Parikh, Kaushal

Targeted therapies have changed the treatment landscape of non-small-cell lung cancer and led to improved patient survival across all stages of lung cancer. Newer advances in common and novel oncogenic drivers continue to occur at vigorous speed, making it challenging to stay up to date with the rapidly evolving field. In this article, we review the emerging perspectives in the treatment of actionable targets in lung cancer. We focus on the development of newer KRAS-directed therapies, particularly on non-G12C mutations, pan-RAS inhibitors, and RAS-GTP inhibitors. We also describe the current standard of care for EGFR- and ALK-altered NSCLC and dive into the novel treatments expected to be in the clinic soon. A similar approach is taken toward MET, HER2, RET, ROS1, and FGFR alterations as emerging targets in non-small-cell lung cancer. Finally, we conclude this review with the current body of evidence for targeting TROP-2 as a novel target, potentially of importance in post-targeted therapy scenarios.

e20588 Background: MET exon 14 skipping mutations are seen in about 3% of patients (pts) with NSCLC, with 2 FDA approved METi for pts with stage IV NSCLC harboring it. Besides the original clinical trials, there is a paucity of real-world data about their outcomes, and adverse events (AE). Our aim was to compare and analyze the utilization of capmatinib (cap) and tepotinib (tep) in this population. Methods: We performed a retrospective chart review of the electronic medical records of all pts with stage IV NSCLC treated with METi between the date of FDA-accelerated approval of these drugs, 5/6/20 for cap and 2/3/21 for tep, and 12/1/23. All pts were treated at the Mayo Clinic Health System. We collected data about baseline characteristics, diagnosis, AE, and outcomes. Chi-squared test was used to compare the frequency of AE, while Kaplan-Meier method was used to calculate median progression free survival (mPFS). Results: A total of 49 pts were treated with METi. Cap was used in 45 pts, 14 received tep, and 10 pts received both, with tep following cap. In the cap group, median age of diagnosis was 74 years (y), 42.22% were male, and the median number of previous lines of therapy (mPLT) was 0. In the tep group, median age of diagnosis was 72 y, 21.43% were male, and the mPLT was 2. Median ECOG at the time of diagnosis was 1 in both groups. There was no statistically significant difference between AE in both groups. Peripheral edema occurred in 75.56% pts who received cap, and in 64.29% with tep (p = 0.41). Pneumonitis happened in 4.44% with cap, and 7.14% with tep (p = 0.69). Creatinine elevation was seen in 37.78% with cap, while 42.86% with tep (p = 0.73), grade 3 elevation was seen in 5.88% and 16.67% respectively. Abnormality in liver function tests occurred in 35.56% of pts in the cap group, and 28.57% in the tep group (p = 0.63), grade 3/4 abnormality occurred in 31.25% and 0% respectively. Finally, pancreatic enzymes elevation was seen in 33.33% of patients in each group (p = 0.67), with none being grade 3/4. Cap was discontinued in 20% of pts due to AE, while it happened in 28.57% of pts with tep. Dose reduction happened in 64.44% of pts who received cap, and 42.86% who received tep. The mPFS was 12.03 months (m) in the cap group, and 8.94 m in the tep group, which was not statistically significant (p = 0.18). Similarly, the mPFS in those treated with tep following cap was 8.94 m. Conclusions: We performed the first real-word comparison between cap and tep. The results demonstrated similar outcomes with both drugs, and no significant differences in AE, suggesting these agents can be employed equivalently. Importantly, rates of therapy discontinuation and dose reduction were high with both, indicating the importance of closely monitoring these pts. The retrospective nature and small sample size are initial limitations that can be overcome with future multi-centric prospective studies.

8071 Background: Data from the PACIFIC study demonstrated a 5-yr median progression free survival (PFS) and overall survival (OS) of 16.9 and 47.5 months respectively for patients with stage 3A and stage 3B NSCLC demonstrating a high risk of relapse. The 8th ed. of the IASLC staging project reports that the 60-month OS for stage 3A, B and C disease is 41%, 24% and 12% respectively, indicating that improved treatment options are needed for this patient population. Induction chemo-IO (ID chemo-IO) followed by concurrent chemo-radiation (CRT) has not been fully investigated due to concerns regarding the toxicity profile, but this may representant an important unexplored avenue for research. We aim to describe the outcomes of patients who received ID chemo-IO followed by CRT with or without maintenance IO. Methods: We conducted a retrospective study across all Mayo Clinic sites. Patients were included if they were diagnosed with Stage 3 NSCLC deemed ineligible for resection and/or requiring raditation over a large-field ] by a multidisciplinary team with plans for ID chemo-IO prior to CRT and maintenance IO. A total of 927 cases of stage 3 NSCLC patients were screened and those receiving ID chemo-IO followed by CRT were extracted (n = 36). Clinical endpoints are PFS, OS, overall response rate (ORR) and treatment related adverse events (TrAE) defined using CTCAE 5.0. Results: The median age was 67 years, 52.8% were female, all patients were past smokers and 97.2% identified as white. The tumor histologies were adenocarcinoma (66.67%), squamous (27.8%), mucinous adenocarcinoma (2.8%) and sarcomatoid (2.8%). Majority were Stage 3B (47.2%) followed by 3C (38.9%) and 3A (13.9%). N2 and N3 disease was noted in 36.1% and 55.6% of patients respectively. PD-L1 by IHC was > 1-49% (47.2%), > 50% (22.2%) and < 1% (19.4%). Patients received ID chemo-IO with pembrolizumab (83.3%), nivolumab (11.1%) and atezolizumab (2.78%). Average number of ID chemo-IO cycles were 3.67 cycles. The ORR to ID chemo-IO was 86.11%. The median PFS was 23.67 mths and the median OS was 32.07 months. About 94% of patients received CRT afterwards and 66.67% received maintenance IO with pembrolizumab (53.17%) or durvalumab (45.83%). Any grade TrAE occured in 58.33% of patients. Pneumonitis was the most common event (38.9%). Grade 3 -4 pneumonitis was noted in 28.5% (4/11) patients. Other toxicities included hepatitis (8.3%), colitis (11.1%) and myasthenia gravis (2.8%) and 22% of these TrAE’s were grade 3 or 4. Conclusions: Our results indicate that ID chemo-IO shows promise as a therapeutic approach for patients with unresectable stage III NSCLC, especially for patients deemed ineligible or high risk for upfront radiation. Further investigation is needed through a randomized clinical trial to systematically explore and validate the safety and efficacy of ID chemo-IO.

Abstract Background: Non-small cell lung cancer (NSCLC) makes up ~85% of lung cancers, and its major subtypes are adenocarcinoma (AD) and squamous cell carcinoma (SC). The histology classification of NSCLC has significant therapeutic and prognostic implications. As liquid biopsies are rapid and non-invasive, computational methods to classify NSCLC subtypes using cell-free DNA (cfDNA) are desired. Methods: Using The Cancer Genome Atlas (TCGA) NSCLC methylation data, we developed a method to classify AD and SC subtypes from cfDNA samples. We mapped TCGA methylation data to Guardant Infinity’s promoter regions and transformed them to allow for the transfer of the TCGA trained model to Infinity cfDNA epigenomic data. An advantage of this approach is that TCGA training data originates from the primary tumor, while cfDNA samples have low tumor fraction (TF) and may also contain signals from metastatic tumors. We trained a penalized Logistic Regression model with LASSO. To better fit the model to Infinity cfDNA data, we performed region filtering. Results: Our model effectively classified AD and SC subtypes from TCGA samples (AUC 0.97) (10-fold cross validation; Table 1). When evaluating on cfDNA samples with epigenomic TF ≥ 1%, the final model shows reasonable performance (AUC 0.94) (Table 1); the performance decreases when reduced to TF &gt; 0.05% (AUC 0.89) as expected (Table 1). When evaluating cfDNA from uncategorized lung samples, the predicted AD probabilities have significant association with KRAS mutations (p-value = 0.027). Conclusion: Our results show that the penalized Logistic Regression model trained with tissue TCGA methylation data through mapping, transformation, and region selection can classify NSCLC subtypes from cfDNA samples. This method may offer a fast, non-invasive tool to inform subtype-based clinical decisions, especially in the setting of poorly-differentiated carcinomas, and to identify subtype switches upon resistance to targeted therapies. Table 1: Model evaluation on tissue TCGA samples and cfDNA Infinity samples (different TF cutoffs) Sample type N samples AUC Accuracy Sensitivity Specificity Precision F1 score tissue TCGA 907 0.97 0.93 0.94 +/- 0.02 0.93 +/- 0.02 0.94 +/- 0.02 0.94 +/- 0.01 cfDNA Infinity 17 (TF ≥ 1%) 0.94 0.88 0.83 +/- 0.3 0.91 +/- 0.17 0.83 +/- 0.3 0.83 +/- 0.21 cfDNA Infinity 29 (TF &gt; 0.05%) 0.89 0.83 0.88 +/- 0.23 0.81 +/- 0.17 0.64 +/- 0.28 0.74 +/- 0.2 Citation Format: Laura Tung, Denis Tolkunov, Catalin Barbacioru, Deepika Kale, Scott Shell, Jill Tsai, Leylah Drusbosky, Kaushal Parikh, Han-Yu Chuang. Non-small cell lung cancer (NSCLC) histology classification using DNA methylation data captured from liquid biopsies [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 3499.

12051 Background: The combination of ipilimumab and nivolumab (Ipi-Nivo) is a standard of care regimen in many malignancies. However, immune-related adverse events (irAE) are common and are of great concern, especially when treating the elderly population. This subgroup of patients may be at greater risk for serious irAEs and be less able to tolerate the potential treatment side effects. We sought to retrospectively evaluate our experience treating elderly patients ≥ 80 years with Ipi-Nivo to characterize adverse events. Methods: A retrospective chart review of the electronic medical records of all patients treated with Ipi-Nivo at the Mayo Clinic Health System was performed. Patients with any solid tumor who received their first dose of Ipi-Nivo at the age of ≥ 80 were included. Records were analyzed for baseline characteristics, cancer type, toxicity, and response to therapy. Differences between continuous and categorical variables were assessed using the students’ t-test and the chi-squared test, respectively. Overall survival (OS) was estimated using the Kaplan-Meier method. Cox proportional hazard models assessed the relative contribution of factors to survival after treatment. P values < 0.05 were considered statistically significant. All analyses were performed using SAS V.9.4. Results: Forty-six patients met inclusion criteria, 13 females and 33 males. Median age of first dose was 83 (Range: 80 - 94). Sixty-seven percent had an ECOG performance status (PS) 0-1 and 33% had an ECOG PS 2-3. Thirteen (28.3%) patients received 4 cycles of Ipi-Nivo. Cancers included: 18 (40%) melanomas, 10 (21%) mesothelioma, 9 (19.5%) lung cancers, and 9 (19.5%) other types. Thirty-one patients (67%) developed at least one irAE. Of the irAEs, 8 (17.4%) were grade 1, 20 (43.5%) were grade 2, 14 (30.4%) were grade 3, and 3 (6.5%) were grade 4. Systemic steroids were used in 29 (63%) patients. Twenty-six (56.5%) patients were hospitalized for any cause, and 12 (26.1%) were hospitalized due to an irAE. Of the 26 patients hospitalized during treatment, 19 (73%) died within 1 year of discharge; 11 (42%) died within < 1 month of discharge and 3 (12%) died within 1-3 months of discharge. Median OS from the date of first Ipi-Nivo dose was 14.6 months in the ECOG PS 0-1 and 6.5 months in the ECOG PS 2-3. ECOG PS of 0-1 was associated with a significantly decreased risk of mortality (HR [hazard ratio] 0.33, 95 % CI [confidence interval]: 0.15-0.70; p=0.0025) compared to ECOG PS of 2-3. Conclusions: This is the first analysis to evaluate the outcomes of Ipi-Nivo in patients ≥ 80 years. Approximately 60% of the patients required systemic steroids and a quarter were hospitalized with grade 3-4 irAEs. As expected, patients with ECOG PS 2-3 did significantly worse than ECOG PS 0-1. Ipi-Nivo should be used with caution in patients ≥ 80 years.

9029 Background: Molecular biomarkers such as EML4-ALK fusion variant 3 (V3) and TP53 mutation are associated with poor prognosis in patients (pts) with anaplastic lymphoma kinase fusion positive ( ALK+) non–small cell lung cancer (NSCLC). We evaluated the effect of EML4-ALK fusion variants and TP53 mutation status on time to treatment discontinuation (TTD) of first-line (1L) treatment with a next-generation ALK tyrosine kinase inhibitor (TKI) in pts with ALK+ NSCLC in the real-world setting. Methods: Pts with advanced/metastatic NSCLC who were ALK+ in circulating tumor DNA by Guardant360 (G360) liquid biopsy test from Jan 1, 2018, to Dec 31, 2021, and received 1L monotherapy with a next-generation ALK TKI (alectinib, brigatinib, ceritinib, lorlatinib) were identified in the Guardant INFORM clinical-genomics database. Median TTD of 1L ALK TKI treatment was determined by Kaplan-Meier (KM) methods. The impact of EML4-ALK fusion variant and TP53 mutation status on TTD was evaluated. Results: Database search identified 495 pts with advanced/metastatic NSCLC who had ALK fusion by G360; of these, 214 pts received 1L treatment with a next-generation ALK TKI; 164 had G360 testing before treatment (alectinib, n=147; brigatinib, n=7; ceritinib, n=2; lorlatinib, n=8). Among these 164 pts, median age was 58.6 y, 53% were female, and 29% had baseline brain metastases. Median follow-up from start of 1L treatment was 14.8 mo. Median TTD was 19.6 mo (95% CI: 13.6–not reached [NR]). TP53 mutations were detected in 66 pts (40%). Median (95% CI) TTD in pts with TP53 mutation vs WT was 17.1 (9.5–28.5) vs 21.9 mo (14.3–NR; log-rank P=0.1712). Of 130 pts with EML4-ALK fusion variant type detected, 63 (48%) had V1, 54 (42%) V3, 8 (6%) V2, 4 (3%) V5, and 1 (1%) V8. In pts with EML4-ALK fusion V1 vs V3, median (95% CI) TTD was 19.0 (13.6–NR) vs 21.8 mo (8.7–NR; HR: 0.73; log-rank P=0.3039), with the KM plot showing numerically longer TTD in pts with V1 vs V3 during the first 18 mo and lines crossing at the tail end. Of 117 pts with both an EML4-ALK fusion variant (V1/V3) and TP53 data, 21 (18%) had both V3 and a TP53 mutation. Pts with co-occurring EML4-ALK V3 and TP53 mutation had the shortest TTD (median TTD 8.7 [3.9–NR; HR: 2.59; P=0.0219]; Table). Conclusions: Among pts with NSCLC and ALK fusion, co-occurrence of EML4-ALK V3 and TP53 mutation is common and associated with poor prognosis and high risk of early discontinuation of 1L treatment with a next-generation ALK TKI, most likely due to disease progression. Additional novel or combination therapies are warranted for this subpopulation. [Table: see text]

8567 Background: Adjuvant osimertinib (osi) improves disease-free survival (DFS) in patients (pts) with resected, early-stage, EGFR-mutant (EGFRmut) NSCLC, yet the benefit of osi after CRT in pts with unresectable locally advanced NSCLC is unknown. Post-hoc analysis of the PACIFIC trial showed a lack of survival benefit with consolidation durva versus placebo in pts with EGFRmut NSCLC. Comparisons between consolidation durva and EGFR TKIs in unresectable EGFRmut NSCLC following CRT are lacking. Methods: We conducted a multi-institutional retrospective analysis of pts with stage III unresectable EGFRmut NSCLC (exon19 deletion, exon21 L858R), who received EGFR TKI or durva after ≥ 2 cycles of platinum-based chemotherapy plus definitive radiation therapy between 2015-2022. Baseline characteristics including age, sex, smoking history, PD-L1 status, and outcomes on DFS, overall survival (OS), and safety were collected. Multivariable (MVA) cox regression analysis was used for statistical analysis. Treatment-related adverse events (trAE) were defined using CTCAE 5.0. Results: Seventeen pts from 12 institutions received an EGFR TKI (osi, n=15; erlotinib, n=2), and 13 pts received consolidation durva. Median follow-up was 23 months. Median age of all pts was 61 years (IQR:52-72) and 76.7% were female. Most pts in both groups had never-smoked and had adenocarcinoma. All pts received ≥ 60 Gy of radiation with concurrent chemotherapy. PD-L1 expression was ≥ 50% in 1/10 (10%) pts treated with durva vs 6/13 (46.2%) treated with TKI, p=0.09. Median duration on treatment for EGFR TKI and durva was 12.2 months and 4.8 months, respectively. Pts treated with EGFR TKI had significantly longer 24-month DFS versus pts treated with durva after adjusting for stage (3A vs 3B vs 3C) (Table). Any grade tRAE occurred in 58.8% (10/17) of pts treated with EGFR TKI vs 38.5% (5/13) with durva. Grade > 3 tRAE occurred in 15.4% (1 pneumonitis and 1 AST/ALT elevation) of pts treated with durva but in none of pts treated with EGFR TKI. Three pts within each arm came off treatment due to toxicity (EGFR TKI: 1 pneumonitis and 2 dermatitis; durva: 1 of each pneumonitis, Type 1 diabetes, AST/ALT elevation). Conclusions: EGFR TKI therapy after definitive CRT was associated with significantly longer DFS compared to durva in this retrospective study of pts with stage III unresectable EGFRmut NSCLC, without unanticipated safety signals. Follow-up is ongoing and OS outcomes will be evaluated subsequently. Further investigation is warranted to define the optimal therapy for locally advanced EGFRmut NSCLC. [Table: see text]

e13559 Background: Recent advances in targeted therapies have increased the survival and quality of life for non-small cell lung cancer (NSCLC) patients. Understanding clinical characteristics and predicting HER2 status may facilitate efficient use of next-generation sequencing (NGS) testing and promote precision medicine/targeted therapies. Methods: NSCLC patients ≤65 years old, diagnosed between 01/2011 and 06/2021 who have NGS test results were identified in from two National Cancer Institute designated cancer centers in the Northeastern region of the United States. Demographics, behavioral, and clinical characteristics were extracted from electronic health record (EHR) data and EHR-linked cancer registry. Prevalence prediction modelling of HER2/ERBB2 mutation was performed using machine learning (ML) methods including logistic regression (LR), random forest (RF), naïve Bayes (NB), extreme gradient boosting (XGBoost) and multi-layer perceptron (MLP). 10- fold cross validation and k-nearest neighbor method were used to impute missing values. Under-sampling, oversampling and feature selection methods were tried. Results: Among 761 NSCLC patients with NGS reports available, 353 (46%) were ≤65 years old. Among 353 (mean age 57, 58% female, 88% non-Hispanic, 69% white, 57% had metastasis, 58% prescribed chemotherapy) 25 (7%) had a HER2 mutation. Based on univariate significance tests with LR on the complete data: cerebrovascular disease, BMI between 27.5-29.9, KRAS, EGFR and MET were significant with odds ratios (ORs) ranging from 0.2-3.9. In our prediction models, BMI, cerebrovascular disease, weight loss, hepatic metastases, diabetes, congestive heart failure, and KRAS, EGFR, MET and RET alteration status were significant predictors in multivariate analyses, suggesting the potential usefulness of these features in predicting HER2 mutation among patients with NSCLC. Area under the ROC curve (AUC) varied across different models from 70.9% (RF), 70% (XGB and MLP), 69.5% (LR) to 68.2% (Naïve Bayes). The best performing model with RF yielding an AUC ~71% can provide relative high specificity and acceptable sensitivity depending on the cut off. Conclusions: Our prediction models yielded AUC around 70% with the best performing model’s AUC being 71% in a subgroup aged ≤65. After further validation, our prediction model may be used to identify patients appropriate for repeat NGS testing who did not have HER2 testing in first molecular profiling. Future work is needed to predict status in repeat testing with previously test negative patients who relapse or have progression of disease. Random forest (RF) Model performance across different cutoff for the predicted probability. [Table: see text]

The treatment metastatic non-small cell lung cancer (NSCLC) is largely influenced by the incorporation of immune checkpoint inhibitors (ICI) in the frontline setting. There are several ICI approved for the management of NSCLC based on the PD-L1 expression of the tumors. PD-L1 is a controversial biomarker with various inconsistencies in expression owing to temporal and spatial heterogeneity. Tumor mutational burden is another much studied biomarker associated with its own challenges and questionable concordance with tumor PD-L1 expression. In this article, we aim to discuss the challenges associated with the existing biomarkers, highlighting the need for emerging biomarkers that can help with decision making in the management of this there where several therapeutic options exist. There are emerging “me too” PD-1/PD-L1 drugs which may serve its purpose in many counties where there is limited access to current approved ICIs. What is increasingly apparent is the need to move the needle forward in the treatment of NSCLC and we will discuss the challenges associated with the current therapeutic landscape and the emerging checkpoints and the future directions that are being explored in the management of metastatic NSCLC.