel evolutionary events, which cause disruption in the same genes (such as BCL9, MCL1, ARNT (also known as HIF1B), TERT and MYC) within separate subclones, were present in 37% of tumours. Most recurrent losses probably occurred before whole-genome doubling, that was found as a clonal event in 49% of tumours. However, loss of heterozygosity at the human leukocyte antigen (HLA) locus and loss of chromosome 8p to a single haploid copy recurred at substantial subclonal frequencies, even in tumours with whole-genome doubling, indicating ongoing karyotype remodelling. Focal amplifications that affected chromosomes 1q21 (which encompasses BCL9, MCL1 and ARNT), 5p15.33 (TERT), 11q13.3 (CCND1), 19q12 (CCNE1) and 8q24.1 (MYC) were frequently subclonal yet appeared to be clonal within single samples. Analysis of an independent series of 1,024 metastatic samples revealed that 13 focal SCNAs were enriched in metastatic samples, including gains in chromosome 8q24.1 (encompassing MYC) in clear cell renal cell carcinoma and chromosome 11q13.3 (encompassing CCND1) in HER2+ breast cancer. Chromosomal instability may enable the continuous selection of SCNAs, which are established as ordered events that often occur in parallel, throughout tumour evolution.

Immune Surveillance in Clinical Regression of Preinvasive Squamous Cell Lung Cancer

Before squamous cell lung cancer develops, precancerous lesions can be found in the airways. From longitudinal monitoring, we know that only half of such lesions become cancer, whereas a third spontaneously regress. Although recent studies have described the presence of an active immune response in high-grade lesions, the mechanisms underpinning clinical regression of precancerous lesions remain unknown. Here, we show that host immune surveillance is strongly implicated in lesion regression. Using bronchoscopic biopsies from human subjects, we find that regressive carcinoma in situ lesions harbor more infiltrating immune cells than those that progress to cancer. Moreover, molecular profiling of these lesions identifies potential immune escape mechanisms specifically in those that progress to cancer: antigen presentation is impaired by genomic and epigenetic changes, CCL27-CCR10 signaling is upregulated, and the immunomodulator TNFSF9 is downregulated. Changes appear intrinsic to the carcinoma in situ lesions, as the adjacent stroma of progressive and regressive lesions are transcriptomically similar. SIGNIFICANCE: Immune evasion is a hallmark of cancer. For the first time, this study identifies mechanisms by which precancerous lesions evade immune detection during the earliest stages of carcinogenesis and forms a basis for new therapeutic strategies that treat or prevent early-stage lung cancer.See related commentary by Krysan et al., p. 1442.This article is highlighted in the In This Issue feature, p. 1426.

Publisher Correction: A clonal expression biomarker associates with lung cancer mortality

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Geospatial immune variability illuminates differential evolution of lung adenocarcinoma

Remarkable progress in molecular analyses has improved our understanding of the evolution of cancer cells toward immune escape1-5. However, the spatial configurations of immune and stromal cells, which may shed light on the evolution of immune escape across tumor geographical locations, remain unaddressed. We integrated multiregion exome and RNA-sequencing (RNA-seq) data with spatial histology mapped by deep learning in 100 patients with non-small cell lung cancer from the TRACERx cohort6. Cancer subclones derived from immune cold regions were more closely related in mutation space, diversifying more recently than subclones from immune hot regions. In TRACERx and in an independent multisample cohort of 970 patients with lung adenocarcinoma, tumors with more than one immune cold region had a higher risk of relapse, independently of tumor size, stage and number of samples per patient. In lung adenocarcinoma, but not lung squamous cell carcinoma, geometrical irregularity and complexity of the cancer-stromal cell interface significantly increased in tumor regions without disruption of antigen presentation. Decreased lymphocyte accumulation in adjacent stroma was observed in tumors with low clonal neoantigen burden. Collectively, immune geospatial variability elucidates tumor ecological constraints that may shape the emergence of immune-evading subclones and aggressive clinical phenotypes.

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

The T cell differentiation landscape is shaped by tumour mutations in lung cancer

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.

The path to a better biomarker: application of a risk management framework for the implementation of PD-L1 and TILs as immuno-oncology biomarkers in breast cancer clinical trials and daily practice

Immune checkpoint inhibitor therapies targeting PD-1/PD-L1 are now the standard of care in oncology across several hematologic and solid tumor types, including triple negative breast cancer (TNBC). Patients with metastatic or locally advanced TNBC with PD-L1 expression on immune cells occupying ≥1% of tumor area demonstrated survival benefit with the addition of atezolizumab to nab-paclitaxel. However, concerns regarding variability between immunohistochemical PD-L1 assay performance and inter-reader reproducibility have been raised. High tumor-infiltrating lymphocytes (TILs) have also been associated with response to PD-1/PD-L1 inhibitors in patients with breast cancer (BC). TILs can be easily assessed on hematoxylin and eosin-stained slides and have shown reliable inter-reader reproducibility. As an established prognostic factor in early stage TNBC, TILs are soon anticipated to be reported in daily practice in many pathology laboratories worldwide. Because TILs and PD-L1 are parts of an immunological spectrum in BC, we propose the systematic implementation of combined PD-L1 and TIL analyses as a more comprehensive immuno-oncological biomarker for patient selection for PD-1/PD-L1 inhibition-based therapy in patients with BC. Although practical and regulatory considerations differ by jurisdiction, the pathology community has the responsibility to patients to implement assays that lead to optimal patient selection. We propose herewith a risk-management framework that may help mitigate the risks of suboptimal patient selection for immuno-therapeutic approaches in clinical trials and daily practice based on combined TILs/PD-L1 assessment in BC. © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A Brief Mindfulness Intervention for Medically Hospitalized Patients with Acute Pain: A Pilot Randomized Clinical Trial

OBJECTIVE

Mindfulness interventions may be beneficial for patients with chronic pain; however, the effects for acute pain are not understood. The purpose of this study was to pilot test a brief mindfulness intervention for acute pain and stress for patients in an inpatient medical setting.

DESIGN

Pilot randomized clinical trial.

SETTING

An inpatient Acute Care Surgery service at an urban hospital.

SUBJECTS

Sixty patients with acute pain were randomly selected and agreed to participate.

METHODS

Interested patients consented to the study and were randomized to the 10-minute intervention (i.e., mindfulness strategy) or comparison group (i.e., education on the Gate Control Theory of Pain). Participants completed pre- and post-assessment measures on pain severity and stress.

RESULTS

Preliminary results showed that within the intervention and comparison groups, participants experienced decreases in pain from pre- to post-intervention (P = 0.002 and 0.005, respectively). Within the intervention group, there was a significant decrease in stress from pre- to post-intervention (P = 0.001). There were no significant changes for stress within the comparison group (P = 0.32). There were no significant differences between the intervention and comparison groups for pain (P = 0.44) or stress (P = 0.07) at post-intervention, although Cohen's d effect sizes were small to medium for pain and stress, respectively.

CONCLUSIONS

A brief mindfulness intervention for medically hospitalized patients with acute pain may decrease pain and stress. Future research should examine this intervention with a fully powered, larger sample to examine efficacy.

A clonal expression biomarker associates with lung cancer mortality

An aim of molecular biomarkers is to stratify patients with cancer into disease subtypes predictive of outcome, improving diagnostic precision beyond clinical descriptors such as tumor stage1. Transcriptomic intratumor heterogeneity (RNA-ITH) has been shown to confound existing expression-based biomarkers across multiple cancer types2-6. Here, we analyze multi-region whole-exome and RNA sequencing data for 156 tumor regions from 48 patients enrolled in the TRACERx study to explore and control for RNA-ITH in non-small cell lung cancer. We find that chromosomal instability is a major driver of RNA-ITH, and existing prognostic gene expression signatures are vulnerable to tumor sampling bias. To address this, we identify genes expressed homogeneously within individual tumors that encode expression modules of cancer cell proliferation and are often driven by DNA copy-number gains selected early in tumor evolution. Clonal transcriptomic biomarkers overcome tumor sampling bias, associate with survival independent of clinicopathological risk factors, and may provide a general strategy to refine biomarker design across cancer types.

Personalized Detection of Circulating Tumor DNA Antedates Breast Cancer Metastatic Recurrence

PURPOSE

Up to 30% of patients with breast cancer relapse after primary treatment. There are no sensitive and reliable tests to monitor these patients and detect distant metastases before overt recurrence. Here, we demonstrate the use of personalized circulating tumor DNA (ctDNA) profiling for detection of recurrence in breast cancer.

EXPERIMENTAL DESIGN

Forty-nine primary patients with breast cancer were recruited following surgery and adjuvant therapy. Plasma samples (n = 208) were collected every 6 months for up to 4 years. Personalized assays targeting 16 variants selected from primary tumor whole-exome data were tested in serial plasma for the presence of ctDNA by ultradeep sequencing (average >100,000X).

RESULTS

Plasma ctDNA was detected ahead of clinical or radiologic relapse in 16 of the 18 relapsed patients (sensitivity of 89%); metastatic relapse was predicted with a lead time of up to 2 years (median, 8.9 months; range, 0.5-24.0 months). None of the 31 nonrelapsing patients were ctDNA-positive at any time point across 156 plasma samples (specificity of 100%). Of the two relapsed patients who were not detected in the study, the first had only a local recurrence, whereas the second patient had bone recurrence and had completed chemotherapy just 13 days prior to blood sampling.

CONCLUSIONS

This study demonstrates that patient-specific ctDNA analysis can be a sensitive and specific approach for disease surveillance for patients with breast cancer. More importantly, earlier detection of up to 2 years provides a possible window for therapeutic intervention.

Abstract 2678: A clonal expression biomarker improves prognostic accuracy: TRACERx lung

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.

A retrospective cohort study comparing dairy calf treatment decisions by farm personnel with veterinary observations of clinical signs

Antimicrobials are frequently administered to calves with diarrhea, despite evidence suggesting questionable efficacy. Even if efficacious, providing the appropriate therapy to an animal requires accurate disease detection. The objective of this study was to use previously collected data and compare clinical scoring by a veterinarian to treatment decisions by on-farm personnel. Data describing daily clinical scores and farm treatments were previously collected from 4 farms for calves from birth to age 28 d. In this data set, a total of 460 calves were enrolled. Daily observations and clinical assessments were made on each farm by the same veterinarian, for a total of 12,101 calf observation days. Farm personnel made all treatment decisions based on their own observations, and these treatments were recorded by study personnel. Overall, the cumulative incidence of a calf exhibiting at least one abnormal clinical sign over the 28-d observation period was 0.93, with cumulative incidences of 0.85 and 0.33 for diarrhea and dehydration, respectively. The cumulative incidence of any treatment (including antibiotics and electrolytes) was 0.85, although the majority of treatments used an antimicrobial. The farm-specific probabilities that a calf with clinical signs of dehydration or diarrhea, respectively, received fluid or electrolyte therapy ranged from 0.08 to 0.27 and 0.03 to 0.12. These probabilities were greater for the day a clinical sign was first observed. The farm-specific probabilities that a calf with clinical signs of diarrhea received an antimicrobial was 0.23 to 0.65, and the probability that a calf exhibiting clinical signs of respiratory disease received an antimicrobial was 0.33 to 0.76. The first observation of diarrhea had similar probabilities to those for all observations of diarrhea. There was greater probability of treatment for calves with their first observed abnormal respiratory signs. Probabilities that treatment with antimicrobials, or fluids or electrolytes, was associated with an abnormal clinical sign were low-that is, calves received treatments in the absence of any abnormal clinical signs. This study illustrates incongruity between treatment decisions by calf treaters (the designated personnel on each farm responsible for calf health assessment and treatment decisions) and those of an observer using a clinical scoring system to identify calves with abnormal clinical signs. These findings indicate opportunities and the need for dairy farmers and advisors to evaluate calf treatment protocols, reasons for treatment, and training programs for calf health and disease detection, as well as to develop monitoring programs for treatment protocol compliance and health outcomes following therapy.