Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.

Immune heterogeneity in small-cell lung cancer and vulnerability to immune checkpoint blockade

Atezolizumab (anti-PD-L1), combined with carboplatin and etoposide (CE), is now a standard of care for extensive-stage small-cell lung cancer (ES-SCLC). A clearer understanding of therapeutically relevant SCLC subsets could identify rational combination strategies and improve outcomes. We conduct transcriptomic analyses and non-negative matrix factorization on 271 pre-treatment patient tumor samples from IMpower133 and identify four subsets with general concordance to previously reported SCLC subtypes (SCLC-A, -N, -P, and -I). Deeper investigation into the immune heterogeneity uncovers two subsets with differing neuroendocrine (NE) versus non-neuroendocrine (non-NE) phenotypes, demonstrating immune cell infiltration hallmarks. The NE tumors with low tumor-associated macrophage (TAM) but high T-effector signals demonstrate longer overall survival with PD-L1 blockade and CE versus CE alone than non-NE tumors with high TAM and high T-effector signal. Our study offers a clinically relevant approach to discriminate SCLC patients likely benefitting most from immunotherapies and highlights the complex mechanisms underlying immunotherapy responses.

Anti-TIGIT antibody improves PD-L1 blockade through myeloid and Treg cells

Tiragolumab, an anti-TIGIT antibody with an active IgG1κ Fc, demonstrated improved outcomes in the phase 2 CITYSCAPE trial (ClinicalTrials.gov: NCT03563716 ) when combined with atezolizumab (anti-PD-L1) versus atezolizumab alone1. However, there remains little consensus on the mechanism(s) of response with this combination2. Here we find that a high baseline of intratumoural macrophages and regulatory T cells is associated with better outcomes in patients treated with atezolizumab plus tiragolumab but not with atezolizumab alone. Serum sample analysis revealed that macrophage activation is associated with a clinical benefit in patients who received the combination treatment. In mouse tumour models, tiragolumab surrogate antibodies inflamed tumour-associated macrophages, monocytes and dendritic cells through Fcγ receptors (FcγR), in turn driving anti-tumour CD8+ T cells from an exhausted effector-like state to a more memory-like state. These results reveal a mechanism of action through which TIGIT checkpoint inhibitors can remodel immunosuppressive tumour microenvironments, and suggest that FcγR engagement is an important consideration in anti-TIGIT antibody development.

Clinical and molecular characterization of long-term survivors with extensive-stage small cell lung cancer treated with first-line atezolizumab plus carboplatin and etoposide

OBJECTIVES

In the Phase I/III IMpower133 study, first-line atezolizumab plus carboplatin and etoposide (CP/ET) treatment for extensive-stage small cell lung cancer (ES-SCLC) significantly improved overall survival (OS) and progression-free survival versus placebo plus CP/ET. We explored patient and disease characteristics associated with long-term survival in IMpower133, and associations of differential gene expression and SCLC-A (ASCL1-driven), SCLC-N (NEUROD1-driven), SCLC-P (POU2F3-driven), and SCLC-inflamed (SCLC-I) transcriptional subtypes with long-term survival.

MATERIALS AND METHODS

Patients with previously untreated ES-SCLC were randomized 1:1 to four 21-day cycles of CP/ET with atezolizumab or placebo. Long-term survivors (LTS) were defined as patients who lived ≥ 18 months post randomization. A generalized linear model was used to evaluate the odds of living ≥ 18 months. Differential gene expression was analyzed using RNA-sequencing data in LTS and non-LTS. OS was assessed by T-effector and B-cell gene signature expression. Distribution of SCLC transcriptional subtypes was assessed in LTS and non-LTS.

RESULTS

More LTS were in the atezolizumab arm (34%) than in the placebo arm (20%). The odds ratio for living ≥ 18 months in the atezolizumab arm versus the placebo arm was 2.1 (P < 0.03). Enhanced immune-related signaling was seen in LTS in both arms. Exploratory OS analyses showed atezolizumab treatment benefit versus placebo across T-effector and B-cell gene signature expression subgroups. A higher proportion of LTS than non-LTS in both arms had the SCLC-I subtype; this difference was particularly pronounced in the atezolizumab arm.

CONCLUSION

These exploratory analyses suggest that long-term survival is more likely with atezolizumab than placebo in ES-SCLC, confirming the treatment benefit of the IMpower133 regimen.

CLINICALTRIAL

gov Identifier: NCT02763579.

The ectonucleotidase CD39 identifies tumor-reactive CD8+ T cells predictive of immune checkpoint blockade efficacy in human lung cancer

Improved identification of anti-tumor T cells is needed to advance cancer immunotherapies. CD39 expression is a promising surrogate of tumor-reactive CD8+ T cells. Here, we comprehensively profiled CD39 expression in human lung cancer. CD39 expression enriched for CD8+ T cells with features of exhaustion, tumor reactivity, and clonal expansion. Flow cytometry of 440 lung cancer biospecimens revealed weak association between CD39+ CD8+ T cells and tumoral features, such as programmed death-ligand 1 (PD-L1), tumor mutation burden, and driver mutations. Immune checkpoint blockade (ICB), but not cytotoxic chemotherapy, increased intratumoral CD39+ CD8+ T cells. Higher baseline frequency of CD39+ CD8+ T cells conferred improved clinical outcomes from ICB therapy. Furthermore, a gene signature of CD39+ CD8+ T cells predicted benefit from ICB, but not chemotherapy, in a phase III clinical trial of non-small cell lung cancer. These findings highlight CD39 as a proxy of tumor-reactive CD8+ T cells in human lung cancer.

Genomic Profiling of Bronchoalveolar Lavage Fluid in Lung Cancer

Genomic profiling of bronchoalveolar lavage (BAL) samples may be useful for tumor profiling and diagnosis in the clinic. Here, we compared tumor-derived mutations detected in BAL samples from subjects with non-small cell lung cancer (NSCLC) to those detected in matched plasma samples. Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) was used to genotype DNA purified from BAL, plasma, and tumor samples from patients with NSCLC. The characteristics of cell-free DNA (cfDNA) isolated from BAL fluid were first characterized to optimize the technical approach. Somatic mutations identified in tumor were then compared with those identified in BAL and plasma, and the potential of BAL cfDNA analysis to distinguish lung cancer patients from risk-matched controls was explored. In total, 200 biofluid and tumor samples from 38 cases and 21 controls undergoing BAL for lung cancer evaluation were profiled. More tumor variants were identified in BAL cfDNA than plasma cfDNA in all stages (P < 0.001) and in stage I to II disease only. Four of 21 controls harbored low levels of cancer-associated driver mutations in BAL cfDNA [mean variant allele frequency (VAF) = 0.5%], suggesting the presence of somatic mutations in nonmalignant airway cells. Finally, using a Random Forest model with leave-one-out cross-validation, an exploratory BAL genomic classifier identified lung cancer with 69% sensitivity and 100% specificity in this cohort and detected more cancers than BAL cytology. Detecting tumor-derived mutations by targeted sequencing of BAL cfDNA is technically feasible and appears to be more sensitive than plasma profiling. Further studies are required to define optimal diagnostic applications and clinical utility.

SIGNIFICANCE

Hybrid-capture, targeted deep sequencing of lung cancer mutational burden in cell-free BAL fluid identifies more tumor-derived mutations with increased allele frequencies compared with plasma cell-free DNA. See related commentary by Rolfo et al., p. 2826.

Inferring gene expression from cell-free DNA fragmentation profiles

Profiling of circulating tumor DNA (ctDNA) in the bloodstream shows promise for noninvasive cancer detection. Chromatin fragmentation features have previously been explored to infer gene expression profiles from cell-free DNA (cfDNA), but current fragmentomic methods require high concentrations of tumor-derived DNA and provide limited resolution. Here we describe promoter fragmentation entropy as an epigenomic cfDNA feature that predicts RNA expression levels at individual genes. We developed 'epigenetic expression inference from cell-free DNA-sequencing' (EPIC-seq), a method that uses targeted sequencing of promoters of genes of interest. Profiling 329 blood samples from 201 patients with cancer and 87 healthy adults, we demonstrate classification of subtypes of lung carcinoma and diffuse large B cell lymphoma. Applying EPIC-seq to serial blood samples from patients treated with PD-(L)1 immune-checkpoint inhibitors, we show that gene expression profiles inferred by EPIC-seq are correlated with clinical response. Our results indicate that EPIC-seq could enable noninvasive, high-throughput tissue-of-origin characterization with diagnostic, prognostic and therapeutic potential.

Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer

Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients, based on their significant overall survival (OS) benefit. Using transcriptomic analysis of 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy from two large randomized clinical trials, we find a significant B cell association with extended OS with PD-L1 blockade, independent of CD8⁺ T cell signals. We then derive gene signatures corresponding to the dominant B cell subsets present in NSCLC from single-cell RNA sequencing (RNA-seq) data. Importantly, we find increased plasma cell signatures to be predictive of OS in patients treated with atezolizumab, but not chemotherapy. B and plasma cells are also associated with the presence of tertiary lymphoid structures and organized lymphoid aggregates. Our results suggest an important contribution of B and plasma cells to the efficacy of PD-L1 blockade in NSCLC.

Single-cell analysis of human non-small cell lung cancer lesions refines tumor classification and patient stratification

Immunotherapy is a mainstay of non-small cell lung cancer (NSCLC) management. While tumor mutational burden (TMB) correlates with response to immunotherapy, little is known about the relationship between the baseline immune response and tumor genotype. Using single-cell RNA sequencing, we profiled 361,929 cells from 35 early-stage NSCLC lesions. We identified a cellular module consisting of PDCD1⁺CXCL13⁺ activated T cells, IgG⁺ plasma cells, and SPP1⁺ macrophages, referred to as the lung cancer activation module (LCAM^hi). We confirmed LCAM^hi enrichment in multiple NSCLC cohorts, and paired CITE-seq established an antibody panel to identify LCAM^hi lesions. LCAM presence was found to be independent of overall immune cell content and correlated with TMB, cancer testis antigens, and TP53 mutations. High baseline LCAM scores correlated with enhanced NSCLC response to immunotherapy even in patients with above median TMB, suggesting that immune cell composition, while correlated with TMB, may be a nonredundant biomarker of response to immunotherapy.

Detecting Liquid Remnants of Solid Tumors: Circulating Tumor DNA Minimal Residual Disease

Growing evidence demonstrates that circulating tumor DNA (ctDNA) minimal residual disease (MRD) following treatment for solid tumors predicts relapse. These results suggest that ctDNA MRD could identify candidates for adjuvant therapy and measure response to such treatment. Importantly, factors such as assay type, amount of ctDNA release, and technical and biological background can affect ctDNA MRD results. Furthermore, the clinical utility of ctDNA MRD for treatment personalization remains to be fully established. Here, we review the evidence supporting the value of ctDNA MRD in solid cancers and highlight key considerations in the application of this potentially transformative biomarker.

SIGNIFICANCE

ctDNA analysis enables detection of MRD and predicts relapse after definitive treatment for solid cancers, thereby promising to revolutionize personalization of adjuvant and consolidation therapies.

The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma

Biological heterogeneity in diffuse large B cell lymphoma (DLBCL) is partly driven by cell-of-origin subtypes and associated genomic lesions, but also by diverse cell types and cell states in the tumor microenvironment (TME). However, dissecting these cell states and their clinical relevance at scale remains challenging. Here, we implemented EcoTyper, a machine-learning framework integrating transcriptome deconvolution and single-cell RNA sequencing, to characterize clinically relevant DLBCL cell states and ecosystems. Using this approach, we identified five cell states of malignant B cells that vary in prognostic associations and differentiation status. We also identified striking variation in cell states for 12 other lineages comprising the TME and forming cell state interactions in stereotyped ecosystems. While cell-of-origin subtypes have distinct TME composition, DLBCL ecosystems capture clinical heterogeneity within existing subtypes and extend beyond cell-of-origin and genotypic classes. These results resolve the DLBCL microenvironment at systems-level resolution and identify opportunities for therapeutic targeting (https://ecotyper.stanford.edu/lymphoma).

Abstract 22: A novel, inflamed small cell lung cancer transcriptional subtype, SCLC-I, defines a subset of patients with distinct immunotherapy vulnerability

Background

Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy with dismal survival outcomes and no established predictive biomarkers. The landmark randomized, phase III IMpower133 trial established the new frontline standard of care for extensive-stage SCLC (ES-SCLC) as etoposide/platinum (EP) plus immune checkpoint blockade (ICB) [anti-PD-L1; atezolizumab (atezo)] based on an overall survival (OS) benefit compared to EP plus placebo. However, this survival benefit is limited in unselected populations, emphasizing the need for predictive biomarkers. Preclinically, there is emerging evidence of transcriptional heterogeneity among SCLC tumors, but the impact on therapeutic benefit remains undefined. Using non-negative matrix factorization (NMF) analysis of gene expression data from 81 SCLC tumors samples, we previously identified four subtypes, including three defined largely by differential expression of the transcription factors ASCL1 (SCLC-A), NEUROD1 (SCLC-N), and POU2F3 (SCLC-P), and a novel, fourth subtype with low expression of all three transcription factor signatures.

Method and Results

Using transcriptional and proteomic data from patient tumors and tumor-derived models, we molecularly characterized each of the four identified subtypes. The previously undescribed fourth subtype, dubbed SCLC-Inflamed (SCLC-I) showed high expression of non-neuroendocrine transcription factors (e.g. REST) and markers of EMT. Most distinctly, relative to the “cold” immune microenvironment typical of SCLC tumors, SCLC-I tumors possess markedly higher expression of interferon-γ signatures and immune checkpoints, including CD274 (PD-L1). Furthermore, cell type deconvolution using CIBERSORTx identified significantly higher infiltration into SCLC-I tumors by multiple immune cell types including T-cells, NK cells, macrophages, and dendritic cells. We predicted SCLC-I might derive disproportionate benefit from ICB due to its inflamed features. To test this, we applied our NMF-derived gene signature to 276 treatment-naïve, ES-SCLC patient tumors from the IMpower133 trial to assign patient subtype. The distribution of subtypes was as follows: SCLC-A 51%, SCLC-N 23%, SCLC-I 18% and SCLC-P 7%. While there was a trend toward OS benefit with the addition of atezo in each subtype, the benefit was numerically greater in SCLC-I. Specifically, median OS (atezo vs placebo arm) in months (mo) was 18.2 mo vs 10.4 mo for SCLC-I tumors, while median OS for the other three subtypes ranged from 9.6-10.9 mo (atezo arm) and 6.0-10.6 mo (placebo arm).

Conclusion

Unbiased transcriptional analyses identify four subtypes with distinct tumor and immune features. While all subtypes experienced improved OS with addition of anti-PD-L1 to frontline EP, SCLC-I patients appear to experience the most durable benefit.

Citation Format: Carl M. Gay, C. Allison Stewart, Lixia Diao, Barzin Y. Nabet, Junya Fujimoto, Luisa M. Solis, Wei Lu, Yuanxin Xi, Robert J. Cardnell, Natalie I. Vokes, Kavya Ramkumar, Stephen G. Swisher, Jack A. Roth, Bonnie S. Glisson, David S. Shames, Ignacio I. Wistuba, Jing Wang, John Minna, John V. Heymach, Lauren A. Byers. A novel, inflamed small cell lung cancer transcriptional subtype, SCLC-I, defines a subset of patients with distinct immunotherapy vulnerability [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 22.

Short Diagnosis-to-Treatment Interval Is Associated With Higher Circulating Tumor DNA Levels in Diffuse Large B-Cell Lymphoma

PURPOSE

Patients with Diffuse Large B-cell Lymphoma (DLBCL) in need of immediate therapy are largely under-represented in clinical trials. The diagnosis-to-treatment interval (DTI) has recently been described as a metric to quantify such patient selection bias, with short DTI being associated with adverse risk factors and inferior outcomes. Here, we characterized the relationships between DTI, circulating tumor DNA (ctDNA), conventional risk factors, and clinical outcomes, with the goal of defining objective disease metrics contributing to selection bias.

PATIENTS AND METHODS

We evaluated pretreatment ctDNA levels in 267 patients with DLBCL treated across multiple centers in Europe and the United States using Cancer Personalized Profiling by Deep Sequencing. Pretreatment ctDNA levels were correlated with DTI, total metabolic tumor volumes (TMTVs), the International Prognostic Index (IPI), and outcome.

RESULTS

Short DTI was associated with advanced-stage disease (P < .001) and higher IPI (P < .001). We also found an inverse correlation between DTI and TMTV (R_S = -0.37; P < .001). Similarly, pretreatment ctDNA levels were significantly associated with stage, IPI, and TMTV (all P < .001), demonstrating that both DTI and ctDNA reflect disease burden. Notably, patients with shorter DTI had higher pretreatment ctDNA levels (P < .001). Pretreatment ctDNA levels predicted short DTI independent of the IPI (P < .001). Although each risk factor was significantly associated with event-free survival in univariable analysis, ctDNA level was prognostic of event-free survival independent of DTI and IPI in multivariable Cox regression (ctDNA: hazard ratio, 1.5; 95% CI [1.2 to 2.0]; IPI: 1.1 [0.9 to 1.3]; -DTI: 1.1 [1.0 to 1.2]).

CONCLUSION

Short DTI largely reflects baseline tumor burden, which can be objectively measured using pretreatment ctDNA levels. Pretreatment ctDNA levels therefore have utility for quantifying and guarding against selection biases in prospective DLBCL clinical trials.

Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities

Despite molecular and clinical heterogeneity, small cell lung cancer (SCLC) is treated as a single entity with predictably poor results. Using tumor expression data and non-negative matrix factorization, we identify four SCLC subtypes defined largely by differential expression of transcription factors ASCL1, NEUROD1, and POU2F3 or low expression of all three transcription factor signatures accompanied by an Inflamed gene signature (SCLC-A, N, P, and I, respectively). SCLC-I experiences the greatest benefit from the addition of immunotherapy to chemotherapy, while the other subtypes each have distinct vulnerabilities, including to inhibitors of PARP, Aurora kinases, or BCL-2. Cisplatin treatment of SCLC-A patient-derived xenografts induces intratumoral shifts toward SCLC-I, supporting subtype switching as a mechanism of acquired platinum resistance. We propose that matching baseline tumor subtype to therapy, as well as manipulating subtype switching on therapy, may enhance depth and duration of response for SCLC patients.

Global analysis of shared T cell specificities in human non-small cell lung cancer enables HLA inference and antigen discovery

To identify disease-relevant T cell receptors (TCRs) with shared antigen specificity, we analyzed 778,938 TCRβ chain sequences from 178 non-small cell lung cancer patients using the GLIPH2 (grouping of lymphocyte interactions with paratope hotspots 2) algorithm. We identified over 66,000 shared specificity groups, of which 435 were clonally expanded and enriched in tumors compared to adjacent lung. The antigenic epitopes of one such tumor-enriched specificity group were identified using a yeast peptide-HLA A^∗02:01 display library. These included a peptide from the epithelial protein TMEM161A, which is overexpressed in tumors and cross-reactive epitopes from Epstein-Barr virus and E. coli. Our findings suggest that this cross-reactivity may underlie the presence of virus-specific T cells in tumor infiltrates and that pathogen cross-reactivity may be a feature of multiple cancers. The approach and analytical pipelines generated in this work, as well as the specificity groups defined here, present a resource for understanding the T cell response in cancer.

Single cell analysis reveals distinct immune landscapes in transplant and primary sarcomas that determine response or resistance to immunotherapy

Immunotherapy fails to cure most cancer patients. Preclinical studies indicate that radiotherapy synergizes with immunotherapy, promoting radiation-induced antitumor immunity. Most preclinical immunotherapy studies utilize transplant tumor models, which overestimate patient responses. Here, we show that transplant sarcomas are cured by PD-1 blockade and radiotherapy, but identical treatment fails in autochthonous sarcomas, which demonstrate immunoediting, decreased neoantigen expression, and tumor-specific immune tolerance. We characterize tumor-infiltrating immune cells from transplant and primary tumors, revealing striking differences in their immune landscapes. Although radiotherapy remodels myeloid cells in both models, only transplant tumors are enriched for activated CD8+ T cells. The immune microenvironment of primary murine sarcomas resembles most human sarcomas, while transplant sarcomas resemble the most inflamed human sarcomas. These results identify distinct microenvironments in murine sarcomas that coevolve with the immune system and suggest that patients with a sarcoma immune phenotype similar to transplant tumors may benefit most from PD-1 blockade and radiotherapy.

KEAP1/NFE2L2 Mutations Predict Lung Cancer Radiation Resistance That Can Be Targeted by Glutaminase Inhibition

Tumor genotyping is not routinely performed in localized non-small cell lung cancer (NSCLC) due to lack of associations of mutations with outcome. Here, we analyze 232 consecutive patients with localized NSCLC and demonstrate that KEAP1 and NFE2L2 mutations are predictive of high rates of local recurrence (LR) after radiotherapy but not surgery. Half of LRs occurred in tumors with KEAP1/NFE2L2 mutations, indicating that they are major molecular drivers of clinical radioresistance. Next, we functionally evaluate KEAP1/NFE2L2 mutations in our radiotherapy cohort and demonstrate that only pathogenic mutations are associated with radioresistance. Furthermore, expression of NFE2L2 target genes does not predict LR, underscoring the utility of tumor genotyping. Finally, we show that glutaminase inhibition preferentially radiosensitizes KEAP1-mutant cells via depletion of glutathione and increased radiation-induced DNA damage. Our findings suggest that genotyping for KEAP1/NFE2L2 mutations could facilitate treatment personalization and provide a potential strategy for overcoming radioresistance conferred by these mutations. SIGNIFICANCE: This study shows that mutations in KEAP1 and NFE2L2 predict for LR after radiotherapy but not surgery in patients with NSCLC. Approximately half of all LRs are associated with these mutations and glutaminase inhibition may allow personalized radiosensitization of KEAP1/NFE2L2-mutant tumors.This article is highlighted in the In This Issue feature, p. 1775.

Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

Abstract 1557: Landscape of tumor cell states and cellular ecosystems in diffuse large B cell lymphoma

The tumor microenvironment (TME) plays critical roles in cancer development, tumor progression, and susceptibility to therapy. However, the phenotypic states and interaction patterns of its underlying cell types remain poorly understood. To address this challenge, we developed a new computational framework, EcoTyper, for large-scale dissection of cell states and cellular communities (i.e., ecosystems) from tumor genomic profiles. EcoTyper integrates single-cell RNA sequencing (scRNA-seq) with CIBERSORTx, an algorithm for bulk RNA-seq deconvolution (Newman et al., Nat Biotechnol, 2019), to identify and validate cellular states and ecosystems that reflect fundamental distinctions in TME biology. Here we applied EcoTyper to diffuse large B cell lymphoma (DLBCL), an aggressive B cell malignancy with clinically distinct molecular subtypes and several immunologically-active therapies. We sought to determine whether EcoTyper could reveal novel biological variation in the DLBCL TME linked to tumor subtypes and genotypes, therapeutic responses, and clinical outcomes. We applied our approach to define transcriptional states from 13 cell types, including malignant, immune, and stromal cells, in over 1,500 DLBCL tumors. Remarkably, nearly all cell states identified by EcoTyper were validated in independent scRNA-seq and bulk RNA-seq datasets. Moreover, many cells states reflected novel phenotypic groupings, and the majority showed strong associations with overall survival, specific mutational profiles, and tumor molecular subtypes. Additionally, by identifying DLBCL tumors with similar communities of cellular states, we defined novel cellular ecosystems, or “ecotypes”, with distinct biological characteristics and clinical outcomes. Several ecotypes showed significant enrichments in canonical or novel tumor genotypes, suggesting an evolutionary interplay between the tumor and host TME. In summary, we developed a novel computational framework to dissect the TME at scale and present the most comprehensive atlas to date of cell states and cellular communities in DLBCL. Our approach is extensible to nearly any cancer type and may lead to the development of novel diagnostics and individualized immunotherapies.

Citation Format: Chloe B. Steen, Bogdan Luca, Mohammad S. Esfahani, Barzin Y. Nabet, Brian Sworder, Farshad Farshidfar, David Kurtz, Chih Long Liu, Ranjana H. Advani, Yasodha Natkunam, June H. Myklebust, Maximilian Diehn, Andrew Gentles, Ash Alizadeh, Aaron M. Newman. Landscape of tumor cell states and cellular ecosystems in diffuse large B cell lymphoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1557.

Abstract 5666: A noninvasive approach for early prediction of therapeutic benefit from immune checkpoint inhibition for lung cancer

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICI) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we analyze 211 samples from 99 patients and demonstrate that pre-treatment circulating tumor DNA (ctDNA) and circulating immune profiles are independently associated with DCB. We further show that ctDNA dynamics after a single ICI infusion can identify the majority of patients who will achieve DCB. Integrating these determinants, we describe an entirely noninvasive multi-analyte assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA- On-treatment) that robustly predicted DCB, and that was validated in two independent cohorts (AUC = 0.89-0.93, PPV = 92-100%, HR = 0.04-0.11). Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICI.

Citation Format: Barzin Y. Nabet, Mohammad S. Esfahani, Emily G. Hamilton, Jacob J. Chabon, Everett J. Moding, Hira Rizvi, Chloe B. Steen, Aadel A. Chaudhuri, Chih Long Liu, Angela B. Hui, Henning Stehr, Linda Goljenola, Michael C. Jin, Young-Jun Jeon, Diane Tseng, Taha Merghoub, Joel W. Neal, Heather A. Wakelee, Sukhmani K. Padda, Kavitha J. Ramchandran, Millie Das, Rene F. Bonilla, Christopher Yoo, Emily L. Chen, Ryan B. Ko, Aaron M. Newman, Matthew D. Hellmann, Ash A. Alizadeh, Maximilian Diehn. A noninvasive approach for early prediction of therapeutic benefit from immune checkpoint inhibition for lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5666.

Integrating genomic features for non-invasive early lung cancer detection

Radiologic screening of high-risk adults reduces lung-cancer-related mortality1,2; however, a small minority of eligible individuals undergo such screening in the United States3,4. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq)5, a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.

Circulating Tumor DNA Analysis to Assess Risk of Progression after Long-term Response to PD-(L)1 Blockade in NSCLC

PURPOSE

Treatment with PD-(L)1 blockade can produce remarkably durable responses in patients with non-small cell lung cancer (NSCLC). However, a significant fraction of long-term responders ultimately progress and predictors of late progression are unknown. We hypothesized that circulating tumor DNA (ctDNA) analysis of long-term responders to PD-(L)1 blockade may differentiate those who will achieve ongoing benefit from those at risk of eventual progression.

EXPERIMENTAL DESIGN

In patients with advanced NSCLC achieving long-term benefit from PD-(L)1 blockade (progression-free survival ≥ 12 months), plasma was collected at a surveillance timepoint late during/after treatment to interrogate ctDNA by Cancer Personalized Profiling by Deep Sequencing. Tumor tissue was available for 24 patients and was profiled by whole-exome sequencing (n = 18) or by targeted sequencing (n = 6).

RESULTS

Thirty-one patients with NSCLC with long-term benefit to PD-(L)1 blockade were identified, and ctDNA was analyzed in surveillance blood samples collected at a median of 26.7 months after initiation of therapy. Nine patients also had baseline plasma samples available, and all had detectable ctDNA prior to therapy initiation. At the surveillance timepoint, 27 patients had undetectable ctDNA and 25 (93%) have remained progression-free; in contrast, all 4 patients with detectable ctDNA eventually progressed [Fisher P < 0.0001; positive predictive value = 1, 95% confidence interval (CI), 0.51-1; negative predictive value = 0.93 (95% CI, 0.80-0.99)].

CONCLUSIONS

ctDNA analysis can noninvasively identify minimal residual disease in patients with long-term responses to PD-(L)1 blockade and predict the risk of eventual progression. If validated, ctDNA surveillance may facilitate personalization of the duration of immune checkpoint blockade and enable early intervention in patients at high risk for progression.

Circulating Tumor DNA Dynamics Predict Benefit from Consolidation Immunotherapy in Locally Advanced Non-Small Cell Lung Cancer

Circulating tumor DNA (ctDNA) molecular residual disease (MRD) following curative-intent treatment strongly predicts recurrence in multiple tumor types, but whether further treatment can improve outcomes in patients with MRD remains unclear. We applied CAPP-Seq ctDNA analysis to 218 samples from 65 patients receiving chemoradiation therapy (CRT) for locally advanced NSCLC, including 28 patients receiving consolidation immune checkpoint inhibition (CICI). Patients with undetectable ctDNA after CRT had excellent outcomes whether or not they received CICI. Among such patients, one died from CICI-related pneumonitis, highlighting the potential utility of only treating patients with MRD. In contrast, patients with MRD after CRT who received CICI had significantly better outcomes than patients who did not receive CICI. Furthermore, the ctDNA response pattern early during CICI identified patients responding to consolidation therapy. Our results suggest that CICI improves outcomes for NSCLC patients with MRD and that ctDNA analysis may facilitate personalization of consolidation therapy.

Lesion-Level Response Dynamics to Programmed Cell Death Protein (PD-1) Blockade

PURPOSE

Response to programmed cell death protein 1 (PD-1) blockade is often conceptualized as resulting from reinvigoration of tumor-infiltrating lymphocytes. However, recruited antitumor immunity from the periphery may also be an important contributor to response. A detailed assessment of the response dynamics of individual metastasis could provide insight to the systemic and local features that mediate response and resistance to immunotherapy.

MATERIALS AND METHODS

Patients with metastatic non-small-cell lung cancer (NSCLC) or mismatch repair deficiency (MMRD) carcinoma treated with PD-1 monotherapy were evaluated independently. Absolute and percent change of each target lesion were quantified at each computed tomography scan using RECIST. Patterns of progression were predefined as systemic or mixed and were correlated with clinical outcomes.

RESULTS

A total of 761 individual lesions from 214 patients with NSCLC and 290 lesions from 78 patients with MMRD carcinoma were examined. Individual target lesion responses aligned with best overall response of each patient (85% NSCLC and 93% MMRD lesions responded in patients with partial response/complete response). In responding patients, timing of response was uniform (73% NSCLC and 76% MMRD lesions responded synchronously), and deeper responses were associated with prolonged progression-free survival and overall survival. By contrast, at progression, mixed progression was common (45% of NSCLC and 53% of MMRD) and associated with improved survival compared with those who experienced systemic progression (NSCLC hazard ratio [HR], 0.58; P = .001; MMRD HR, 0.40; P = .07). Organ sites had differential responses, with lymph node and liver metastasis among the most and least responsive, respectively.

CONCLUSION

Temporal-spatial patterns of response across individual metastases tend to be uniform, favoring the role of peripheral, clonally directed antitumor immunity as a key mediator of response to PD-1 blockade. In contrast, progression is more heterogeneous, potentially revealing the clinical importance of local features and intertumoral heterogeneity.

Exosomes in the tumor microenvironment as mediators of cancer therapy resistance

Exosomes are small extracellular vesicles that contain genetic material, proteins, and lipids. They function as potent signaling molecules between cancer cells and the surrounding cells that comprise the tumor microenvironment (TME). Exosomes derived from both tumor and stromal cells have been implicated in all stages of cancer progression and play an important role in therapy resistance. Moreover, due to their nature as mediators of cell-cell communication, they are integral to TME-dependent therapy resistance. In this review, we discuss current exosome isolation and profiling techniques and their role in TME interactions and therapy resistance. We also explore emerging clinical applications of both exosomes as biomarkers, direct therapeutic targets, and engineered nanocarriers. In order to fully understand the TME, careful interrogation of exosomes and their cargo is critical. This understanding is a promising avenue for the development of effective clinical applications.

Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA

Current regimens for the detection and surveillance of bladder cancer are invasive and have suboptimal sensitivity. Here, we present a novel high-throughput sequencing (HTS) method for detection of urine tumor DNA (utDNA) called utDNA CAPP-Seq (uCAPP-Seq) and apply it to 67 healthy adults and 118 patients with early-stage bladder cancer who had urine collected either prior to treatment or during surveillance. Using this targeted sequencing approach, we detected a median of 6 mutations per patient with bladder cancer and observed surprisingly frequent mutations of the PLEKHS1 promoter (46%), suggesting these mutations represent a useful biomarker for detection of bladder cancer. We detected utDNA pretreatment in 93% of cases using a tumor mutation-informed approach and in 84% when blinded to tumor mutation status, with 96% to 100% specificity. In the surveillance setting, we detected utDNA in 91% of patients who ultimately recurred, with utDNA detection preceding clinical progression in 92% of cases. uCAPP-Seq outperformed a commonly used ancillary test (UroVysion, P = 0.02) and cytology and cystoscopy combined (P ≤ 0.006), detecting 100% of bladder cancer cases detected by cytology and 82% that cytology missed. Our results indicate that uCAPP-Seq is a promising approach for early detection and surveillance of bladder cancer. SIGNIFICANCE: This study shows that utDNA can be detected using HTS with high sensitivity and specificity in patients with early-stage bladder cancer and during post-treatment surveillance, significantly outperforming standard diagnostic modalities and facilitating noninvasive detection, genotyping, and monitoring.This article is highlighted in the In This Issue feature, p. 453.

Exosome RNA Unshielding Couples Stromal Activation to Pattern Recognition Receptor Signaling in Cancer

Interactions between stromal fibroblasts and cancer cells generate signals for cancer progression, therapy resistance, and inflammatory responses. Although endogenous RNAs acting as damage-associated molecular patterns (DAMPs) for pattern recognition receptors (PRRs) may represent one such signal, these RNAs must remain unrecognized under non-pathological conditions. We show that triggering of stromal NOTCH-MYC by breast cancer cells results in a POL3-driven increase in RN7SL1, an endogenous RNA normally shielded by RNA binding proteins SRP9/14. This increase in RN7SL1 alters its stoichiometry with SRP9/14 and generates unshielded RN7SL1 in stromal exosomes. After exosome transfer to immune cells, unshielded RN7SL1 drives an inflammatory response. Upon transfer to breast cancer cells, unshielded RN7SL1 activates the PRR RIG-I to enhance tumor growth, metastasis, and therapy resistance. Corroborated by evidence from patient tumors and blood, these results demonstrate that regulation of RNA unshielding couples stromal activation with deployment of RNA DAMPs that promote aggressive features of cancer. VIDEO ABSTRACT.

Abstract A45: Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways in triple-negative breast cancer

Breast cancer cells can achieve protection from DNA damage both through cell-autonomous mechanisms and intercellular communication with the tumor microenvironment. Previously, we described an Interferon-Related DNA Damage Resistance Signature comprising of a network of interferon-stimulated genes (ISGs) that promotes and clinically predicts chemotherapy and radiation resistance in breast cancer. Here, we examine the heterotypic tumor-stroma interactions that regulate ISGs. We show that STAT1 and other ISGs are induced in breast cancer cells following interaction with stroma. STAT1 induces NOTCH3 expression, explaining a requirement for juxtacrine signaling. Moreover, we report that stroma upregulates ISG expression in breast cancer cells through exosomes. Exosomes transferred from the stroma and ISG induction are both dependent on RAB27B. In mice, targeting these pathways abrogate stroma-mediated resistance and results in long-term tumor-free survival. Analysis of primary human tumors supports the role of anti-viral/NOTCH3 pathways in NOTCH signaling and stroma-mediated resistance. To determine whether these observations can further predict clinical efficacy, cell lines derived from a genetically engineered mouse model for p53-induced breast cancer, K14cre;Brca1F/F;p53F/F, were tested. We show that stroma induces breast cancer ISGs through exosomes, which in turn can induce signaling to activate NOTCH3 and regulate DNA damage resistance.

Citation Format: Tony J. Wu, Barzin Y. Nabet, Bihui Xu, Mirjam C. Boelens, Jos Jonkers, Andy J. Minn. Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways in triple-negative breast cancer. [abstract]. In: Proceedings of the AACR Special Conference: Function of Tumor Microenvironment in Cancer Progression; 2016 Jan 7–10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2016;76(15 Suppl):Abstract nr A45.

Basal and stress-induced Hsp70 are modulated by ataxin-3

Regulation of basal and induced levels of hsp70 is critical for cellular homeostasis. Ataxin-3 is a deubiquitinase with several cellular functions including transcriptional regulation and maintenance of protein homeostasis. While investigating potential roles of ataxin-3 in response to cellular stress, it appeared that ataxin-3 regulated hsp70. Basal levels of hsp70 were lower in ataxin-3 knockout (KO) mouse brain from 2 to 63 weeks of age and hsp70 was also lower in fibroblasts from ataxin-3 KO mice. Transfecting KO cells with ataxin-3 rescued basal levels of hsp70 protein. Western blots of representative chaperones including hsp110, hsp90, hsp70, hsc70, hsp60, hsp40/hdj2, and hsp25 indicated that only hsp70 was appreciably altered in KO fibroblasts and KO mouse brain. Turnover of hsp70 protein was similar in wild-type (WT) and KO cells; however, basal hsp70 promoter reporter activity was decreased in ataxin-3 KO cells. Transfecting ataxin-3 restored hsp70 basal promoter activity in KO fibroblasts to levels of promoter activity in WT cells; however, mutations that inactivated deubiquitinase activity or the ubiquitin interacting motifs did not restore full activity to hsp70 basal promoter activity. Hsp70 protein and promoter activity were higher in WT compared to KO cells exposed to heat shock and azetidine-2-carboxylic acid, but WT and KO cells had similar levels in response to cadmium. Heat shock factor-1 had decreased levels and increased turnover in ataxin-3 KO fibroblasts. Data in this study are consistent with ataxin-3 regulating basal level of hsp70 as well as modulating hsp70 in response to a subset of cellular stresses.

Combining ATR suppression with oncogenic Ras synergistically increases genomic instability, causing synthetic lethality or tumorigenesis in a dosage-dependent manner

Previous studies indicate that oncogenic stress activates the ATR-Chk1 pathway. Here, we show that ATR-Chk1 pathway engagement is essential for limiting genomic instability following oncogenic Ras transformation. ATR pathway inhibition in combination with oncogenic Ras expression synergistically increased genomic instability, as quantified by chromatid breaks, sister chromatid exchanges, and H2AX phosphorylation. This level of instability was significantly greater than that observed following ATR suppression in untransformed control cells. In addition, consistent with a deficiency in long-term genome maintenance, hypomorphic ATR pathway reduction to 16% of normal levels was synthetic lethal with oncogenic Ras expression in cultured cells. Notably, elevated genomic instability and synthetic lethality following suppression of ATR were not due to accelerated cycling rates in Ras-transformed cells, indicating that these synergistic effects were generated on a per-cell-cycle basis. In contrast to the synthetic lethal effects of hypomorphic ATR suppression, subtle reduction of ATR expression (haploinsufficiency) in combination with endogenous levels of K-ras(G12D) expression elevated the incidence of lung adenocarcinoma, spindle cell sarcoma, and thymic lymphoma in p53 heterozygous mice. K-ras(G12D)-induced tumorigenesis in ATR(+/-)p53(+/-) mice was associated with intrachromosomal deletions and loss of wild-type p53. These findings indicate that synergistic increases in genomic instability following ATR reduction in oncogenic Ras-transformed cells can produce 2 distinct biological outcomes: synthetic lethality upon significant suppression of ATR expression and tumor promotion in the context of ATR haploinsufficiency. These results highlight the importance of the ATR pathway both as a barrier to malignant progression and as a potential target for cancer treatment.