Abstract 370: Smoking history as an independent predictor for immune checkpoint inhibitors (ICIs) in metastatic non-small cell lung cancer (NSCLC)

Importance: Immune Checkpoint Inhibitors (ICIs) induce durable response in a subset of non-small cell lung cancer (NSCLC) patients. There is an unmet need to develop effective predictors for ICIs in metastatic NSCLC.

Objective: Define the predictive impact of smoking history (pack-years) on the clinical outcomes of ICI monotherapy and further to validate the potential clinical utility in metastatic NSCLC.

Design, setting, and participants: This study was conducted on 680 metastatic NSCLC patients treated with ICIs between April 2013 and September 2020 at the Dana-Farber Cancer Institute and Brigham and Women's Hospital. Patient TMB and programmed cell death-ligand 1 (PD-L1) tumor proportion score (TPS) were determined by clinical targeted Next Generation Sequencing (NGS) and immunohistochemistry (IHC) and detailed smoking history and clinicopathological characteristics were prospectively collected.

Main outcomes and measures: Evaluation of the association of smoking pack-years with objective response rate (ORR), progression-free survival (PFS) and overall survival (OS) in metastatic NSCLC patients treated with ICI monotherapy. Assessment of time-dependent area under the curve (AUC) for predictive models of clinical outcomes.

Results: Among 680 metastatic NSCLC patients who received ICI monotherapy: 109 (16.0%) never smokers, 397 (58.4%) former smokers [median 30 pack-years], and 174 (25.6%) current smokers [median 40 pack-years]. Multivariable analysis suggested that doubling of smoking pack-years is significantly associated with better clinical outcomes of ICIs. (ORR OR = 1.20, P < 0.001; PFS HR = 0.92, P < 0.001; OS HR = 0.94, P = 0.01) Predictive models incorporating smoking pack-years yielded additional information and achieved similar model performance compared to the one using TMB.

Conclusions and Relevance: This finding suggests that detailed smoking information has a significant predictive value on clinical outcomes of ICI monotherapy independent of PD-L1 TPS. Smoking pack-years could serve as a non-invasive and consistent surrogate for TMB when it is not readily available for treatment-decision in metastatic NSCLC.

Citation Format: Xinan Wang, Biagio Ricciuti, Joao V. Alessi, Tom Nguyen, Mark M. Awad, Xihong Lin, Bruce E. Johnson, David C. Christiani. Smoking history as an independent predictor for immune checkpoint inhibitors (ICIs) in metastatic non-small cell lung cancer (NSCLC) [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 370.

Smoking History as a Potential Predictor of Immune Checkpoint Inhibitor Efficacy in Metastatic Non-Small Cell Lung Cancer

BACKGROUND

Despite the therapeutic efficacy of immune checkpoint inhibitors (ICIs) in a subset of patients, consistent and easily obtainable predictors of efficacy remain elusive.

METHODS

This study was conducted on 644 advanced non-small cell lung cancer (NSCLC) patients treated with ICI monotherapy between April 2013 and September 2020 at the Dana-Farber Cancer Institute and Brigham and Women's Hospital. Patient smoking history, clinicopathological characteristics, tumor mutation burden (TMB) by clinical targeted next-generation sequencing, and programmed death ligand-1 (PD-L1) tumor proportion score (TPS) by immunohistochemistry were prospectively collected. The association of smoking history with clinical outcomes of ICI monotherapy in metastatic NSCLC patients was evaluated after adjusting for other potential predictors. All statistical tests were 2-sided.

RESULTS

Of 644 advanced NSCLC patients, 105 (16.3%) were never smokers, 375 (58.2%) were former smokers (median pack-years = 28), and 164 (25.4%) were current smokers (median pack-years = 40). Multivariable logistic and Cox proportional hazards regression analyses suggested that doubling of smoking pack-years is statistically significantly associated with improved clinical outcomes of patients treated with ICI monotherapy (objective response rate odds ratio = 1.21, 95% confidence interval [CI] = 1.09 to 1.36, P < .001; progression-free survival hazard ratio = 0.92, 95% CI = 0.88 to 0.95, P < .001; overall survival hazard ratio = 0.94, 95% CI = 0.90 to 0.99, P = .01). Predictive models incorporating pack-years and PD-L1 TPS yielded additional information and achieved similar model performance compared with using TMB and PD-L1 TPS.

CONCLUSIONS

Increased smoking exposure had a statistically significant association with improved clinical outcomes in metastatic NSCLC treated with ICI monotherapy independent of PD-L1 TPS. Pack-years may serve as a consistent and readily obtainable surrogate of ICI efficacy when TMB is not available to inform prompt clinical decisions and allow more patients to benefit from ICIs.

Identification and management of pathogenic mutations in BRCA1, BRCA2, and PALB2 in a tumor-only genomic testing program

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Background: Tumor-genomic testing is increasingly used to guide treatment decisions in cancer patients. Although tumor-only testing cannot definitively distinguish between germline versus somatic alterations, the identification of pathogenic or likely pathogenic (P/LP) variants in certain genes should prompt consideration of germline testing. Germline P/LPs in BRCA1, BRCA2 and PALB2 ( B1B2PAL) are associated with hereditary cancer syndromes. Methods: We reviewed tumor-only genomic data (Dana-Farber Oncopanel) between 10/2016 and 6/2018 to examine the prevalence of P/LPs in BRCA1, BRCA2, PALB2 among adult cancer patients at Dana-Farber Cancer Institute/Brigham and Women’s Hospital. We characterized the frequency of P/LPs by primary tumor type, confirmation by germline testing before or within 12 months after Oncopanel testing or not, and factors associated with germline testing. Results: Among 7,575 patients, the median age was 62 (range 18-99); 53.9% were female. A total of 272 (3.6%) had P/LPs in BRCA1 (n = 90), BRCA2 (n = 162) and/or PALB2 (n = 29). P/LPs in B1B2PAL were detected in 5.3% (38/712) of breast, 11.9% (34/285) of ovarian, 6.6% (18/272) of pancreatic, and 5.1% (12/234) of prostate cancers. P/LPs in B1B2PAL were also detected in other neoplasms (12.9% (8/62) of non-melanoma skin, 5.0% (43/855) of colorectal, 7.6% (20/264) of endometrial, and 4.6% (10/216) of head and neck cancers). Of 169 patients who had not had prior germline testing, 29/169 (17.2%) completed germline testing within 12 months after Oncopanel; 13 (7.7%) referred for testing declined or did not complete testing within 12 months, 14 (8.3%) died before or within 3 months of the Oncopanel results, and 113 (66.9%) had no documented germline testing within 12 months. Among 132 patients who had germline testing, 117 (88.6%) had a clinical indication based on personal or family history compared to 66/140 (47.1%) who did not undergo germline testing. Among 132/272 (48.5%) germline-tested patients, 70.5% were positive for a germline mutation in B1B2PAL; the remainder had somatic B1B2PAL mutations only. Germline testing was more often performed in patients with B1B2PAL-associated tumors (breast, ovarian, pancreatic and prostate cancers) or other clinical indications for germline testing. Conclusions: A low but clinically meaningful rate of P/LPs in BRCA1, BRCA2 and PALB2 was detected by tumor-only genomic testing in diverse malignancies. Given the implications of B1B2PAL alterations on treatment and familial cancer risk, our data support current NCCN guidelines recommending germline testing among patients with cancer and P/LPs in B1B2PAL detected on tumor-genomic testing and highlights the need for systems to ensure germline testing when indicated.

Physician concern about delaying lung cancer treatment while awaiting biomarker testing: Results of a survey of U.S. oncologists

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Background: With rapid advancements in biomarker testing informing lung cancer treatment decisions, clinicians are challenged to maintain knowledge of who, what and when to test and how to treat based on test results. An ASCO taskforce including representatives from the American Cancer Society National Lung Cancer Roundtable and patient advocates conducted a study to assess biomarker testing and treatment practices for patients with advanced non-small cell lung cancer (aNSCLC) among U.S. oncologists. Methods: A survey was sent to 2374 ASCO members – lung cancer specialists and general oncologists. Eligibility required treating ≥1 lung cancer patient/month. Proportions were estimated across groups and compared using chi-square tests. Results: 170 responses were analyzed. 59% of respondents work at an academic center (i.e., have a fellowship program), while 41% work at a community (non-academic hospital/health system/private practice). Nearly all (98%) believe biomarker results should be received within 1 or 2 weeks of ordering, yet 37% wait an average of 3 or 4 weeks for results. Of respondents who usually wait 3 or 4 weeks, 37% initiate a non-targeted systemic treatment while waiting. Respondents from community practices were more likely to initiate non-targeted systemic treatment if results were not available after 2 weeks (59% compared to 40% of academic respondents; p = 0.013). ). When asked about reasons for not testing, respondents <5 years since training were more likely to report that delaying treatment while waiting for results was always/often a concern compared to those >6 years from training (41% vs 19%). Respondents reported high testing rates in both non-squamous and squamous aNSCLC. Roughly equal representation of generalists/specialists and academic/community respondents helps mitigate potential concerns about external validity. Conclusions: Respondents indicated that treatment decisions are impacted by delays in biomarker test results. Clinicians should be informed about when it is safe and appropriate to defer treatment while biomarker testing is pending. Respondents suggest that diagnostic biomarker testing companies should strive to expedite results.[Table: see text]

Association between Smoking History and Tumor Mutation Burden in Advanced Non-Small Cell Lung Cancer

Lung carcinogenesis is a complex and stepwise process involving accumulation of genetic mutations in signaling and oncogenic pathways via interactions with environmental factors and host susceptibility. Tobacco exposure is the leading cause of lung cancer, but its relationship to clinically relevant mutations and the composite tumor mutation burden (TMB) has not been fully elucidated. In this study, we investigated the dose-response relationship in a retrospective observational study of 931 patients treated for advanced-stage non-small cell lung cancer (NSCLC) between April 2013 and February 2020 at the Dana Farber Cancer Institute and Brigham and Women's Hospital. Doubling smoking pack-years was associated with increased KRAS^G12C and less frequent EGFR^del19 and EGFR^L858R mutations, whereas doubling smoking-free months was associated with more frequent EGFR^L858R . In advanced lung adenocarcinoma, doubling smoking pack-years was associated with an increase in TMB, whereas doubling smoking-free months was associated with a decrease in TMB, after controlling for age, gender, and stage. There is a significant dose-response association of smoking history with genetic alterations in cancer-related pathways and TMB in advanced lung adenocarcinoma. SIGNIFICANCE: This study clarifies the relationship between smoking history and clinically relevant mutations in non-small cell lung cancer, revealing the potential of smoking history as a surrogate for tumor mutation burden.

Multimodal pooled Perturb-CITE-seq screens in patient models define mechanisms of cancer immune evasion

Resistance to immune checkpoint inhibitors (ICIs) is a key challenge in cancer therapy. To elucidate underlying mechanisms, we developed Perturb-CITE-sequencing (Perturb-CITE-seq), enabling pooled clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9 perturbations with single-cell transcriptome and protein readouts. In patient-derived melanoma cells and autologous tumor-infiltrating lymphocyte (TIL) co-cultures, we profiled transcriptomes and 20 proteins in ~218,000 cells under ~750 perturbations associated with cancer cell-intrinsic ICI resistance (ICR). We recover known mechanisms of resistance, including defects in the interferon-γ (IFN-γ)-JAK/STAT and antigen-presentation pathways in RNA, protein and perturbation space, and new ones, including loss/downregulation of CD58. Loss of CD58 conferred immune evasion in multiple co-culture models and was downregulated in tumors of melanoma patients with ICR. CD58 protein expression was not induced by IFN-γ signaling, and CD58 loss conferred immune evasion without compromising major histocompatibility complex (MHC) expression, suggesting that it acts orthogonally to known mechanisms of ICR. This work provides a framework for the deciphering of complex mechanisms by large-scale perturbation screens with multimodal, single-cell readouts, and discovers potentially clinically relevant mechanisms of immune evasion.

Expansion sequencing: Spatially precise in situ transcriptomics in intact biological systems

Methods for highly multiplexed RNA imaging are limited in spatial resolution and thus in their ability to localize transcripts to nanoscale and subcellular compartments. We adapt expansion microscopy, which physically expands biological specimens, for long-read untargeted and targeted in situ RNA sequencing. We applied untargeted expansion sequencing (ExSeq) to the mouse brain, which yielded the readout of thousands of genes, including splice variants. Targeted ExSeq yielded nanoscale-resolution maps of RNAs throughout dendrites and spines in the neurons of the mouse hippocampus, revealing patterns across multiple cell types, layer-specific cell types across the mouse visual cortex, and the organization and position-dependent states of tumor and immune cells in a human metastatic breast cancer biopsy. Thus, ExSeq enables highly multiplexed mapping of RNAs from nanoscale to system scale.

Genomic Characterization of de novo Metastatic Breast Cancer

PURPOSE

In contrast to recurrence after initial diagnosis of stage I-III breast cancer [recurrent metastatic breast cancer (rMBC)], de novo metastatic breast cancer (dnMBC) represents a unique setting to elucidate metastatic drivers in the absence of treatment selection. We present the genomic landscape of dnMBC and association with overall survival (OS).

EXPERIMENTAL DESIGN

Targeted DNA sequencing (OncoPanel) was prospectively performed on either primary or metastatic tumors from 926 patients (212 dnMBC and 714 rMBC). Single-nucleotide variants, copy-number variations, and tumor mutational burden (TMB) in treatment-naïve dnMBC primary tumors were compared with primary tumors in patients who ultimately developed rMBC, and correlated with OS across all dnMBC.

RESULTS

When comparing primary tumors by subtype, MYB amplification was enriched in triple-negative dnMBC versus rMBC (21.1% vs. 0%, P = 0.0005, q = 0.111). Mutations in KMTD2, SETD2, and PIK3CA were more prevalent, and TP53 and BRCA1 less prevalent, in primary HR⁺/HER2^- tumors of dnMBC versus rMBC, though not significant after multiple comparison adjustment. Alterations associated with shorter OS in dnMBC included TP53 (wild-type: 79.7 months; altered: 44.2 months; P = 0.008, q = 0.107), MYC (79.7 vs. 23.3 months; P = 0.0003, q = 0.011), and cell-cycle (122.7 vs. 54.9 months; P = 0.034, q = 0.245) pathway genes. High TMB correlated with better OS in triple-negative dnMBC (P = 0.041).

CONCLUSIONS

Genomic differences between treatment-naïve dnMBC and primary tumors of patients who developed rMBC may provide insight into mechanisms underlying metastatic potential and differential therapeutic sensitivity in dnMBC. Alterations associated with poor OS in dnMBC highlight the need for novel approaches to overcome potential intrinsic resistance to current treatments.

Clinical Pan-Cancer Assessment of Mismatch Repair Deficiency Using Tumor-Only, Targeted Next-Generation Sequencing

PURPOSE

Given regulatory approval of immune checkpoint inhibitors in patients with mismatch repair-deficient (MMR-D) cancers agnostic to tumor type, it has become important to characterize occurrence of MMR-D and develop cost-effective screening approaches. Using a next-generation sequencing (NGS) panel (OncoPanel), we developed an algorithm to identify MMR-D frequency in tumor samples and applied it in a clinical setting with pathologist review.

METHODS

To predict MMR-D, we adapted methods described previously for use in NGS panels, which assess patterns of single base-pair insertion or deletion events occurring in homopolymer regions. Tumors assayed with OncoPanel between July 2013 and July 2018 were included. For tumors tested after June 2017, sequencing results were presented to pathologists in real time for clinical MMR determination, in the context of tumor mutation burden, other mutational signatures, and clinical data.

RESULTS

Of 20,301 tumors sequenced, 2.7% (553) were retrospectively classified as MMR-D by the algorithm. Of 4,404 samples with pathologist sign-out of MMR status, the algorithm classified 147 (3.3%) as MMR-D: in 116 cases, MMR-D was confirmed by a pathologist, five cases were overruled by the pathologist, and 26 were assessed as indeterminate. Overall, the highest frequencies of OncoPanel-inferred MMR-D were in endometrial (21%; 152/723), colorectal (9.7%; 169/1,744), and small bowel (9.3%; 9/97) cancers. When algorithm predictions were compared with historical MMR immunohistochemistry or polymerase chain reaction results in a set of 325 tumors sequenced before initiation of pathologist assessment, the overall sensitivity and specificity of the algorithm were 91.1% and 98.2%, respectively.

CONCLUSION

We show that targeted, tumor-only NGS can be leveraged to determine MMR signatures across tumor types, suggesting that broader biomarker screening approaches may have clinical value.

Abstract PR01: A cancer cell program promotes T-cell exclusion and resistance to checkpoint blockade

Immune checkpoint inhibitors (ICI) produce durable responses in some melanoma patients, but many patients derive no clinical benefit, and the molecular underpinnings of such resistance remain elusive. Here, we leveraged single-cell RNA-seq (scRNA-seq) from 33 melanoma tumors and computational analyses to interrogate malignant cell states that promote immune evasion. We identified a resistance program expressed by malignant cells that is associated with T-cell exclusion and immune evasion. The program is expressed prior to immunotherapy, characterizes cold niches in situ, and predicts clinical responses to anti-PD-1 therapy in an independent cohort of 112 melanoma patients. CDK4/6-inhibition represses this program in individual malignant cells, induces senescence, and reduces melanoma tumor outgrowth in mouse models in vivo when given in combination with immunotherapy. Our study provides a high-resolution landscape of ICI resistant cell states, identifies clinically predictive signatures, and suggests new therapeutic strategies to overcome immunotherapy resistance. This study will be published on Nov. 1st in Cell (Jerby-Arnon et al., Cell 2018).

This abstract is also being presented as Poster A25.

Citation Format: Parin Shah, Michael Cuoco, Mei-Ju Su, Johannes Melms, Rachel Leeson, Abhay Kanodia, Shaolin Mei, Jia-Ren Lin, Shu Wang, Bokang Rabasha, David Liu, Alex K. Shalek, Itay Tirosh, Peter K. Sorger, Kai Wucherpfennig, Eliezer M. Van Allen, Dirk Schadendorf, Bruce E. Johnson, Asaf Rotem, Orit Rozenblatt-Rosen, Levi A. Garraway, Charles H. Yoon, Benjamin Izar, Aviv Regev, Livnat Jerby-Arnon. A cancer cell program promotes T-cell exclusion and resistance to checkpoint blockade [abstract]. In: Proceedings of the AACR Special Conference on Melanoma: From Biology to Target; 2019 Jan 15-18; Houston, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(19 Suppl):Abstract nr PR01.

The Impact of COVID-19 on Clinical Trial Execution at the Dana-Farber Cancer Institute

Interventions designed to limit the spread of COVID-19 are having profound effects on the delivery of healthcare, but data showing the impact on oncology clinical trial enrollment, treatment, and monitoring are limited. We prospectively tracked relevant data from oncology clinical trials at Dana-Farber Cancer Institute (DFCI) from January 1, 2018 to June 30, 2020, including the number of open trials, new patient enrollments, in-person and virtual patient visits, dispensed investigational infusions, dispensed/shipped oral investigational agents, research biopsies, and blood samples. We ascertained why patients came off trials and determined on-site clinical research staffing levels. We used two-sided Wilcoxon rank sum tests to assess the statistical significance of the reported changes. Nearly all patients on interventional treatment trials were maintained, and new enrollments continued at just under half the pre-pandemic rate. The median number of investigational prescriptions shipped to patients increased from 0-74 (range: 22-107) per week from March-June 2020. The median number of telemedicine appointments increased from 0-107 (range: 33-267) per week from March-June 2020. Research biopsies and blood collections decreased dramatically after DFCI implemented COVID-19-related policies in March 2020. The number of research nurses and clinical research coordinators on-site also decreased after March 2020. Substantial changes were required to safely continue clinical research during the pandemic; yet, we observed no increases in serious adverse events or major violations related to drug dosing. Lessons learned from adapting research practices during COVID-19 can inform industry sponsors and governmental agencies to consider altering practices to increase operational efficiency and convenience for patients.

Identifying ERBB2 Activating Mutations in HER2-Negative Breast Cancer: Clinical Impact of Institute-Wide Genomic Testing and Enrollment in Matched Therapy Trials

PURPOSE

The yield of comprehensive genomic profiling in recruiting patients to molecular-based trials designed for small subgroups has not been fully evaluated. We evaluated the likelihood of enrollment in a clinical trial that required the identification of a specific genomic change based on our institute-wide genomic tumor profiling.

PATIENTS AND METHODS

Using genomic profiling from archived tissue samples derived from patients with metastatic breast cancer treated between 2011 and 2017, we assessed the impact of systematic genomic characterization on enrollment in an ongoing phase II trial (ClinicalTrials.gov identifier: NCT01670877). Our primary aim was to describe the proportion of patients with a qualifying ERBB2 mutation identified by our institutional genomic panel (OncoMap or OncoPanel) who enrolled in the trial. Secondary objectives included median time from testing result to trial registration, description of the spectrum of ERBB2 mutations, and survival. Associations were calculated using Fisher's exact test.

RESULTS

We identified a total of 1,045 patients with metastatic breast cancer without ERBB2 amplification who had available genomic testing results. Of these, 42 patients were found to have ERBB2 mutation and 19 patients (1.8%) were eligible for the trial on the basis of the presence of an activating mutation, 18 of which were identified by OncoPanel testing. Fifty-eight percent of potentially eligible patients were approached, and 33.3% of eligible patients enrolled in the trial guided exclusively by OncoPanel testing.

CONCLUSION

More than one half of eligible patients were approached for trial participation and, significantly, one third of those were enrolled in NCT01670877. Our data illustrate the ability to enroll patients in trials of rare subsets in routine clinical practice and highlight the need for these broadly based approaches to effectively support the success of these studies.

Abstract CT214: CANOPY-1: Safety run-in results from phase (ph) 3 study of canakinumab (CAN) or placebo (PBO) in combination (comb) with pembrolizumab (PEM) plus platinum-based doublet chemotherapy (Ctx) as 1st line therapy in patients (pts) with advanced or metastatic NSCLC

Cytokine interleukin-1β (IL-1β) has multiple pro-tumorogenic effects on tumor microenvironment, thereby promoting carcinogenesis, tumor invasiveness, and immunosuppression. CAN is a selective IL-1β inhibitor that aims to target tumor-promoting inflammation to reduce immune suppression, thereby potentiating effects of immunotherapy with PD-1 inhibitors such as PEM. Ph 3 CANTOS study has shown IL-1β inhibition with CAN was associated with reduced incidence of lung cancer (LC) and LC mortality in pts with atherosclerosis, providing a rationale to investigate therapeutic role of CAN in LC. CANOPY-1 (NCT03631199) is a PBO-controlled, double-blind, randomized, ph 3 trial designed to evaluate efficacy and safety of PEM + Ctx ± CAN in tx naive pts with stage IIIB/IIIC (not eligible for definitive chemo-radiation curative tx) or stage IV squamous and nonsquamous NSCLC. The study was divided into 2 parts: part 1 is open labelled, safety run-in part where pts received CAN 200 mg s.c Q3W + PEM 200 mg i.v Q3W + platinum-based Ctx (as induction during first 4 cycles only); Cohort A (A, non-squamous), carboplatin + pemetrexed; Cohort B (B, non-squamous), cisplatin + pemetrexed; Cohort C (C, squamous or non-squamous), carboplatin + paclitaxel. Part 2 is randomized and evaluates efficacy and safety of CAN comb regimen vs PBO comb regimen. Primary objective of safety run-in part: recommended ph 3 dose regimen (RP3R) of CAN comb. Secondary objectives: ORR, DCR, DOR, safety, PK, and immunogenicity. As of 14 May 2019 (follow-up of ≥42 days from C1D1 unless pt discontinued earlier), 10 pts in A, 11 pts in B, and 9 pts in C were treated, of which 73% were male, median age was 63 yrs. In total, 24/30 (80%) pts enrolled were still receiving tx; primary reason for tx discontinuation was progressive disease (3 pts in A and 1 pt each in B and C) and 1 pt died due to study indication. 1 pt reported DLT during first 42 days of study tx (C: grade 3 hepatitis, not related to CAN). RP3R of CAN in comb with standard dose PEM + Ctx was 200 mg SC Q3W based on Bayesian logistic regression model (BLRM). Serious AEs regardless of causality were reported in 8 (27%) pts (2 pts in A and 3 pts each in B and C), none of which were considered to be related to CAN. Most common AEs (≥20%, any grade) across all cohorts (n=30) were nausea (37%), vomiting (30%), constipation and fatigue (each 23%), and neutrophil count decrease (20%). 14 pts (47%) experienced grade 3 AEs and 1 pt experienced grade 4 AE (cardiac tamponade [unrelated]). No fatal serious AEs were reported. AEs leading to discontinuation of one of the study drugs were reported in 3 (10%) pts (hepatitis, peripheral neuropathy, and polyneuropathy) but none were CAN related. AEs leading to dose reduction and dose interruption of one of study drugs were reported in 3 (10%) pts and 5 (17%) pts, respectively. Only 1 DLT was reported with CAN + PEM + Ctx. Based on BLRM and all relevant clinical data, the RP3R of CAN as 200 mg SC Q3W comb was considered safe and well tolerated. Enrollment for the randomized part is completed.

Citation Format: Bruce E. Johnson, Tae Min Kim, T. Jeroen N. Hiltermann, Fabrice Barlesi, Christian Grohe, Yasushi Goto, Orvar Gunnarsson, Tobias Overbeck, Noemi Reguart, Martin Wermke, Gilberto Castro Castro, Enriqueta Felip, Alastair Greystoke, Benjamin J. Solomon, Stephanie Deudon, Anne-Laure Louveau, Vanessa Passos, Daniel SW Tan. CANOPY-1: Safety run-in results from phase (ph) 3 study of canakinumab (CAN) or placebo (PBO) in combination (comb) with pembrolizumab (PEM) plus platinum-based doublet chemotherapy (Ctx) as 1st line therapy in patients (pts) with advanced or metastatic NSCLC [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 CT214.

Abstract 2063: Deep natural language processing for automated ascertainment of cancer outcomes from clinician progress notes

Introduction: Clinical research using genomic datasets, such as AACR Project GENIE, requires outcomes such as cancer progression and response to contextualize molecular information. We are developing the “PRISSMM” (Pathology, Radiology/Imaging, Signs/Symptoms, Medical oncologist assessment, and tumor Markers) framework for clinical curation of genomic data. Natural language processing (NLP) models based on this framework could accelerate curation of reproducible endpoints. However, the application of NLP at scale to extract outcomes from oncologist notes, which mix historical and current information, has been limited to date.

Methods: Medical oncologists' progress notes were reviewed for patients with lung cancer whose tumors were sequenced through an institutional precision medicine study from 2013-2018. For each note, curators recorded whether the assessment/plan indicated the presence of (a) any cancer, (b) progression/worsening of disease, and/or (c) response to therapy/improvement of disease. Next, a recurrent neural network was trained to extract the assessment/plan from each note. Finally, convolutional neural networks were trained on the assessments/plans to predict the probability that each curated outcome was present. Model performance was evaluated among a held-out 10% test subset of patients using the area under the receiver-operating characteristic curve (AUC) and area under the precision-recall curve (AUPRC). Associations between curated response or progression endpoints (generated using 10-fold cross-validation) and overall survival were measured using Cox models, treating the endpoints as time-varying covariates, among patients receiving palliative-intent systemic therapy.

Results: Results among 7,597 curated notes for 919 patients are indicated in the Table.

EndpointAUC of NLP models for identifying endpoint in the test setProportion of manually curated notes with endpointAUPRC of NLP models for identifying endpoint in the test setHR (95% CI) for mortality associated with endpoint, as manually curated, among patients receiving palliative- intent treatmentHR (95% CI) for mortality associated with endpoint, as predicted using NLP models using F1-optimal threshold probabilitiesAny evidence of lung cancer0.940.770.97N/AN/AProgression0.860.200.652.93 (2.33-3.67)2.49 (2.00-3.09)Response to treatment0.900.120.570.70 (0.47-1.03)0.45 (0.30-0.67)

Conclusion: Neural network NLP models can extract meaningful outcomes from oncologist notes for clinical curation of electronic health records at scale.

Citation Format: Kenneth L. Kehl, Wenxin Xu, Haitham A. Elmarakeby, Michael J. Hassett, Jackson Nyman, Bruce E. Johnson, Eliezer M. Van Allen, Deb Schrag. Deep natural language processing for automated ascertainment of cancer outcomes from clinician progress notes [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 2063.

Abstract CT286: CANOPY program clinical trials: Canakinumab (Cana) in patients (pts) with non-small cell lung cancer (NSCLC)

Background: In the CANTOS study, treatment (tx) with Cana (selective IL-1β inhibitor) was associated with reduced incidence and mortality of NSCLC in stable post-myocardial infarction pts with elevated high-sensitivity C-reactive protein levels. The results provided a rationale to investigate the therapeutic role of Cana in NSCLC. Methods: The phase (ph) 2, open-label CANOPY-N study (NCT03968419) is evaluating Cana or pembrolizumab (pembro) alone or in combination as neoadjuvant tx in stage IB-IIIA, tx-naive NSCLC pts eligible for primary resection (except N2 and T4 tumors) with planned surgery in 4-6 weeks (wks) from the 1st dose of study tx. Pts (~110) are randomized 2:2:1 to Cana (2 doses 200 mg SC Q3W), Cana + pembro, or pembro (2 doses 200 mg iv Q3W) for 2 three-wk cycles. Randomization (R) stratification: histology (squamous [sq] vs non-sq). Primary endpoint: major pathological response rate at time of surgery.CANOPY-A (NCT03447769), CANOPY-1 (NCT03631199), and CANOPY-2 (NCT03626545) are ph 3, multicenter, double-blind studies. In CANOPY-A (Cana in adjuvant setting), pts (~1500) with stages IIA-IIIA and IIIB (T&gt;5 cm N2), any histology, completely resected (R0) NSCLC post cisplatin-based chemotherapy (CTx) and radiation therapy (if applicable) are randomized 1:1 to Cana (200 mg SC Q3W)/placebo (PBO; SC Q3W) for 18 cycles. R stratification: AJCC/UICC v.8 stage (IIA vs IIB vs IIIA vs IIIB with T&gt;5 cm, N2 disease), histology (sq vs non-sq), region (western Europe and North America vs eastern Asia vs rest of the world). Primary endpoint: disease-free survival. CANOPY-1 and CANOPY-2 consist of Part 1 (open-label, safety run-in; enrollment complete) and Part 2 (randomized 1:1, PBO-controlled, efficacy & safety; ongoing). CANOPY-1 eligibility: pts with previously untreated stages IIIB/IIIC or IV NSCLC and known PD-L1 status (for Part 2), without EGFR sensitizing mutations and/or ALK rearrangements. Part 1 (3 cohorts of ~9 pts each, based on different platinum-CTx): to confirm the recommended phase 3 regimen (RP3R) for Cana. In Part 2, pts (~600) are randomized to Cana (200 mg SC Q3W)/PBO + pembro + CTx for 4 cycles, followed by maintenance tx (Cana/PBO + pembro ± pemetrexed) until progressive disease (PD). R stratification: PD-L1 status (tumor proportion score &lt;1% vs ≥1%), histology (sq vs non-sq), geographic region (eastern Asia vs North America + western Europe vs rest of the world). Screening has ceased as of Dec 9, 2019. In CANOPY-2, pts with stage IIIB-IV NSCLC, who received prior PD-(L)1 inhibitor therapy and platinum-based CTx, without EGFR sensitizing mutations and/or ALK rearrangements are eligible. Part 1 (~9 pts): to confirm the RP3R of Cana + docetaxel. In Part 2, pts (~226) are randomized to receive Cana (200 mg SC Q3W)/PBO + docetaxel (75 mg/m2 iv Q3W) until PD. R stratification: number of prior lines of therapy in advanced setting (1 vs 2 prior lines of therapy) and histology (sq vs non-sq). Primary endpoints: CANOPY-1 and CANOPY-2 Part 1: to confirm RP3R of the combination; CANOPY-1 Part 2: progression-free survival and overall survival (OS); CANOPY-2 Part 2: OS.

Citation Format: Luis Paz-Ares, Edward B. Garon, Tony Mok, Andrea Ardizzoni, Fabrice Barlesi, Byoung Chul Cho, Gilberto de Castro, Pedro De Marchi, Enriqueta Felip, Yasushi Goto, Alastair Greystoke, Shun Lu, Darren Wan-Teck Lim, Martin Reck, Benjamin J. Solomon, David R. Spigel, Daniel SW Tan, Michael Thomas, James Chih-Hsin Yang, Jay M. Lee, Pilar Garrido, Edward Kim, Bruce E. Johnson. CANOPY program clinical trials: Canakinumab (Cana) in patients (pts) with non-small cell lung cancer (NSCLC) [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 CT286.

A single-cell landscape of high-grade serous ovarian cancer

Malignant abdominal fluid (ascites) frequently develops in women with advanced high-grade serous ovarian cancer (HGSOC) and is associated with drug resistance and a poor prognosis1. To comprehensively characterize the HGSOC ascites ecosystem, we used single-cell RNA sequencing to profile ~11,000 cells from 22 ascites specimens from 11 patients with HGSOC. We found significant inter-patient variability in the composition and functional programs of ascites cells, including immunomodulatory fibroblast sub-populations and dichotomous macrophage populations. We found that the previously described immunoreactive and mesenchymal subtypes of HGSOC, which have prognostic implications, reflect the abundance of immune infiltrates and fibroblasts rather than distinct subsets of malignant cells2. Malignant cell variability was partly explained by heterogeneous copy number alteration patterns or expression of a stemness program. Malignant cells shared expression of inflammatory programs that were largely recapitulated in single-cell RNA sequencing of ~35,000 cells from additionally collected samples, including three ascites, two primary HGSOC tumors and three patient ascites-derived xenograft models. Inhibition of the JAK/STAT pathway, which was expressed in both malignant cells and cancer-associated fibroblasts, had potent anti-tumor activity in primary short-term cultures and patient-derived xenograft models. Our work contributes to resolving the HSGOC landscape3-5 and provides a resource for the development of novel therapeutic approaches.

From clinical specimens to human cancer preclinical models-a journey the NCI-cell line database-25 years later

The intramural the National Cancer Institute (NCI) and more recently the University of Texas Southwestern Medical Center with many different collaborators comprised a complex, multi-disciplinary team that collaborated to generated large, comprehensively annotated, cell-line related research resources which includes associated clinical, and molecular characterization data. This material has been shared in an anonymized fashion to accelerate progress in overcoming lung cancer, the leading cause of cancer death across the world. However, this cell line collection also includes a range of other cancers derived from patient-donated specimens that have been remarkably valuable for other types of cancer and disease research. A comprehensive analysis conducted by the NCI Center for Research Strategy of the 278 cell lines reported in the original Journal of Cellular Biochemistry Supplement, documents that these cell lines and related products have since been used in more than 14 000 grants, and 33 207 published scientific reports. This has resulted in over 1.2 million citations using at least one cell line. Many publications involve the use of more than one cell line, to understand the value of the resource collectively rather than individually; this method has resulted in 2.9 million citations. In addition, these cell lines have been linked to 422 clinical trials and cited by 4700 patents through publications. For lung cancer alone, the cell lines have been used in the research cited in the development of over 70 National Comprehensive Cancer Network clinical guidelines. Finally, it must be underscored again, that patient altruism enabled the availability of this invaluable research resource.

Author Correction: A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors

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

Concurrent osimertinib plus gefitinib for first-line treatment of EGFR-mutated non-small cell lung cancer (NSCLC)

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Background: First-line treatment with an EGFR tyrosine kinase inhibitor (TKI) is standard of care for patients (pts) with EGFR-mutated NSCLC. The EGFR TKI osimertinib is active against the acquired gefitinib-resistant mutation EGFR T790M, as is gefitinib against the osimertinib-resistant EGFR C797S. Preclinical evidence suggests dual EGFR inhibition with gefitinib + osimertinib may delay emergence of acquired resistance. Methods: This ongoing phase I/II study enrolled pts with stage IV EGFR-mutated (L858R or del19) NSCLC, without prior therapy for metastatic disease. Treatment in dose escalation (n = 6): concurrent osimertinib 40 mg or 80 mg + gefitinib 250 mg daily. In dose expansion (n = 21): osimertinib + gefitinib at the maximum tolerated dose (MTD). Prior to protocol amendment 6 pts received alternating monthly cycles of TKI monotherapy and were excluded from this analysis. The primary endpoints in the dose escalation and expansion phases were, respectively, identification of the MTD and feasibility, defined as receipt of combination therapy for ≥ 6 four-week cycles. Secondary endpoints included overall response rate (ORR), survival outcomes, plasma EGFR mutation clearance (cell free DNA by droplet digital PCR (ddPCR)), and mechanisms of acquired resistance. Results: From May 2017 to July 2019 27 pts were enrolled and evaluable for the primary endpoints. The MTD was osimertinib 80 mg plus gefitinib 250 mg orally daily. In feasibility analysis, 81.5% completed ≥6 cycles combination therapy (1 pt discontinued for progression, 4 for toxicity). The ORR was 85.2% (95% CI 67.5%-94.1%). Best response: 85.2% partial response, 14.8% stable disease. The most common treatment-related adverse effects (TRAEs) (% any grade, % grade 3) were rash (96.3%, 3.7%), diarrhea (85.2%, 11.1%) and dry skin (70.4%, 0%). Plasma ddPCR (n = 25 pts) detected the driver EGFR mutation at baseline in 68% of pts. In these pts, plasma EGFR cleared to undetectable at 2 weeks treatment in 82.4%. At 14.8 months median follow up the median progression free survival was not yet reached. Conclusions: Combination therapy with osimertinib and gefitinib is tolerable for first-line treatment of EGFR-mutated NSCLC and resulted in rapid plasma clearance of the EGFR mutation. The observed ORR is consistent with previously reported first-line response rates to osimertinib. Analysis of survival outcomes and acquired resistance mechanisms are pending data maturity and will facilitate understanding of the role of first-line dual EGFR TKI therapy for this pt population. Clinical trial information: NCT03122717 .

Development and validation of a novel EHR-based tumor progression outcome to support biomarker discovery

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Background: Obtaining clinical outcomes for analysis has historically been a critical barrier to cancer genomics research. EHRs could constitute an important data source to bridge this gap, but EHRs rarely capture structured outcomes such as cancer progression. Novel, robust methods are needed to capture clinically relevant outcomes from EHRs. Methods: Among patients with lung adenocarcinoma whose tumors were sequenced via the Dana Farber Cancer Institute/Brigham and Women’s PROFILE study from 2013-2018, imaging reports following first palliative-intent systemic therapy were annotated using natural language processing (NLP) models trained to capture cancer progression according to the structured “PRISSMM” framework. NLP-based cancer progression and imaging report frequency were jointly modeled using inverse-intensity weighted generalized estimated equations, censored at six months, to explore associations between alterations in lung cancer biomarkers (ALK, EGFR, ROS1, BRAF, KRAS, SMARCA4) and progression. Among patients with KRAS mutations who received immunotherapy, we also analyzed the association between STK11 mutations and progression. The novel outcome generated by the model – imaging report-based progression (iPROG) – corresponded to the difference in the mean log odds of progression per inverse-intensity weighted report associated with a given biomarker; it was reported as adjusted mean probability and in exponentiated form as an odds ratio (OR). Results: Among 690 patients with lung adenocarcinoma, associations between tumor mutations and the iPROG outcome are listed in the Table. Conclusions: A deep NLP model applied to EHR data can capture a novel cancer progression outcome, which is associated with known prognostic markers in lung cancer. Application of this method to large “real world” datasets, with attention to interactions between treatment and genomics, could speed biomarker discovery. [Table: see text]

Updated overall survival (OS) and genomic analysis from a single-arm phase II study of dabrafenib (D) + trametinib (T) in patients (pts) with BRAF V600E mutant (Mut) metastatic non-small cell lung cancer (NSCLC)

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Background: The phase II multicenter, open label study, which evaluated efficacy and safety of D+T in pretreated (cohort B) and treatment (tx)-naive (cohort C) pts with BRAF V600E mut metastatic NSCLC. The results of the primary analysis have been reported. Here, we present an updated survival and genomic analysis data for cohorts B and C. Methods: Tx-naïve (n=36) and pretreated (n=57) pts received D 150 mg twice daily + T 2 mg daily. Primary objective: ORR, secondary objectives: PFS, DOR, OS, safety, tolerability and PK of D+T. Tumor samples were centrally tested using a NGS cancer targeted panel (Oncomine Dx Target test, ThermoFisher Scientific). KM curves and Cox regression models were used to evaluate potential associations between baseline genomic landscape and pt efficacy endpoints. Results: As of June 22, 2019, median (m) follow-up was 16.3 mo in tx-naïve pts and 16.6 mo in pretreated pts. mOS was 17.3 mo (95% CI: 12.3, 40.2; 3 yr OS: 40%) and 18.2 mo (95% CI: 14.3, 28.6; 3 yr OS: 33%) with 14/36 and 11/57 pts alive in tx naïve and pretreated pts respectively. Detailed efficacy results are presented in table. 57/62 tumor samples retrieved from 93 pts were centrally confirmed to have BRAF V600E mut; 5 non-confirmed BRAF tumors (3 pts had PR) were positive for c-MET T1010I, KRAS G12V, ALK fusion and 2 JAK3 S493C with mPFS of 13.8 mo while OS was NE due to limited data points. Eleven pts (18%) had concomitant somatic mutations and/or genetic alterations in addition to BRAF V600E mut: 4 had alterations within PI3K pathway4 had concomitant mutations at IDH1 R132X, and 3 pts had additional mutations at BRAF G466V, KRAS G13C and a cMET exon 14 skipping, respectively. Pts whose tumors had concomitant genetic alterations, particularly in PI3K pathway, showed a trend towards decreased PFS and OS. Safety profile was similar to previous reported results. Conclusions: This update of BRF113928 study reported improved and durable OS rates with combination D+T in BRAF V600E mut NSCLC pts. Co-occurring genetic alterations might influence clinical outcomes of such pts. Further validation is ongoing to corroborate current genomic findings. Clinical trial information: NCT01336634 . [Table: see text]

Genomic profiling of breast cancer brain metastases reveals targetable alterations

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Background: Genomic characterization of breast cancer brain metastases (BCBMs) has thus far been limited. The objective of this study was to describe the landscape of genomic alterations in patients (pts) with BCBMs. Methods: Targeted next-generation DNA sequencing of > 300 cancer-related genes (OncoPanel) was prospectively performed on primary and metastatic (met) tumors in 321 pts with a diagnosis of BCBM between August 2016 and April 2019 at Dana-Farber Cancer Institute (table). Enrichment analysis of genomic alterations was performed using a two-sided Fisher exact test and differences in tumor mutation burden (TMB) between groups were assessed using two-sided Mann-Whitney U test. Multiple comparison correction was performed using the Benjamini-Hochberg procedure. Results: All subtypes were represented in BCBM (25 HR+/HER2-; 24 HR+/HER2+; 27 HR-/HER2+; 18 TNBC; 5 unknown; n = 99) and extracranial (EC) samples: (96 HR+/HER2-; 32 HR+/HER2+; 22 HR-/HER2+; 41 TNBC; 31 unknown; n = 222). BCBMs were found most commonly to have mutations or copy number alterations in TP53, ERBB2, PIK3CA, GATA3, PTEN, ESR1, CDH1, BRCA2, ARID1A, BRCA1 (>5% frequency, table). Two pts acquired ERBB2 amplification (amp) between the matched primary breast sample and brain met. In pair-wise comparisons of BCBMs to unmatched primaries or EC mets, only ERBB2 amp was significantly enriched (table, † = adjusted p < 0.05). There was no significant difference in TMB between BCBM and EC mets (median 9.12 vs 7.26, p = 0.15). In contrast, TMB was significantly higher in BCBMs compared to unmatched primaries (median 9.12 vs 7.26, p=0.005). Conclusions: BCBMs display similar mutations and copy number alterations compared to primary tumors and EC mets in pts with BCBM. These data suggest that BCBMs contain actionable genomic alterations that are most often also reflected in EC disease. Alterations in ERBB2, PIK3CA/PTEN, and BRCA1/2 represent potentially targetable alterations in pts with BCBM. [Table: see text]

A single-cell and single-nucleus RNA-Seq toolbox for fresh and frozen human tumors

Single-cell genomics is essential to chart tumor ecosystems. Although single-cell RNA-Seq (scRNA-Seq) profiles RNA from cells dissociated from fresh tumors, single-nucleus RNA-Seq (snRNA-Seq) is needed to profile frozen or hard-to-dissociate tumors. Each requires customization to different tissue and tumor types, posing a barrier to adoption. Here, we have developed a systematic toolbox for profiling fresh and frozen clinical tumor samples using scRNA-Seq and snRNA-Seq, respectively. We analyzed 216,490 cells and nuclei from 40 samples across 23 specimens spanning eight tumor types of varying tissue and sample characteristics. We evaluated protocols by cell and nucleus quality, recovery rate and cellular composition. scRNA-Seq and snRNA-Seq from matched samples recovered the same cell types, but at different proportions. Our work provides guidance for studies in a broad range of tumors, including criteria for testing and selecting methods from the toolbox for other tumors, thus paving the way for charting tumor atlases.

The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.