Citations

8617 Background: Dato-DXd is an antibody-drug conjugate (ADC) composed of an anti-TROP2 monoclonal antibody linked to a potent topoisomerase I inhibitor payload. We report updated findings from TROPION-Lung02 (NCT04526691) evaluating Dato-DXd plus pembro with or without Pt-CT as 1L therapy for aNSCLC. Methods: Patients (Pts) received Dato-DXd (4 or 6 mg/kg) plus pembro 200 mg alone (doublet) or with Pt-CT (triplet; cisplatin 75 mg/m2 or carboplatin AUC 5) Q3W across 6 cohorts. Pts in the expansion stage were primarily treatment (tx)-naïve. PD-L1 expression was evaluated by tumor proportion score (TPS < 50% or ≥50%) using immunohistochemistry (22C3 assay). The primary objectives were safety and tolerability, with efficacy a secondary objective. Results: 96 pts were treated with doublet (n = 42) or triplet (n = 54) therapy in the 1L setting. At data cutoff (Oct 31, 2023), 45% and 20% of pts receiving doublet or triplet tx were ongoing. Median age was 66 years in both subgroups. Median treatment durations were 6.6 and 5.8 months. Across doublet and triplet tx, the most common any-grade (Gr) treatment-emergent adverse events (TEAEs) were stomatitis (57%, 33%) and nausea (40%, 46%), mainly Gr 1–2. Gr ≥3 TEAEs were seen in 57% and 76% of pts; serious TEAEs in 38% and 44%. TEAEs associated with Dato-DXd discontinuation occurred in 29% and 39% of pts receiving doublet or triplet tx. TEAEs associated with death were seen in 2% and 9%, none considered related to study drug. Efficacy outcomes, including ORR and preliminary PFS, in the 1L setting overall and by PD-L1 status are summarized in the Table. Conclusions: As 1L therapy for aNSCLC, Dato-DXd plus pembro with or without Pt-CT continues to demonstrate durable antitumor activity. Efficacy was observed regardless of PD-L1 expression. Tolerability of the combinations was as expected based on known profiles of the individual agents, with no new safety signals observed. To date, this is the largest dataset reported for any ADC combined with an anti-PD-1/L1 agent in the 1L setting for aNSCLC. Clinical trial information: NCT04526691 . [Table: see text]

NGS used to diagnose and treat NSCLC patient with initial concern for metaplastic breast cancer

e15046 Background: ctDNA assays can be used to assess molecular residual disease, and the value of ctDNA monitoring in disease surveillance and treatment response assessment has been demonstrated in colon, breast, lung, and bladder cancers. However, the data of ctDNA in rare cancers has been lacking. We conducted this retrospective study to investigate the potential roles of ctDNA monitoring in rare tumors in both surveillance and response evaluation. Methods: ctDNA assay results of 12 patients (pts) with rare cancers including adrenocortical carcinoma (ACC) (4 pts), salivary gland cancers (3 pts), pleural or peritoneal malignant mesothelioma (4 pts), and anaplastic thyroid cancer (ATC) (1pt) undergoing treatment or surveillance in 2023 at Mayo Clinic Florida were analyzed. The trends of ctDNA levels were correlated with radiographic images findings. Results: Among the 12 patients, ctDNA was detected in at least one time point in 9 (75%) pts, including 1 (100%) ATC pt, 2 (66%) salivary gland pts, 3 (75%) malignant mesothelioma pts, and 3 (75%) ACC pts. Among these 9 pts, 5 pts had ctDNA collected at more than one timepoints, and the trends of ctDNA levels were consistent with image findings in all 5 pts. Among these 5 pts, one pt received definitive surgery for ACC with clearance of ctDNA after the surgery and one salivary gland cancer pt was undergoing surveillance and later developed disease progression. The other 3 pts were undergoing palliative systemic therapy and had responded to treatments. Conclusions: ctDNA was detectable in majority of the patients with rare malignancies reviewed in this study, including ACC, ATC, pleural or peritoneal malignant mesothelioma, and salivary gland cancers. Further study is warranted to investigate the role of ctDNA monitoring in surveillance and treatment response evaluation in rare malignancies.

Abstract Objectives Precise literature recommendation and summarization are crucial for biomedical professionals. While the latest iteration of generative pretrained transformer (GPT) incorporates 2 distinct modes—real-time search and pretrained model utilization—it encounters challenges in dealing with these tasks. Specifically, the real-time search can pinpoint some relevant articles but occasionally provides fabricated papers, whereas the pretrained model excels in generating well-structured summaries but struggles to cite specific sources. In response, this study introduces RefAI, an innovative retrieval-augmented generative tool designed to synergize the strengths of large language models (LLMs) while overcoming their limitations. Materials and Methods RefAI utilized PubMed for systematic literature retrieval, employed a novel multivariable algorithm for article recommendation, and leveraged GPT-4 turbo for summarization. Ten queries under 2 prevalent topics (“cancer immunotherapy and target therapy” and “LLMs in medicine”) were chosen as use cases and 3 established counterparts (ChatGPT-4, ScholarAI, and Gemini) as our baselines. The evaluation was conducted by 10 domain experts through standard statistical analyses for performance comparison. Results The overall performance of RefAI surpassed that of the baselines across 5 evaluated dimensions—relevance and quality for literature recommendation, accuracy, comprehensiveness, and reference integration for summarization, with the majority exhibiting statistically significant improvements (P-values &lt;.05). Discussion RefAI demonstrated substantial improvements in literature recommendation and summarization over existing tools, addressing issues like fabricated papers, metadata inaccuracies, restricted recommendations, and poor reference integration. Conclusion By augmenting LLM with external resources and a novel ranking algorithm, RefAI is uniquely capable of recommending high-quality literature and generating well-structured summaries, holding the potential to meet the critical needs of biomedical professionals in navigating and synthesizing vast amounts of scientific literature.

Abstract Background Metaplastic breast carcinoma (MBC) is an unusual malignancy that presents a diagnostic challenge due to the presence of varying cytomorphologies that can be seen in benign and malignant tumors. We posit that metastatic disease to the breast, itself an uncommon entity, should be considered in the differential diagnosis of MBC. We report a unique case of metastatic non-small cell lung cancer (NSCLC) with an actionable driver mutation that presented as a symptomatic breast mass and was initially considered to represent MBC. Report A 74-year-old woman with a 22-pack-year smoking history presented to the breast clinic complaining of a palpable left breast mass that had grown rapidly over the previous month. Ultrasound-guided biopsy of the breast mass revealed high-grade poorly differentiated carcinoma. On immunohistochemical (IHC) evaluation, tumor cells were strongly positive for epithelial markers CAM5.2 and keratin AE1/AE3, weakly positive for breast cancer (BC) marker TRPS1, and negative for BC marker GATA3, squamous cell carcinoma markers p63 and CK5, and melanoma marker SOX10. Metaplastic triple-negative BC was diagnosed. However, concern remained for metastasis from a non-breast primary tumor due to the patient’s constitutional symptoms such as fatigue, night sweats, and 60-pound unintentional weight loss over the previous year, as well as interval development of a suspicious nodular rash on her right upper extremity. An FDG-PET-CT was obtained and demonstrated a hypermetabolic left lung consolidation (maximum SUV 33.3) measuring 7.2 cm, pulmonary nodules, and extensive thoracic lymphadenopathy. Due to rising suspicion for a primary lung tumor, additional IHC staining on the original breast biopsy was requested. Tumor cells were positive for TTF-1, consistent with metastatic lung adenocarcinoma. Tissue next-generation sequencing (NGS) identified a MET exon 14 skipping mutation, making the patient eligible for treatment with capmatinib, a first-line kinase inhibitor targeted therapy for metastatic NSCLC. At the time of this report, the patient has completed a course of palliative stereotactic body radiation therapy to the left lung and started capmatinib 400 mg BID, which she is tolerating well. Her first restaging scans after treatment initiation will be obtained one week after the time of this report. Conclusion In the absence of heightened suspicion for a non-breast primary tumor, our patient had initially received a diagnosis of triple-negative MBC. This diagnosis would have exposed her to increased treatment-related toxicities from cytotoxic chemotherapy and poor prognosis from MBC without survival benefit from targeted therapy for NSCLC. We advocate for the use of supplemental body imaging, expert and comprehensive IHC evaluation, and multidisciplinary discussion in cases of MBC and undifferentiated breast malignancy to facilitate accurate diagnosis and treatment. Citation Format: Tanmayi Pai, Marte Wasserman, Jason Lewis, Miglena Komforti, James Jakub, Augustine Lee, Yanyan Lou, Pooja Advani, Rohit Rao. Metastatic Lung Cancer Masquerading as Metaplastic Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-20-08.

Abstract Background: Based on preclinical data showing addition of CDK4/6 inhibitors to gemcitabine is synergistic, ribociclib was evaluated in combination with gemcitabine to determine the maximum tolerated dose (MTD) and dose limiting toxicities (DLT). Methods: In this single arm multicohort phase I trial, we evaluated the safety and efficacy of Ribociclib plus Gemcitabine in patients with advanced solid tumors. Patients received Gemcitabine intravenously on days 1 and 8 followed by Ribociclib days 8–14, with treatment repeated every 3 weeks. Results: The study enrolled 43 patients between October 2017 and September 2019. The escalation phase (19 patients) determined the MTD and recommended phase II dose (RP2D) to be ribociclib 800mg daily and gemcitabine 1000mg/m2 for the expansion phase (24 patients). One patient experienced Grade 4 thrombocytopenia. Eleven patients experienced Grade 3 adverse events (AE), the most common being neutropenia, thrombocytopenia, and anemia. No partial or complete responses were observed. 15/22 (68%) of efficacy evaluable patients who received the MTD achieved best response of stable disease. Conclusions: The addition of Ribociclib to Gemcitabine was tolerated well and yielded stability of tumors in both cohorts. Ribociclib and gemcitabine could have synergistic activity in certain tumor types, and our data provides support for the combination. Clinical Trial Registration: NCT03237390

PURPOSE KRAS is the most commonly mutated driver oncogene in non–small cell lung cancer (NSCLC). Sotorasib and adagrasib, KRAS G12C inhibitors, have been granted accelerated US approval; however, hepatotoxicity is a common side effect with higher rates in patients treated with sotorasib proximal to checkpoint inhibitor (CPI) therapy. The aim of this study was to assess the feasibility and safety of adagrasib after discontinuation of sotorasib because of treatment-related grade 3 hepatotoxicity through real-world and clinical cases. METHODS Medical records from five patients treated in real-world settings were retrospectively reviewed. Patients had locally advanced or metastatic KRAS G12C -mutated NSCLC and received adagrasib after sotorasib in the absence of extracranial disease progression. Additional data were collected for 12 patients with KRAS G12C -mutated NSCLC enrolled in a phase Ib cohort of the KRYSTAL-1 study and previously treated with sotorasib. The end points associated with both drugs included timing and severity of hepatotoxicity, best overall response, and duration of therapy. RESULTS All patients were treated with CPIs followed by sotorasib (initiated 0-64 days after CPI). All five real-world patients experienced hepatotoxicity with sotorasib that led to treatment discontinuation, whereas none experienced treatment-related hepatotoxicity with subsequent adagrasib treatment. Three patients from KRYSTAL-1 transitioned from sotorasib to adagrasib because of hepatotoxicity; one experienced grade 3 ALT elevation on adagrasib that resolved with therapy interruption and dose reduction. CONCLUSION Adagrasib may have a distinct hepatotoxicity profile from sotorasib and is more easily combined with CPIs either sequentially or concurrently. These differences may be used to inform clinical decisions regarding an initial KRAS G12C inhibitor for patients who recently discontinued a CPI or experience hepatotoxicity on sotorasib.

Abstract Background: Immune checkpoint inhibitors (ICIs) have significantly improved outcomes for patients with metastatic non-small cell lung cancer (NSCLC). However, clinical management is challenging. The PD-L1 biomarker does not optimally guide the choice between ICI monotherapy and combination ICI-chemotherapy, and there are currently no biomarkers to predict immune-related adverse events (irAEs). Here, we describe a versatile platform based on plasma proteomics and machine learning for generating predictive tools to support treatment decisions. Methods: Pre-treatment plasma samples were collected from 616 NSCLC patients receiving ICI-based therapy (NCT04056247). Clinical benefit (CB) data and irAEs were recorded. Proteomic profiling of plasma samples was performed using the SomaScan® assay, covering ~7000 proteins per sample. Proteins associated with Clinical Benefit (progression-free survival at 12 months) were classified as resistance-associated proteins (RAPs). Proteins associated with grade ≥3 irAEs occurring within the first 100 days of treatment were classified as toxicity-associated proteins (TAPs). RAPs and TAPs were integrated into two separate machine learning-based models, yielding CB and irAE probabilities, respectively. The CB model used a CB probability threshold to assign patients a PROphet-positive or PROphet-negative result. Bioinformatic analysis was performed on RAPs and TAPs. Results: CB and irAE models displayed strong predictive performance with a high correlation between predicted probability and observed CB or irAE rate (CB model: R2=0.98; p-value&lt;0.0001; irAE model: R2= 0.92; p-value &lt;0.0001). In the CB model, patients classified as PROphet-positive achieved significantly longer overall survival (OS) than PROphet-negative patients, with a median OS of 25.9 vs. 10.8 months (hazard ratio, HR = 0.51; p-value&lt;0.001). Furthermore, patients with PD-L1 ≥50% tumors and a PROphet-negative result had significantly longer OS with ICI-chemotherapy in comparison to ICI monotherapy (HR=0.23, p-value = 0.0003), suggesting that combination therapy is preferable for such patients despite high PD-L1 levels. Bioinformatic analysis showed that RAPs related to immune regulation, angiogenesis, chemo-resistance, and other potential resistance mechanisms displayed higher expression levels in patients who did not benefit from treatment. Neutrophil- and inflammation-related proteins were significantly enriched in patients who experienced irAEs. Conclusions: We describe two machine-learning based predictive tools that may be used separately or in combination to inform treatment decisions based on the patient’s likelihood to benefit from ICI therapy and to develop serious irAEs. Our findings also provide biological insights related to treatment resistance and immune-related toxicity. Citation Format: Michal Harel, Petros Christopoulos, Igor Puzanov, Jair Bar, Iris Kamer, Niels Reinmuth, Ina Koch, Mor Moskovitz, Adva Levy-Barda, Alona Zer, Michal Lotem, David Farrugia, Rivka Katzenelson, Gillian Price, Abed Agbarya, Helen Cheley, Adam Hassani, Mahmoud Abu-Amna, Tom Geldart, Anirban Chatterjee, Andreas Polychronis, Maya Gottfried, Yanyan Lou, Tatiana Harkovsky, Alison Brewster, Ido Wolf, Ella Tepper, Ben Yellin, Itamar Sela, Coren Lahav, Yehonatan Elon, Raya Leibowitz, Adam P. Dicker, Young Kwang Chae, Ryan J. Sullivan, David Carbone, David Gandara, Jarushka Naidoo. Plasma proteomics-based models for predicting therapeutic benefit and immune-related adverse events in non-small cell lung cancer patients treated with immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1208.

PURPOSE Current guidelines for the management of metastatic non–small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. PATIENTS AND METHODS We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247 ) of patients undergoing PD-1/PD-L1 inhibitor–based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. RESULTS Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor–based treatments, evidenced by high concordance between predicted and observed CB ( R 2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). CONCLUSION Plasma proteome–based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor–based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

Docetaxel +/− ramucirumab remains the standard-of-care therapy for patients with metastatic non-small-cell lung cancer (NSCLC) after progression on platinum doublets and immune checkpoint inhibitors (ICIs). The aim of our study was to investigate whether the cancer gene mutation status was associated with clinical benefits from docetaxel +/− ramucirumab. We also investigated whether platinum/taxane-based regimens offered a better clinical benefit in this patient population. A total of 454 patients were analyzed (docetaxel +/− ramucirumab n=381; platinum/taxane-based regimens n=73). Progression-free survival (PFS) and overall survival (OS) were compared among different subpopulations with different cancer gene mutations and between patients who received docetaxel +/− ramucirumab versus platinum/taxane-based regimens. Among patients who received docetaxel +/− ramucirumab, the top mutated cancer genes included TP53 (n=167), KRAS (n=127), EGFR (n=65), STK11 (n=32), ERBB2 (HER2) (n=26), etc. None of these cancer gene mutations or PD-L1 expression was associated with PFS or OS. Platinum/taxane-based regimens were associated with a significantly longer mQS (13.00 m, 95% Cl: 11.20–14.80 m versus 8.40 m, 95% Cl: 7.12–9.68 m, LogRank P=0.019) than docetaxel +/− ramcirumab. Key prognostic factors including age, histology, and performance status were not different between these two groups. In conclusion, in patients with metastatic NSCLC who have progressed on platinum doublets and ICIs, the clinical benefit from docetaxel +/− ramucirumab is not associated with the cancer gene mutation status. Platinum/taxane-based regimens may offer a superior clinical benefit over docetaxel +/− ramucirumab in this patient population.