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Purpose:Acquired resistance to next-generation ALK tyrosine kinase inhibitors (TKIs) is often driven by secondary ALK mutations. Here, we investigated utility of plasma genotyping for identifying ALK resistance mutations at relapse on next-generation ALK TKIs.Experimental Design:We analyzed 106 plasma specimens from 84 patients with advanced ALK-positive lung cancer treated with second- and third-generation ALK TKIs using a commercially available next-generation sequencing (NGS) platform (Guardant360). Tumor biopsies from TKI-resistant lesions underwent targeted NGS to identify ALK mutations.Results:By genotyping plasma, we detected an ALK mutation in 46 (66%) of 70 patients relapsing on a second-generation ALK TKI. When post-alectinib plasma and tumor specimens were compared, there was no difference in frequency of ALK mutations (67% vs. 63%), but plasma specimens were more likely to harbor ≥2 ALK mutations (24% vs. 2%, P = 0.004). Among 29 patients relapsing on lorlatinib, plasma genotyping detected an ALK mutation in 22 (76%), including 14 (48%) with ≥2 ALK mutations. The most frequent combinations of ALK mutations were G1202R/L1196M and D1203N/1171N. Detection of ≥2 ALK mutations was significantly more common in patients relapsing on lorlatinib compared with second-generation ALK TKIs (48% vs. 23%, P = 0.017). Among 15 patients who received lorlatinib after a second-generation TKI, serial plasma analysis demonstrated that eight (53%) acquired ≥1 new ALK mutations on lorlatinib.Conclusions:ALK resistance mutations increase with each successive generation of ALK TKI and may be underestimated by tumor genotyping. Sequential treatment with increasingly potent ALK TKIs may promote acquisition of ALK resistance mutations leading to treatment-refractory compound ALK mutations.

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Histologic transformation from non-small cell to small cell lung cancer has been reported as a resistance mechanism to targeted therapy in EGFR-mutant and ALK fusion-positive lung cancers. Whether small cell transformation occurs in other oncogene-driven lung cancers remains unknown. Here we analyzed the genomic landscape of two pre-mortem and 11 post-mortem metastatic tumors collected from an advanced, ROS1 fusion-positive lung cancer patient, who had received sequential ROS1 inhibitors. Evidence of small cell transformation was observed in all metastatic sites at autopsy, with inactivation of RB1 and TP53, and loss of ROS1 fusion expression. Whole-exome sequencing revealed minimal mutational and copy number heterogeneity, suggestive of “hard” clonal sweep. Patient-derived models generated from autopsy retained features consistent with small cell lung cancer and demonstrated resistance to ROS1 inhibitors. This case supports small cell transformation as a recurring resistance mechanism, and underscores the importance of elucidating its biology to expand therapeutic opportunities.

Purpose: Most ALK-positive lung cancers will develop ALK-independent resistance after treatment with next-generation ALK inhibitors. MET amplification has been described in patients progressing on ALK inhibitors, but frequency of this event has not been comprehensively assessed. Experimental Design: We performed FISH and/or next-generation sequencing on 207 posttreatment tissue (n = 101) or plasma (n = 106) specimens from patients with ALK-positive lung cancer to detect MET genetic alterations. We evaluated ALK inhibitor sensitivity in cell lines with MET alterations and assessed antitumor activity of ALK/MET blockade in ALK-positive cell lines and 2 patients with MET-driven resistance. Results: MET amplification was detected in 15% of tumor biopsies from patients relapsing on next-generation ALK inhibitors, including 12% and 22% of biopsies from patients progressing on second-generation inhibitors or lorlatinib, respectively. Patients treated with a second-generation ALK inhibitor in the first-line setting were more likely to develop MET amplification than those who had received next-generation ALK inhibitors after crizotinib (P = 0.019). Two tumor specimens harbored an identical ST7-MET rearrangement, one of which had concurrent MET amplification. Expressing ST7-MET in the sensitive H3122 ALK-positive cell line induced resistance to ALK inhibitors that was reversed with dual ALK/MET inhibition. MET inhibition resensitized a patient-derived cell line harboring both ST7-MET and MET amplification to ALK inhibitors. Two patients with ALK-positive lung cancer and acquired MET alterations achieved rapid responses to ALK/MET combination therapy. Conclusions: Treatment with next-generation ALK inhibitors, particularly in the first-line setting, may lead to MET-driven resistance. Patients with acquired MET alterations may derive clinical benefit from therapies that target both ALK and MET.

OBJECTIVE. ALK rearrangements are an established targetable oncogenic driver in non–small cell lung cancer (NSCLC). The goal of this study was to determine the imaging features of the primary tumor...

Purpose: Acquired resistance to next-generation ALK tyrosine kinase inhibitors (TKIs) is often driven by secondary ALK mutations. Here, we investigated utility of plasma genotyping for identifying ALK resistance mutations at relapse on next-generation ALK TKIs. Experimental Design: We analyzed 106 plasma specimens from 84 patients with advanced ALK-positive lung cancer treated with second- and third-generation ALK TKIs using a commercially available next-generation sequencing (NGS) platform (Guardant360). Tumor biopsies from TKI-resistant lesions underwent targeted NGS to identify ALK mutations. Results: By genotyping plasma, we detected an ALK mutation in 46 (66%) of 70 patients relapsing on a second-generation ALK TKI. When post-alectinib plasma and tumor specimens were compared, there was no difference in frequency of ALK mutations (67% vs. 63%), but plasma specimens were more likely to harbor ≥2 ALK mutations (24% vs. 2%, P = 0.004). Among 29 patients relapsing on lorlatinib, plasma genotyping detected an ALK mutation in 22 (76%), including 14 (48%) with ≥2 ALK mutations. The most frequent combinations of ALK mutations were G1202R/L1196M and D1203N/1171N. Detection of ≥2 ALK mutations was significantly more common in patients relapsing on lorlatinib compared with second-generation ALK TKIs (48% vs. 23%, P = 0.017). Among 15 patients who received lorlatinib after a second-generation TKI, serial plasma analysis demonstrated that eight (53%) acquired ≥1 new ALK mutations on lorlatinib. Conclusions: ALK resistance mutations increase with each successive generation of ALK TKI and may be underestimated by tumor genotyping. Sequential treatment with increasingly potent ALK TKIs may promote acquisition of ALK resistance mutations leading to treatment-refractory compound ALK mutations.

Introduction Circulating tumor DNA analysis is an emerging genotyping strategy that can identify tumor-specific genetic alterations in plasma including mutations and rearrangements. Detection of ROS1 fusions in plasma requires genotyping approaches that cover multiple breakpoints and target a variety of fusion partners. Compared to other molecular subsets of NSCLC, experience with detecting ROS1 genetic alterations in plasma is limited. Methods To describe the spectrum of ROS1 fusions in NSCLC and determine sensitivity for detecting ROS1 fusions in plasma, we queried the Guardant Health plasma dataset and an institutional tissue database and compared plasma findings to tissue results. In addition, we used the Guardant360 NGS assay to detect potential genetic mediators of resistance in plasma from patients with ROS1-positive NSCLC who were relapsing on crizotinib. Results We detected seven distinct fusion partners in plasma, most of which (n = 6 of 7) were also represented in the tissue dataset. Fusions pairing CD74 with ROS1 predominated in both cohorts (plasma: n = 35 of 56, 63%; tissue: n = 26 of 52, 50%). There was 100% concordance between the specific tissue- and plasma-detected ROS1 fusion for seven patients genotyped with both methods. Sensitivity for detecting ROS1 fusions in plasma at relapse on ROS1-directed therapy was 50%. Six (33%) of 18 post-crizotinib plasma specimens harbored ROS1 kinase domain mutations, five of which were ROS1 G2032R. Two (11%) post-crizotinib plasma specimens had genetic alterations (n = 1 each BRAF V600E and PIK3CA E545K) potentially associated with ROS1-independent signaling. Conclusions Plasma genotyping captures the spectrum of ROS1 fusions observed in tissue. Plasma genotyping is a promising approach to detecting mutations that drive resistance to ROS1-directed therapies.

Background Plasma genotyping is an emerging approach for the identification of genetic alterations mediating resistance to anaplastic lymphoma kinase (ALK)-targeted therapy. The authors reviewed plasma genotyping and imaging findings to assess the correlation between circulating tumor DNA (ctDNA) burden and disease burden in patients with ALK-positive lung cancer. Methods The authors analyzed 97 plasma specimens from 75 patients with ALK-positive lung cancer to identify ALK and non-ALK alterations. Disease burden was estimated by tabulating lesions per organ and calculating lesion diameters, areas, and volumes. Disease burden was correlated with the allelic frequency (AF) of plasma alterations. Results The mean interval between plasma collection and imaging was 8 days. ctDNA was detected in approximately 85% of plasma specimens. An ALK fusion and ALK mutation were detected in 79% and 76%, respectively, of plasma specimens. Using the maximum plasma alteration AF and maximum ALK alteration AF as independent surrogates of ctDNA burden, a higher disease burden measurement on imaging was found to be associated with higher ctDNA burden. Total body and extrathoracic tumor volume but not intrathoracic tumor volume correlated with ctDNA burden. Of all the disease sites assessed, the ctDNA burden correlated most with involvement of the liver, bones, and adrenal glands. Despite being the defining alteration in ALK-positive lung cancer, isolated plasma ALK fusion AF did not perform as well as the maximum plasma alteration AF or maximum ALK alteration AF for correlating tumor burden. Conclusions In patients with ALK-positive lung cancer, the maximum plasma alteration AF and maximum ALK alteration AF correlate with the extrathoracic burden of disease and are more predictive of tumor burden compared with the ALK fusion AF alone. Lay summary Analysis of genetic material shed from cancer cells into the circulation offers insights into the molecular composition of tumors. The circulating tumor DNA (ctDNA) varies over time and across individuals and is impacted by the distribution of disease. Herein, the authors estimated tumor burden on imaging and correlated it with ctDNA by calculating the maximum allelic frequency. The current study findings demonstrated that the greatest correlation exists between extrathoracic, extracranial tumor burden (particularly involvement of the liver, adrenal glands, or bones) and ctDNA burden, suggesting a biological basis for the interpatient and temporal intrapatient differences in ctDNA yield that have been described in previous studies.

Rearranged during transfection proto-oncogene (RET) fusions represent a potentially targetable oncogenic driver in non-small cell lung cancer (NSCLC). Imaging features and metastatic patterns of advanced RET fusion-positive (RET+) NSCLC are not well established. Our goal was to compare the imaging features and patterns of metastases in RET+, ALK+ and ROS1+ NSCLC. Patients with RET+, ALK+, or ROS1+ NSCLC seen at our institution between January 2014 and December 2018 with available pre-treatment imaging were identified. The clinicopathologic features, imaging characteristics, and the distribution of metastases were reviewed and compared. We identified 215 patients with NSCLC harboring RET, ALK, or ROS1 gene fusion (RET = 32, ALK = 116, ROS1 = 67). Patients with RET+ NSCLC were older at presentation compared to ALK+ and ROS1+ patients (median age: RET = 64 years, ALK = 51 years, p &lt, 0.001, ROS = 54 years, p = 0.042) and had a higher frequency of neuroendocrine histology (RET = 12%, ALK = 2%, p = 0.025, ROS1 = 0%, p = 0.010). Primary tumors in RET+ patients were more likely to be peripheral (RET = 69%, ALK = 47%, p = 0.029, ROS1 = 36%, p = 0.003), whereas lobar location, size, and density were comparable across the three groups. RET+ NSCLC was associated with a higher frequency of brain metastases at diagnosis compared to ROS1+ NSCLC (RET = 32%, ROS1 = 10%, p = 0.039. Metastatic patterns were otherwise similar across the three molecular subgroups, with high incidences of lymphangitic carcinomatosis, pleural metastases, and sclerotic bone metastases. RET+ NSCLC shares several distinct radiologic features and metastatic spread with ALK+ and ROS1+ NSCLC. These features may suggest the presence of RET fusions and help identify patients who may benefit from further molecular genotyping.

Introduction The current standard initial therapy for advanced ALK receptor tyrosine kinase (ALK)–positive NSCLC is a second-generation ALK tyrosine kinase inhibitor (TKI) such as alectinib. The optimal next-line therapy after failure of a second-generation ALK TKI remains to be established; however, standard options include the third-generation ALK TKI lorlatinib or platinum/pemetrexed-based chemotherapy. The efficacy of platinum/pemetrexed-based chemotherapy has not been evaluated in cases that are refractory to second-generation TKIs. Methods This was a retrospective study performed at three institutions. Patients were eligible if they had advanced ALK-positive NSCLC refractory to one or more second-generation ALK TKI(s) and had received platinum/pemetrexed-based chemotherapy. Results Among 58 patients eligible for this study, 37 had scans evaluable for response with measurable disease at baseline. The confirmed objective response rate to platinum/pemetrexed-based chemotherapy was 29.7% (11 of 37 patients; 95% confidence interval [CI]: 15.9% – 47.0%), with median duration of response of 6.4 months (95% CI: 1.6 months – not reached). The median progression-free survival for the entire cohort was 4.3 months (95% CI: 2.9 – 5.8 months). Progression-free survival was longer in patients who received platinum/pemetrexed in combination with an ALK TKI compared to those who received platinum/pemetrexed alone (6.8 months vs. 3.2 months, respectively; hazard ratio = 0.33; p = 0.025). Conclusions Platinum/pemetrexed-based chemotherapy shows modest efficacy in ALK-positive NSCLC after failure of second-generation ALK TKIs. The activity may be higher if administered with an ALK TKI, suggesting a potential role for continued ALK inhibition.

BACKGROUND: Acquired resistance to next-generation ALK tyrosine kinase inhibitors (TKIs) is often driven by secondary ALK mutations. Here we investigated utility of plasma genotyping for identifying ALK resistance mutations at relapse on next-generation ALK TKIs. METHODS: We analyzed 106 plasma specimens from 84 patients with advanced ALK-positive lung cancer treated with second- and third-generation ALK TKIs using a commercially available next-generation sequencing (NGS) platform (Guardant360). Tumor biopsies from TKI-resistant lesions underwent targeted NGS to identify ALK mutations. RESULTS: By genotyping plasma, we detected an ALK mutation in 46 (66%) of 70 patients relapsing on a second-generation ALK TKI. When post-alectinib plasma and tumor specimens were compared, there was no difference in frequency of ALK mutations (67% vs 63%), but plasma specimens were more likely to harbor ≥2 ALK mutations (24% vs 2%, p=0.004). Among 29 patients relapsing on lorlatinib, plasma genotyping detected an ALK mutation in 22 (76%), including 14 (48%) with ≥2 ALK mutations. The most frequent combinations of ALK mutations were G1202R/L1196M and D1203N/1171N. Detection of ≥2 ALK mutations was significantly more common in patients relapsing on lorlatinib compared to second-generation ALK TKIs (48% vs 23%, p=0.017). Among 15 patients who received lorlatinib after a second-generation TKI, serial plasma analysis demonstrated that 8 (53%) acquired ≥1 new ALK mutations on lorlatinib. CONCLUSIONS: ALK resistance mutations increase with each successive generation of ALK TKI and may be underestimated by tumor genotyping. Sequential treatment with increasingly potent ALK TKIs may promote acquisition of ALK resistance mutations leading to treatment-refractory compound ALK mutations.

ROS proto-oncogene 1 (ROS1) rearrangements are a known molecular target in non-small-cell lung cancer (NSCLC). Our goal was to determine whether ROS1-rearranged NSCLC has imaging features and patterns of metastasis, which differ from those of anaplastic lymphoma kinase (ALK)-rearranged or epidermal growth factor receptor (EGFR)-mutant NSCLC.We retrospectively identified patients with metastatic ROS1-rearranged, ALK-rearranged, or EGFR-mutant NSCLC from January 2014 to June 2018 and included those with pretreatment imaging studies available. We assessed the imaging features of the primary tumor and the distribution of metastases in these patients. The Wilcoxon rank-sum test and Fisher exact test were used to compare the imaging features.We identified 257 patients (167 women and 90 men; median age, 56 years; range, 19-90 years) with metastatic NSCLC (ROS1, 53; ALK, 87; EGFR, 117). Compared with ALK-rearranged or EGFR-mutant NSCLC, ROS1-rearranged NSCLC was less likely to present with extrathoracic metastases (ROS1, 49%; ALK, 75%; EGFR, 72%; P .01), including brain metastases (ROS1, 9%; ALK, 25%; EGFR, 40%; P .04). Compared with EGFR-mutant NSCLC, ROS1-rearranged tumors were more likely to exhibit imaging features of lymphangitic carcinomatosis (ROS1, 42%; EGFR, 12%; P .01) and less likely to have air bronchograms in the primary tumor (ROS1, 2%; EGFR, 28%; P .01). ROS1-rearranged tumors were also more likely to present with distant nodal metastases (ROS1, 15%; EGFR, 2%; P .01) and sclerotic-type bone metastases (ROS1, 17%; EGFR, 6%; P .01).Although considerable overlap exists in the imaging features of ROS1-rearranged, ALK-rearranged, and EGFR-mutant NSCLC, we found that ROS1-rearranged NSCLC has certain distinct imaging features and patterns of spread.

Driver mutations alter cells from normal to cancer through several evolutionary epochs: premalignancy, early malignancy, subclonal diversification, metastasis and resistance to therapy. Later stages of disease can be explored through analyzing multiple samples collected longitudinally, on or between successive treatments, and finally at time of autopsy. It is also possible to study earlier stages of cancer development through probabilistic reconstruction of developmental trajectories based on mutational information preserved in the genome. Here we present a suite of tools, called Phylogic N-Dimensional with Timing (PhylogicNDT), that statistically model phylogenetic and evolutionary trajectories based on mutation and copy-number data representing samples taken at single or multiple time points. PhylogicNDT can be used to infer: (i) the order of clonal driver events (including in pre-cancerous stages); (ii) subclonal populations of cells and their phylogenetic relationships; and (iii) cell population dynamics. We demonstrate the use of PhylogicNDT by applying it to whole-exome and whole-genome data of 498 lung adenocarcinoma samples (434 previously available and 64 of newly generated data). We identify significantly different progression trajectories across subtypes of lung adenocarcinoma (EGFR mutant, KRAS mutant, fusion-driven and EGFR/KRAS wild type cancers). In addition, we study the progression of fusion-driven lung cancer in 21 patients by analyzing samples from multiple timepoints during treatment with 1st and next generation tyrosine kinase inhibitors. We characterize their subclonal diversification, dynamics, selection, and changes in mutational signatures and neoantigen load. This methodology will enable a systematic study of tumour initiation, progression and resistance across cancer types and therapies.

9067 Background: Second-generation (gen) ALK tyrosine kinase inhibitors (TKIs) are standard first- and second-line therapies in patients (pts) with advanced ALK+ non-small cell lung cancer (NSCLC). After progression on second-gen TKI(s), standard options include platinum (PT)-based chemotherapy (chemo) or the third-gen ALK TKI lorlatinib. The efficacy of PT-based chemo is established in treatment-naive pts but is undefined in pts who have failed prior ALK TKIs. Here we evaluate the efficacy of PT/pemetrexed (pem)-based chemo in pts with ALK+ NSCLC refractory to second-gen TKIs. Methods: A retrospective study was performed at three institutions. Pts were eligible if they had advanced ALK+ NSCLC refractory to ≥1 second-gen TKI, and received PT-pem-based chemo. Medical records and imaging were reviewed to determine outcomes. Results: Among 55 eligible pts, chemo regimens included: PT/pem (31/55, 56%), PT/pem/bevacizumab (bev) (6/55, 11%), PT/pem/PD-1 inhibitor (3/55, 5%), PT/pem with ALK TKI (8/55, 15%), PT/pem/bev with TKI (6/55, 11%), and PT/pem/PD-1 inhibitor with TKI (1/55, 2%). Pts had received one (6/55, 11%), two (38/55, 69%), or more (11/55, 20%) prior TKIs. Six pts (11%) previously received adjuvant or neoadjuvant chemo. Radiographic data for response evaluation was available for 39 pts. Among 36 pts with measurable baseline disease, confirmed ORR was 31% (11/36; 95% CI, 16-48%); 13 (36%) had stable disease. The median duration of response was 5.4 months (95% CI, 1.5-7.1 months). The median progression-free survival (PFS) for the entire cohort was 4.0 months (95% CI, 2.8-4.6 months). Chemo (PT/pem +/- bev or PD-1 inhibitor) plus ALK TKI (n = 15) was associated with a significant increase in PFS compared to chemo without TKI (n = 40) (median PFS 6.8 vs 3.2 months; HR 0.306; p = 0.002). Similarly, PT/pem plus ALK TKI (n = 8) was associated with increased PFS compared to PT/pem without TKI (n = 31) (median PFS 6.8 vs 2.9 months; HR 0.358; p = 0.036). Conclusions: The efficacy of PT-pem-based chemo is limited after failure of second-gen ALK TKIs but may be higher in pts who receive chemo plus ALK TKI, suggesting a potential role for ongoing ALK inhibition. The modest benefit of PT-pem-based chemo highlights the need for other therapeutic strategies for pts refractory to second-gen TKIs.

3079 Background: ALK tyrosine kinase inhibitors (TKIs) are effective in treating advanced anaplastic lymphoma kinase (ALK) fusion-positive non-small-cell lung cancers (NSCLC), and specific ALK variants are associated with the development of resistance to specific TKIs. Humans struggle to harness the full potential of the highly complex next-generation sequencing bioinformatics pipeline output. As a consequence, the decision to report a variant remains difficult, and we considered the discrete nature of the data and the binary decision (report vs. not-report) as an ideal setting to apply an artificial intelligence (AI) approach for variant reporting. Methods: We assessed diagnostic performance of an AI model in calling ALK-resistance mutations in n = 50 consecutive ALK fusion positive patients who relapsed on TKI-therapy and underwent repeat biopsy at MGH. The random forest model was derived from independent datasets (training and validation) capturing the reporting decision on > 36,000 variants with ~500 features per variant resulting in a matrix of > 18 million data points. The model output is a contiguous prediction score from 0 (not report) to 1 (report) and a visual drill-down functionality allows exploration of the underlying features that contributed to the decision. Results: Examination of n = 76 tests from n = 50 patients with a total of n = 130 reported variants (and = 115 not reported variants) included a total of n = 31 ALK point mutations: p.1156(n = 2), p.1171(n = 8), p.1174(n = 2), p.1180(n = 2), p.1196(n = 1), p.1198(n = 1), p.1202(n = 8), p.1203(n = 1), p.1204(n = 1), p.1206(n = 1), p.1269(n = 4). Setting a screening threshold of the model at > 10% for reporting showed only one false-negative (p.Ile1171Asn) variant and 96.7% sensitivity. The average model score for ALK variants was 0.664 (range: 0.08–0.98; median 0.8) and did not show significant differences from other reported variants (0.636; 0–1; 0.7; t-test 0.66). The model would have called n = 18 of the non-reported control variants (average 0.07; range < 0.001–0.64; P < 0.0001) and was 84% specific. Review of the drill-down function identified prior call frequency, allelic ratio, and predicted transcript consequences as common model features. Importantly, the model is currently agnostic to the medical literature and does not take clinical parameters (e.g. TKI type) into account, which may further improve performance. Conclusions: Applying artificial intelligence to large discrete datasets is one approach to help identify clinically relevant variants in the setting of ALK resistance in ALK-fusion positive NSCLC.