Phase I/II Study of Combined BCL-xL and MEK Inhibition with Navitoclax and Trametinib in KRAS or NRAS Mutant Advanced Solid Tumors

Abstract

Purpose:

MEK inhibitors (MEKi) lack monotherapy efficacy in most RAS-mutant cancers. BCL-xL is an anti-apoptotic protein identified by a synthetic lethal shRNA screen as a key suppressor of apoptotic response to MEKi.

Patients and Methods:

We conducted a dose escalation study (NCT02079740) of the BCL-xL inhibitor navitoclax and MEKi trametinib in patients with RAS-mutant tumors with expansion cohorts for: pancreatic, gynecologic (GYN), non–small cell lung cancer (NSCLC), and other cancers harboring KRAS/NRAS mutations. Paired pretreatment and day 15 tumor biopsies and serial cell-free (cf)DNA were analyzed.

Results:

A total of 91 patients initiated treatment, with 38 in dose escalation. Fifty-eight percent had ≥3 prior therapies. A total of 15 patients (17%) had colorectal cancer, 19 (11%) pancreatic, 15 (17%) NSCLC, and 32 (35%) GYN cancers. The recommended phase II dose (RP2D) was established as trametinib 2 mg daily days 1 to 14 and navitoclax 250 mg daily days 1 to 28 of each cycle. Most common adverse events included diarrhea, thrombocytopenia, increased AST/ALT, and acneiform rash. At RP2D, 8 of 49 (16%) evaluable patients achieved partial response (PR). Disease-specific differences in efficacy were noted. In patients with GYN at the RP2D, 7 of 21 (33%) achieved a PR and median duration of response 8.2 months. No PRs occurred in patients with colorectal cancer, NSCLC, or pancreatic cancer. MAPK pathway inhibition was observed in on-treatment tumor biopsies. Reductions in KRAS/NRAS mutation levels in cfDNA correlated with clinical benefit.

Conclusions:

Navitoclax in combination with trametinib was tolerable. Durable clinical responses were observed in patients with RAS-mutant GYN cancers, warranting further evaluation in this population.

Translational Relevance.

RAS mutations are present in ∼20% of patients with cancer, yet few effective therapies exist for RAS-mutant cancers. Here, we report a dose escalation and expansion study of the BCL-xL inhibitor navitoclax and the MEK inhibitor trametinib in patients with KRAS- or NRAS-mutant solid tumors. Notably, we observed that the combination of navitoclax and trametinib demonstrated striking activity in patients with RAS-mutated gynecologic (GYN) cancers (across subtypes—cervical, endometrial, ovarian) with encouraging durability. However, responses were not observed in other solid tumor types, such as colorectal, pancreatic, and non–small cell lung cancer, suggesting a unique sensitivity of RAS-mutant GYN cancers to combined BCL-xL and MEK inhibition. Taken together, this study suggests that combined BCL-xL and MEK inhibition may be a promising therapeutic strategy in RAS-mutant GYN cancers, and follow-up studies are currently underway.

Introduction

RAS mutations are the most common oncogenic mutations, present in ∼20% of human cancer. Therefore, effective therapies for RAS-mutant cancers are critically needed. Of the three RAS isoforms, KRAS accounts for the majority (85%) of RAS mutations, followed by mutations in NRAS (11%) and HRAS (4%; ref. 1). For more than three decades since their discovery, RAS proteins have proved difficult to target directly with small molecule inhibitors. Even with recent advances in this space, currently only inhibitors targeting a specific KRAS mutation (KRAS G12C) have been FDA-approved in NSCLC (2–5). Thus, as an alternative approach to direct RAS targeting, many efforts have focused on targeting key downstream effectors of RAS. RAS has been shown to activate several important effector signaling pathways, including the MAPK pathway, the PI3K pathway, and Ral signaling pathways (1, 6). Several studies have suggested that the MAPK pathway—which drives the sequential activation of the RAF proteins (ARAF, BRAF, and CRAF), the MEK proteins (MEK1 and MEK2), and the ERK proteins (ERK1 and ERK2)—may be the most critical downstream RAS effector in tumor cells. However, inhibition of MAPK signaling alone, particularly with MEK inhibitors, typically leads to a cytostatic effect in preclinical models and fails to induce tumor regressions (1, 6, 7). Although MEK inhibitors have demonstrated efficacy in some cancers such as low-grade serous ovarian cancer (LGSOC) in both RAS-mutant and RAS-wildtype, confirmed response rates are below 30% and cancers inevitably develop resistance (8–10). In other solid tumors besides LGSOC, clinical experience with numerous MEK inhibitors has thus far failed to demonstrate meaningful clinical monotherapy activity across most RAS-mutant tumors (8, 9, 11, 12).

Previously, we conducted a synthetic lethal functional genomic screen to identify targets that cooperate with MEK inhibitors to induce cell death in KRAS-mutant cancers. One of the top candidates identified was the anti-apoptotic gene BCL2L1, which encodes the BCL-xL protein (7). Mechanistic studies demonstrated that although MEK inhibition led to marked increases in levels of the pro-apoptotic protein BIM, the majority of BIM protein remained bound and sequestered by the anti-apoptotic protein BCL-xL. However, cotreatment with the BH3 mimetic navitoclax (13), which inhibits BCL-xL and BCL-2, prevented this inhibitory interaction, resulting in high levels of free BIM protein that could drive apoptosis. Across models of KRAS-mutant colorectal cancer, pancreatic cancer, and non–small cell lung cancer (NSCLC), navitoclax in combination with a MEK inhibitor led to a dramatic increase in apoptosis relative to either agent alone, as well as profound tumor regressions in mouse xenograft models. Similarly, other studies have suggested a role for BCL-xL and/or other antiapoptotic proteins in the apoptotic response to MAPK pathway inhibition (14).

On the basis of these data, we performed a dose escalation study of the combination of navitoclax and the MEK inhibitor trametinib in KRAS- or NRAS-mutant advanced solid tumors, followed by dose expansion cohorts in specific tumor types. Paired pre- and on-treatment tumor biopsies and serial cfDNA were analyzed to characterize mechanisms of response and resistance.

Patients and Methods

Study design

This research study is a phase IB clinical trial to test the safety and efficacy of navitoclax in combination with trametinib in patients with KRAS- or NRAS-mutant advanced solid tumors (NCT02079740) under an NCI-sponsored investigational new drug application. Patients were treated at the Massachusetts General Hospital Cancer Center and the Dana-Farber Cancer Institute. Abbvie and Novartis were the suppliers of navitoclax and trametinib, respectively. The study was conducted in accordance with Guidelines for Good Clinical Practice and the ethical principles described in the Declaration of Helsinki and approved by the local institutional review board.

Part I of the study involved dose escalation of navitoclax in combination with trametinib in a 3+3 design according to three different schedules, for safety reasons, as depicted in Fig. 1A. All three schedules employed a 7-day lead-in dose of 150 mg navitoclax prior to initiation of the specific navitoclax dose, as this strategy had been found to reduce the incidence of thrombocytopenia in prior studies (15, 16). In schedule A, the 7-day lead-in of navitoclax at 150 mg was given as monotherapy, followed by administration of navitoclax and trametinib at the specified dose level on days 1 to 28 of each cycle. In schedule B, the 150 mg lead-in was given on days 1 to 7 of cycle 1 and was initiated concomitantly with trametinib, given days 1 to 28 of each cycle. In schedule C, trametinib was also initiated concomitantly with navitoclax, but trametinib was given on days 1 to 14 of each cycle, whereas navitoclax was given continuously on days 1 to 28.

Figure 1.

Study design. A, Study schema for part 1 dose escalation and CONSORT diagram. Specific dose levels, dosing schedule, and patients enrolled are shown. B, Study schema for part 2 dose expansion cohorts and CONSORT diagram. Specific tumor types and patients enrolled are shown.

Part II of the study involved dose expansion cohorts at the recommended phase II dose (RP2D) of navitoclax 250 mg daily on days 1 to 28 of each cycle (after a lead-in dose of 150 mg on days 1–7 of cycle 1 only) and trametinib 2 mg daily on days 1 to 14 of each cycle (dose level 5C). Specific expansion cohorts were enrolled for patients with KRAS- or NRAS-mutant advanced (i) pancreatic cancer, (ii) gynecologic (GYN) cancers, (iii) NSCLC, and (iv) other cancers harboring NRAS mutation. Each cohort was designed to enroll a total of 12 patients according to a Simon two-stage design with the ability to expand each cohort to a total of 25 patients if at least one partial response was observed in the first 12 patients. This design had an 11% false-positive and a 22% false-negative error rate for testing a 17% versus a 5% response rate. The probability of early stopping was 54% if the underlying response rate was truly only 5%. Cohort 3 (NSCLC) was terminated prior to reaching the enrollment goal of 12 patients due to slow accrual and lack of an efficacy signal. An originally planned expansion cohort in colorectal cancer was amended and replaced with an expansion cohort for GYN cancers based on the lack of efficacy observed in patients with colorectal cancer and the promising activity observed in patients with GYN during dose escalation.

Patients

Eligible patients were required to: (i) Be 18 years of age or older. (ii) Have Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1. (iii) Have histologically- or cytologically-confirmed diagnosis of KRAS or NRAS mutation-positive malignancy that was metastatic or unresectable and for which standard curative measures did not exist or were no longer effective. Patients needed mutations affecting codons 12, 13, 61, or 146 as determined by a Clinical Laboratory Improvement Amendments (CLIA)-approved assay to be eligible for this study. (iv) Have measurable disease, defined as at least one lesion that can be accurately measured in at least one dimension (longest diameter to be recorded for nonnodal lesions and short axis for nodal lesions) as ≥20 mm with conventional techniques or as ≥10 mm with spiral CT scan, MRI, or calipers by clinical exam. (iv) Have received at least one line of prior systemic chemotherapy and must have experienced documented radiographic progression or intolerance on this therapy.

Patients were not eligible for the study if they had (i) evidence of abnormal organ and/or bone marrow based on laboratory assessments; (ii) history of another malignancy; (iii) brain metastasis, except for treated lesions stable for at least 2 months; (iv) history of interstitial lung disease or pneumonitis; (v) evidence of left ventricular dysfunction; (vi) evidence of retinal vein occlusion or central serous retinopathy; or (vii) concurrent need for anti-coagulation or medications that affect platelet function. Additional inclusion and exclusion criteria were applied in addition to the key criteria listed above.

Efficacy assessments

Patients received study therapy until disease progression, unacceptable toxicity, death, or discontinuation for any other reason. Safety was monitored throughout the study for all patients across cohorts via physical examinations, laboratory evaluations, vital sign and weight measurements, performance status evaluations, ocular and dermatologic examinations, concomitant medication monitoring, electrocardiograms, echocardiograms, and adverse event (AE) monitoring (characterized and graded per Common Terminology Criteria for Adverse Events, v4.0). AEs were recorded using standard Medical Dictionary for Regulatory Activities coding. Dose interruptions, reductions, and discontinuations for all of the study drugs were monitored.

Antitumor efficacy was assessed by CT or MRI at baseline and then every 8 weeks until progression or death. Response determination was based on RECIST v1.1 by the Dana-Farber/Harvard Cancer Center Tumor Metrics Core. Patients were considered efficacy evaluable if they had at least one scan after initiating therapy. For the purposes of this study, clinical benefit was defined as achieving partial or complete response or stable disease.

Analysis of MAPK inhibition in paired tumor biopsies

All patients enrolled in the dose escalation stage of the study and the first 15 patients enrolled in the dose expansion stage underwent paired pretreatment (day −21 to day 0) and day 15 on-treatment tumor biopsies per protocol if deemed clinically safe and feasible. All patients provided informed written consent for these procedures. For comparison, paired pre- and on-treatment tumor biopsies were used that had previously been obtained through Institutional Review Board (IRB)-approved protocols from patients with melanoma receiving BRAF inhibitor with or without MEK inhibitor therapy at the Massachusetts General Hospital; these patients previously provided written informed consent through IRB-approved protocols.

The degree of MAPK pathway inhibition at day 15, relative to pretreatment was evaluated by qRT-PCR assessing levels of MAPK-regulated transcripts. RNA extraction was performed using RNeasy Kit (Qiagen) per the manufacturer's protocol. Reverse transcription was performed using qScript cDNA SuperMIx (Quantabio). qPCR analysis was performed using TaqMan Gene Expression Master Mix (Thermo Fisher Scientific) on the Roche Light Cycler 480. TaqMan Gene Expression Assays of DUSP6 (Hs04329643_s1) and SPRY4 (Hs01935412_s1) were purchased from Thermo Fisher Scientific. Beta-actin (Thermo Fisher Scientific, 4326315E) was used as endogenous control. The average change in both transcripts was averaged for each patient.

Analysis of circulating tumor DNA

Cell-free DNA was extracted from plasma using QIAamp Circulating Nucleic Acid Kit (Qiagen) and assessed by digital droplet PCR using probes for tumor-specific KRAS or NRAS point mutations. For droplet digital PCR (ddPCR) experiments, DNA template (up to 10 μL, with a total of 20 ng) was added to 10 μL of ddPCR Supermix for Probes (Bio-Rad) and 2 μL of the custom primer/probe mixture. This reaction mix was added to a DG8 cartridge together with 60 μL of Droplet Generation Oil for Probes (Bio-Rad) and used for droplet generation. Droplets were then transferred to a 96-well plate (Eppendorf) and then thermal cycled with the following conditions: 5 minutes at 95°C, 40 cycles of 94°C for 30 seconds, 55°C (with a few grades difference among assays) for 1 minute followed by 98°C for 10 minutes (Ramp Rate 2°C/second). Droplets were analyzed with the QX200 Droplet Reader (Bio-Rad) for fluorescent measurement of FAM and HEX probes. Gating was performed based on positive and negative controls, and mutant populations were identified. The ddPCR data were analyzed with QuantaSoft analysis software (Bio-Rad) to obtain Fractional Abundance of the mutant DNA alleles in the wild-type/normal background. The quantification of the target molecule was presented as the number of total copies (mutant plus wild-type) per sample in each reaction. Allelic fraction is calculated as follows: AF % = [N_mut/(N_mut + N_wt) × 100], where N_mut is the number of mutant alleles and N_wt is the number of wild-type alleles per reaction. ddPCR analysis of normal control DNA and no DNA template controls were always included. Probe and primer sequences are available upon request.

Data availability

Clinical trial data are available at ClinicalTrials.gov under trial number NCT02079740 and are available from the corresponding author upon request. Raw data are available upon reasonable request from the corresponding author.

Results

Patient demographics

From March 2014 to April 2022, 103 patients were screened and 91 patients enrolled and treated across two institutions during Part 1 dose escalation (n = 38) and Part 2 dose expansion (n = 53), as shown in Fig. 1. Patient demographics are shown in Table 1 and Supplementary Table S1. Median age was 60 (range 32–78) and 71% were female. Overall, 32 (35%) patients with GYN cancers, 19 (21%) with pancreatic cancer, 15 (17%) with colorectal cancer, 15 (17%) with NSCLC, and 11 (12%) with other cancers were enrolled. Seventy-three (80%) patients had tumors harboring KRAS mutations, including 25 with G12D, 22 with G12V, 10 with G12C, and 16 with other mutation. Eighteen (20%) patients had NRAS-mutant tumors. Patients had a median number of three prior lines of therapy with 53 (58%) having received three or more lines of prior therapy.

Table 1.

Baseline patient characteristics (n = 91).

Age	Median (range)		60 (32–78)
Sex	Female		65 (71.4%)
	Male		26 (28.6%)
Race	White		78 (85.7%)
	Asian		5 (5.5%)
	Black		2 (2.2%)
	Other		3 (3.3%)
	Unavailable		3 (3.3%)
Prior line of treatment
	<3 lines of treatment		38 (41.8%)
	≥3 lines of treatment		53 (58.2%)
KRAS or NRAS mutations status
	KRAS		73 (80.2%)
		G12D	25
		G12V	22
		G12C	10
		Other KRAS	16
	NRAS		18 (19.8%)
Diagnosis	GYN cancers		32 (35.2%)
		Endometrial cancer	11
		Ovarian cancer	16
		Cervical cancer	5
	Pancreas cancer		19 (20.8%)
	GI cancers		18 (19.8%)
		Colon cancer	15
		Cholangiocarcinoma	2
		Gastric cancer	1
		Esophageal cancer	1
	Lung cancer		15 (16.5%)
	Others		7 (4.4%)
		Melanoma	6
		Thyroid cancer	1

Dose escalation

Dose escalation to determine the RP2D explored three dosing schedules in a 3+3 design (Fig. 1A). All three schedules employed a 7-day lead-in dose of 150 mg navitoclax prior to initiation of the specific navitoclax dose, as this strategy had been found to reduce the incidence of thrombocytopenia in prior studies (15, 16). In schedule A, the 7-day lead-in of navitoclax at 150 mg was given as monotherapy, followed by administration of navitoclax and trametinib at the specified dose level on days 1 to 28 of each cycle. In schedule B, the 150 mg lead-in was given on days 1 to 7 of cycle 1 and was initiated concomitantly with trametinib, given days 1 to 28 of each cycle. In schedule C, trametinib was also initiated concomitantly with navitoclax, but trametinib was given on days 1 to 14 of each cycle, whereas navitoclax was given continuously on days 1 to 28.

After no dose-limiting toxicities (DLT) were observed through dose level 3A, evaluation of schedule B, which enabled initiation of trametinib simultaneously with navitoclax, was undertaken. Two DLTs were observed in dose level 3B, which included one patient with grade 3 increases in AST and ALT and one patient with grade 4 hypokalemia. Although no DLTs were observed prior to dose level 3B, evidence of toxicity (typically rash or diarrhea) occurring after the first month of dosing, was observed in several patients and was considered by the investigators to be attributable to continuous daily dosing of trametinib. Thus, evaluation of schedule C, in which trametinib is administered on days 1 to 14 only of each cycle, was initiated. Two patients experienced DLTs at dose level 6C, 1 with grade 3 hyperbilirubinemia and 1 with grade 3 enterocolitis, and the RP2D was established as navitoclax 250 mg daily on days 1 to 28 of each cycle (after a lead-in dose of 150 mg on days 1–7 of cycle 1 only) and trametinib 2 mg daily on days 1 to 14 of each cycle.

Adverse events

The most common treatment-emergent AEs (TEAE), as shown in Table 2, include diarrhea, thrombocytopenia, increase in AST and ALT, acneiform rash, nausea, vomiting, fatigue, decreased neutrophil count, and anemia. Notably, while decreases in platelet count were noted in 71% of patients, only 2 patients (2%) experienced grade 3 or greater thrombocytopenia. The most common grade 3 or greater TEAEs (Supplementary Table S2) were neutrophil decrease, anemia, hypokalemia, and diarrhea. Of the 91 patients enrolled in the study, 48 experienced dose interruptions, 27 underwent dose reductions, and 9 discontinued treatment due to toxicity. Of 53 patients treated at the RP2D, 26 experienced dose interruptions, 14 underwent dose reductions, and 8 discontinued treatment due to toxicity. Grade 5 events included stroke and multisystem organ failure due to disease progression deemed not related to study treatment.

Table 2.

TEAE ≥10% of all patients (N = 85).

	All grade	Grade 1	Grade 2	Grade 3	Grade 4
Diarrhea	62 (72.9%)	41 (48.2%)	16 (18.8%)	5 (5.9%)	0 (0.0%)
Platelet count decreased	60 (70.6%)	39 (45.9%)	19 (22.4%)	2 (2.4%)	0 (0.0%)
AST increased	58 (68.2%)	46 (54.1%)	8 (9.4%)	4 (4.7%)	0 (0.0%)
Rash acneiform	51 (60.0%)	42 (49.4%)	9 (10.6%)	0 (0.0%)	0 (0.0%)
ALT increased	46 (54.1%)	36 (42.4%)	6 (7.1%)	4 (4.7%)	0 (0.0%)
Vomiting	42 (49.4%)	34 (40.0%)	5 (5.9%)	3 (3.5%)	0 (0.0%)
Nausea	41 (48.2%)	33 (38.8%)	6 (7.1%)	2 (2.4%)	0 (0.0%)
Fatigue	38 (44.7%)	25 (29.4%)	13 (15.3%)	0 (0.0%)	0 (0.0%)
Neutrophil decreased	37 (43.5%)	14 (16.5%)	17 (20.0%)	6 (7.1%)	0 (0.0%)
Anemia	34 (40.0%)	10 (11.8%)	18 (21.2%)	6 (7.1%)	0 (0.0%)
Hypokalemia	28 (32.9%)	17 (20.0%)	4 (4.7%)	6 (7.1%)	1 (1.2%)
Hypocalcemia	27 (31.8%)	20 (23.5%)	5 (5.9%)	2 (2.4%)	0 (0.0%)
Hypoalbuminemia	27 (31.8%)	12 (14.1%)	13 (15.3%)	2 (2.4%)	0 (0.0%)
Alkaline phosphatase increased	26 (30.6%)	21 (24.7%)	4 (4.7%)	1 (1.2%)	0 (0.0%)
Anorexia	25 (29.4%)	19 (22.4%)	6 (7.1%)	0 (0.0%)	0 (0.0%)
Edema limbs	21 (24.7%)	17 (20.0%)	4 (4.7%)	0 (0.0%)	0 (0.0%)
Hypomagnesemia	19 (22.4%)	15 (17.7%)	1 (1.2%)	2 (2.4%)	1 (1.2%)
Hyponatremia	19 (22.4%)	17 (20.0%)	0 (0.0%)	2 (2.4%)	0 (0.0%)
Constipation	18 (21.2%)	14 (16.5%)	4 (4.7%)	0 (0.0%)	0 (0.0%)
Dehydration	18 (21.2%)	8 (9.4%)	8 (9.4%)	2 (2.4%)	0 (0.0%)
Rash maculo-papular	18 (21.2%)	15 (17.7%)	2 (2.4%)	1 (1.2%)	0 (0.0%)
Abdominal pain	16 (18.8%)	11 (13.0%)	3 (3.5%)	2 (2.4%)	0 (0.0%)
Hyperglycemia	16 (18.8%)	15 (17.7%)	0 (0.0%)	1 (1.2%)	0 (0.0%)
Fever	16 (18.8%)	10 (11.8%)	6 (7.1%)	0 (0.0%)	0 (0.0%)
Blood bilirubin increased	14 (16.5%)	8 (9.4%)	2 (2.4%)	4 (4.7%)	0 (0.0%)
Flatulence	14 (16.5%)	14 (16.5%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
Dizziness	14 (16.5%)	12 (14.1%)	1 (1.2%)	1 (1.2%)	0 (0.0%)
Pruritus	13 (15.3%)	13 (15.3%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
INR increased	12 (14.1%)	10 (11.8%)	2 (2.4%)	0 (0.0%)	0 (0.0%)
Bloating	12 (14.1%)	12 (14.1%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
Hypophosphatemia	12 (14.1%)	6 (7.1%)	4 (4.7%)	2 (2.4%)	0 (0.0%)
Myalgia	12 (14.1%)	11 (13.0%)	0 (0.0%)	1 (1.2%)	0 (0.0%)
Thromboembolic event	11 (13.0%)	2 (2.4%)	4 (4.7%)	5 (5.9%)	0 (0.0%)
Mucositis oral	10 (11.8%)	3 (3.5%)	5 (5.9%)	2 (2.4%)	0 (0.0%)
Hypertension	10 (11.8%)	2 (2.4%)	6 (7.1%)	2 (2.4%)	0 (0.0%)
Dry skin	10 (11.8%)	10 (11.8%)	0 (0.0%)	0 (0.0%)	0 (0.0%)
Dyspnea	10 (11.8%)	8 (9.4%)	2 (2.4%)	0 (0.0%)	0 (0.0%)
Activated PTT prolonged	9 (10.6%)	9 (10.6%)	0 (0.0%)	0 (0.0%)	0 (0.0%)

Abbreviation: INR, international normalized ratio.

Clinical efficacy

No objective tumor responses were observed prior to dose-level 5C, the RP2D. Of 75 patients treated who were efficacy evaluable, 8 (11%) achieved a partial response (PR), and 46 (61%) achieved clinical benefit [defined as best response of stable disease (SD) or PR by RECIST; Fig. 2A]. At RP2D, 8 (16%) had a PR and 29 (59%) achieved clinical benefit among 49 evaluable patients (Fig. 2B). Interestingly, striking differences in efficacy between tumor types were observed (Fig. 2C–F). For patients with GYN at the RP2D, 7 of 24 (29%) total and 7 of 21 (33%) patients who were efficacy evaluable achieved a confirmed PR, whereas no PRs were observed in patients with colorectal cancer (n = 13), pancreatic cancer (n = 16), or NSCLC (n = 13). One patient with an NRAS-mutant melanoma also achieved a PR at the RP2D. In patients with GYN, PRs were observed in ovarian (n = 3, of which only one was low grade serous), endometrial (n = 2), Mullerian (n = 1), and cervical cancers (n = 1).

Figure 2.

Clinical efficacy. A, Best tumor response by RECIST in all patients at all dose levels, shown by tumor type. B, Best tumor response by RECIST in patients treated at the RP2D, shown by tumor type. C–F, Best tumor response by RECIST in patients treated at all dose levels with (C) colorectal cancer, (D) pancreatic ductal adenocarcinoma (PDAC), (E) NSCLC, and (F) GYN cancers. Patients treated at the RP2D are indicated with a red diamond.

Median duration of response (DOR) for patients with GYN was 8.17 months, with 4 of 7 patients achieving a PR remaining on therapy for more than 1 year (Fig. 3A). Two patients with GYN experienced PRs lasting more than 2 years, and 1 GYN patient with SD also remained on therapy for more than 2 years. Median progression-free survival (PFS) for patients with GYN was 4.8 months (Fig. 3B), which was significantly greater than the median PFS for patients with all other tumor types (1.87 months, P = 0.0025). Median overall survival (OS) was also greater for patients with GYN compared with all other tumor types (18.13 months vs. 6.57 months, respectively; P = 0.022; Fig. 3C). The patient with NRAS-mutant melanoma remains on treatment with an ongoing PR at 14 months.

Figure 3.

Time on treatment and PFS and OS. A, Swim plot of patients showing time on treatment by tumor type. Time of first response is indicated by a black triangle and patients still ongoing on treatment at the time of the data cut are indicated with an arrow. B and C, Kaplan–Meyer curves for (B) PFS and (C) OS are shown for patients with GYN versus non-GYN tumor types with associated P values.

Serial cfDNA analysis

Plasma for serial cfDNA was collected at baseline and at monthly intervals throughout therapy for 53 patients enrolled during the dose expansion portion of the study and analyzed by mutant-specific ddPCR, and the change in levels of tumor-specific mutations in cfDNA was assessed, as we have done previously (17). Individual KRAS or NRAS mutations present in each patient's tumor were detectable in 51 patients, and the decrease in KRAS or NRAS mutation level in cfDNA after 4 weeks of treatment was significantly greater for patients achieving clinical benefit (PR or SD) versus those with progressive disease (PD) as their best response (P = 0.0045; Fig. 4A). Of 21 patients whose KRAS or NRAS mutation levels decreased by at least 30% from baseline (utilizing a threshold defined in our prior study; ref. 17) after 4 weeks of treatment, 16 (76%) achieved clinical benefit. Only 2 of 21 patients with PD (10%) exhibited a decrease of 30% or more. Patients who exhibited a 30% or greater decrease in KRAS or NRAS mutation levels in cfDNA after 4 weeks of treatment had significantly greater median PFS (4.8 months vs. 1.81 months, P = 0.0014) and OS (18.13 months vs. 6.63 months, P = 0.013) compared with those who did not (Fig. 4B).

Figure 4.

Serial ctDNA analysis and MAPK pathway inhibition in paired tumor biopsies. A, Percent change in KRAS or NRAS mutant allele-fraction in ctDNA after 4 weeks of treatment, relative to pre-treatment levels, in patients achieving clinical benefit (defined as PR or SD) versus PD on first restaging scan. B, PFS and OS for patients who achieved a 30% or greater decrease in ctDNA levels by 4 weeks, relative to pretreatment levels, compared with patients who did not. C and D, Examples of patients with (C) ovarian cancer and (D) cervical cancer who achieved durable partial responses. Serial monitoring of tumor-specific NRAS or KRAS mutation allele fraction in ctDNA throughout treatment is shown, along with CT scans from baseline, response nadir, and progression with lesions indicated. E, The degree of MAPK pathway suppression was assessed by measurement of MAPK-regulated transcript levels in each patient's day 15 tumor biopsy relative to the paired pretreatment biopsy. Patients from this study were compared with similar paired pre- and on-treatment tumor biopsies obtained from BRAF^V600 mutant melanoma treated with BRAF inhibitor therapy with or without MEK inhibitor. F, The degree of MAPK pathway suppression achieved by day 15 of treatment was compared between patients achieving PR or SD versus PD on first restating scan, with individual tumor types indicated.

Serial cfDNA analysis of two exceptional responders, including an NRAS Q61R patient with ovarian cancer and a KRAS G12D patient with cervical cancer, along with CT images of target and nontarget lesions at baseline, response nadir, and eventual disease progression are shown (Fig. 4C and D). In both cases, mutant KRAS or NRAS levels in cfDNA decreased rapidly after initiation of treatment and remained suppressed until disease progression.

Analysis of paired tumor biopsies

Paired baseline and day 15 on-treatment biopsies were attempted (if clinically feasible, per protocol) on all patients during the Part 1 dose escalation and on the first 8 patients of the Part 2 dose expansion. Overall, both biopsies were successfully obtained for 23 patients. To assess the degree of MAPK inhibition achieved on treatment, RNA was isolated from each biopsy, and the levels of MAPK-regulated transcripts DUSP6, SPRY4, and ETV5 were measured at day 15 versus pretreatment by qRT-PCR. Overall, RNA quantities sufficient for qRT-PCR were obtained from both the pretreatment and day 15 biopsies in 23 patients. Most patients achieved a decrease in MAPK-regulated transcript levels after 15 days of treatment (Fig. 4E). However, the degree of MAPK pathway suppression was significantly less than what was observed for patients with BRAFV600-mutant melanoma treated with BRAF inhibitor therapy, suggesting that the degree of MAPK pathway achieved by this regimen may be suboptimal.

Notably, the degree of MAPK suppression was significantly greater in patients who achieved clinical benefit (PR or SD) compared with patients whose best response was PD (Fig. 4F). Although small sample size limited comparisons of pathway inhibition in response to therapy across tumor types, these data suggest that the degree of MAPK pathway suppression achieved may be an important factor in driving therapeutic efficacy.

Discussion

Although the MAPK pathway is thought to be the most critical downstream RAS effector pathway, to date MEK inhibitors have failed to exhibit appreciable single agent activity in most RAS-mutant cancers. Consistent with this finding, MEK inhibitors have primarily cytostatic effects in most preclinical models of RAS-mutant cancer, and MEK inhibition alone is thought to be insufficient to drive cell death and tumor regressions. Here, based on preclinical data suggesting that inhibition of the anti-apoptotic protein BCL-xL may cooperate with MEK inhibition to induce tumor cell death in RAS mutant cancer models, we performed a phase I/II study of the BCL-xL inhibitor navitoclax with the MEK inhibitor trametinib in KRAS and NRAS mutant patients with cancer.

Interestingly, although this combination did not produce responses in NSCLC, colorectal cancer, and pancreatic cancer, in patients with GYN a 33% confirmed response rate was observed at the RP2D with encouraging durability (median DOR of over 8 months). Importantly, efficacy was seen in ovarian, endometrial, Mullerian, and cervical cancer, suggesting potential activity of this combination across GYN tumor types. Although responses to MEK inhibitors alone have been observed previously in LGSOC (8–10), it is important to note that only one of the seven responders was a patient with LGSOC. Outside of LGSOC, there is limited experience with MEK inhibitors as monotherapy in GYN cancers. A phase II study of selumetinib in recurrent endometrial cancer reported very limited clinical activity, with an objective response rate of 6% (3 of 52 patients) and median PFS of 2.3 months (18). The small number of patients and multiple GYN tumor types and histologies enrolled to this proof-of-concept trial limit a more comprehensive understanding of the comparative efficacy of MEK inhibition to standard-of-care therapy in these tumors. Nonetheless, these data are promising that combination MEK and BCL-xL inhibition has clinical potential across multiple GYN tumor types. Additional studies are needed to examine this activity in disease and histology-specific cohorts. Within LGSOC, where MEK inhibitor monotherapy activity has been demonstrated (8–10), important questions include whether the addition of BCL-xL inhibition substantially adds to this activity or whether a MEK inhibitor/BCL-xL inhibitor combination might be active following progression on MEK inhibitor alone.

Intriguingly, in high-grade serous ovarian cancers (HGSOC), we have also found that HGSOC patient-derived xenograft models that show strong ERK-pathway activation respond to MEK inhibition with upregulation of BIM, a pro-apoptotic target of BCL-xL, and that dual inhibition with navitoclax enhances the efficacy of MEK inhibitors in most models (19), only one of which contained a KRAS mutation; these findings suggest that combined inhibition of MEK and BCL-xL with a combination such as trametinib/navitoclax might have potential in RAS-mutated and nonmutated contexts. Furthermore, whether increased BIM expression at baseline or in response to MEK inhibition might underlie enhanced sensitivity to combined BCL-xL and MEK inhibition in GYN cancers warrants further study.

Analysis of paired tumor biopsies performed before and after 15 days of treatment revealed that inhibition of MAPK signaling observed was less robust than that observed in BRAF^V600 mutant melanoma patients treated with BRAF inhibitor combinations (Fig. 5A). Because high-level suppression of MAPK signaling has previously been shown to be required for clinical antitumor efficacy (20), the lack of consistent and robust inhibition of MAPK signaling may be one reason that efficacy was not observed more broadly across patients. Indeed, significantly greater levels of MAPK suppression were observed in patients who achieved clinical benefit (PR or SD) compared with those with PD. However, one potential limitation of this analysis is that due to the limited amount of biopsy tissue, only MAPK-regulated transcripts could be analyzed and parallel analysis of changes in protein markers could not be performed. Several studies have suggested that adaptive feedback signaling can lead to reactivation of the MAPK pathway following treatment with MEK inhibitors, and that this adaptive feedback reactivation may be more pronounced in some tumor types, such as colorectal cancer (21–24). This hypothesis could represent one factor contributing to the differential efficacy observed between tumor types on this study. Although the biopsy sample size was too small to allow for careful comparison of MAPK inhibition across tumor types, the data do suggest a potential trend toward better MAPK suppression in GYN patients compared with other tumor types, but the data are not conclusive. This hypothesis also suggests that combinations of BCL-xL inhibitors with MAPK pathway inhibitors (such as ERK inhibitors, or MEK inhibitors that also prevent RAF-mediated MEK activation) that are less vulnerable to adaptive feedback reactivation and thus more able to sustain MAPK suppression might have the potential to increase efficacy and warrant further exploration. (25)

Prior studies with navitoclax, particularly those conducted in patients with hematologic malignancies, experienced issues with thrombocytopenia as a result of a key role for BCL-xL in platelet survival (26, 27). However, in this study of solid tumor patients, thrombocytopenia was not a major issue, with only 2% of patients experiencing grade 3 or greater thrombocytopenia. One explanation for this could be that solid tumor patients in general may start with higher platelet counts and may have less bone marrow defects as compared with patients with hematologic malignancies. Another factor that may have lessened the frequency and impact of thrombocytopenia is the 7-day lead-in dosing of navitoclax, which has been proposed to stimulate marrow production and mitigate acute decreases in peripheral platelet counts. Although further evaluation is necessary, these data suggest that BCL-xL targeting in solid tumor patients may be feasible, and future studies with these agents may not need to exclude anticoagulation as was done in this study, given the low rate of Grade 3 or higher thrombocytopenia observed.

Limitations of this study include the small sample size of certain individual tumor types. In particular, while promising efficacy was observed in three different GYN cancer subtypes (ovarian, endometrial, and cervical), the limited number of patients with each specific tumor subtype preclude a thorough assessment of the activity in each group and thus warrants further exploration. In addition, although our study explored different schedules of BCL-xL and MEK inhibitor administration, a more comprehensive optimization of dose schedule would be warranted in future studies.

Overall, this study demonstrates that combined BCL-xL and MEK inhibition is feasible in advanced solid tumor patients with promising efficacy observed in patients with KRAS- or NRAS-mutant GYN cancers. Assessment of the degree of MAPK suppression achieved in paired tumor biopsies suggest that combinations of BCL-xL inhibitors with MAPK pathway inhibitors capable of achieving a greater degree of MAPK suppression could be one strategy to improve efficacy, and thus combinations with next-generation MEK inhibitors, ERK inhibitors, or even newer classes of inhibitors such as KRAS inhibitors could be warranted. These data also support a focused clinical assessment of combined BCL-xL/MAPK inhibition in patients with GYN cancer given the promising initial efficacy observed. On the basis of these data, a clinical trial of the BCL-xL inhibitor pelcitoclax and the MEK inhibitor cobimetinib in recurrent patients with ovarian cancer is currently underway (NCT05691504).

Supplementary Material

Supplementary Material 1

Supplementary Table S1, Supplementary Table S2, Supplementary Figure S1

This article is featured in Highlights of This Issue, p. 1703

Disclaimer

The Editor-in-Chief of Clinical Cancer Research is an author on this article. In keeping with AACR editorial policy, a senior member of the Clinical Cancer Research editorial team managed the consideration process for this submission and independently rendered the final decision concerning acceptability.

Authors' Disclosures

R.B. Corcoran reports personal fees from AbbVie, Amgen, Astex, Daiichi Sankyo, Elicio, FOG Pharma, Guardant Health, Mirati, Natera, Navire, Qiagen, Roche, Syndax, Tango Therapeutics, Taiho, and Theonis; grants and personal fees from Pfizer, Asana Biosciences, and AstraZeneca; other support from Avidity Biosciences and Erasca; personal fees and other support from C4 Therapeutics, Cogent Biosciences, Kinnate, Nested Therapeutics, nRichDx, Remix Therapeutics, Revolution Medicines, Interline Therapeutics, Alterome Therapeutics, and Sidewinder Therapeutics; and grants from Novartis outside the submitted work. K.T. Do reports other support from Moderna Therapeutics outside the submitted work. J.M. Cleary reports grants from Merus, Roche, Servier, BMS, Merck, and Tesaro; nonfinancial support from Astrazeneca, Bayer, Esperas Pharma, Arcus, and Pyxis Oncology; and personal fees from Incyte and Blueprint Medicines outside the submitted work. A.R. Parikh reports equity in C2i Genomics, XGenomes, Cadex, Vionix, and Parithera; is an advisor/consultant for Eli Lilly, Mirati, Pfizer, Inivata, Biofidelity, Checkmate Pharmaceuticals, FMI, Guardant, AbbVie, Bayer, Delcath, Taiho, CVS, Value Analytics Lab, Seagen, Saga, AZ, Scare Inc, Illumina, Taiho, Hookipa, Kahar Medical, Xilio Therapeutics, Sirtex, Takeda, and Science For America; receives fees from UpToDate; receives travel fees from Karkinos Healthcare; has been on the DSMC for a Roche study; has been on the Steering Committee for Exilixis; and has received research funding to the Institution from PureTech, PMV Pharmaceuticals, Plexxicon, Takeda, BMS, Mirati, Novartis, Erasca, Genentech, Daiichi Sankyo, and Syndax. C.D. Weekes reports grants from Novartis, Elicio, and Dicephera outside the submitted work. J. Veneris reports other support from GSK outside the submitted work. L.G. Ahronian reports other support from Tango Therapeutics outside the submitted work. G. Mauri reports other support from COR2ED outside the submitted work. E.E. Van Seventer reports other support from Blueprint Medicines outside the submitted work. R.T. Penson reports grants from MGH during the conduct of the study, as well as personal fees from AstraZeneca, Genentech/Roche, Sutro Biopharma, Immunogen, GlaxoSmithKline, Novocure, Merck, Mersana, and Vascular Biogenics outside the submitted work. D. Juric reports grants and personal fees from Novartis, Genentech, Syros, Eisai, Pfizer, and AstraZeneca; personal fees from Vibliome, PIC Therapeutics, Mapkure, and Relay Therapeutics; and grants from Amgen, InventisBio, Arvinas, Takeda, Blueprint, Ribon Therapeutics, and Infinity outside the submitted work. K.T. Flaherty reports personal fees and other support from Clovis Oncology, Strata Oncology, Checkmate Pharmaceuticals, Kinnate Biopharma, Scorpion Therapeutics, PIC Therapeutics, Apricity, Fog Pharma, Tvardi, xCures, Monopteros, Vibliome, ALX Oncology, Karkinos, Soley Therapeutics, Alterome, IntrECate, PreDICTA, and Transcode Therapeutics; grants and personal fees from Novartis; personal fees from Genentech; and other support from Takeda during the conduct of the study. R.J. Sullivan reports grants and personal fees from Merck, as well as personal fees from Novartis, Pfizer, BMS, and Replimune outside the submitted work. R.S. Heist reports other support from AbbVie, Claim, AstraZeneca, Daichii Sankyo, Merck, Lilly, Novartis, Regeneron, and Sanofi during the conduct of the study, as well as grant funding to institution from Agios, Daichii Sankyo, Mythic, Novartis, Lilly, AbbVie, Mirati, Turning Point, and Erasca. U.A. Matulonis reports personal fees from Tango, NextCure, Eisai, Symphogen, Alkermes, Allarity, Immunogen, GSK, and ProfoundBio outside the submitted work. J.F. Liu reports personal fees from Bristol Myers Squibb, AstraZeneca, Eisai, Genentech/Roche, GlaxoSmithKline, Regeneron Therapeutics, Daiichi Sankyo, and Zentalis, as well as other support from 2X Oncology, Aravive, Arch Oncology, AstraZeneca, Bristol-Myers Squibb, Clovis Oncology, CytomX Therapeutics, GlaxoSmithKline, Impact Therapeutics, Regeneron, Surface Oncology, Vigeo Therapeutics, and Zentalis Pharmaceuticals outside the submitted work. G.I. Shapiro reports grants and personal fees from Merck KGaA/EMD Serono; grants from Tango Therapeutics, Bristol Myers Squibb, Pfizer, and Eli Lilly; and personal fees from Bicycle Therapeutics, Boehringer Ingelheim, ImmunoMet, Concarlo Holdings, Syros, Zentalis, Blueprint Medicines, Kymera Therapeutics, Janssen, and Xinthera outside the submitted work. In addition, G.I. Shapiro has a patent (dosage regimen for sapacitabine and seliciclib) issued to self and Cyclacel Therapeutics, as well as a patent (compositions and methods for predicting response and resistance to CDK4/6 inhibition) issued to self and Liam Cornell. No disclosures were reported by the other authors.

Authors' Contributions

R.B. Corcoran: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, validation, investigation, methodology, writing–original draft. K.T. Do: Investigation, writing–review and editing. J.E. Kim: Data curation, Formal analysis, investigation, writing–original draft, writing–review and editing. J.M. Cleary: Investigation, writing–review and editing. A.R. Parikh: Investigation, writing–review and editing. O.O. Yeku: Investigation, writing–review and editing. N. Xiong: Data curation, formal analysis, investigation, writing–review and editing. C.D. Weekes: Investigation, writing–review and editing. J. Veneris: Formal analysis, investigation, writing–review and editing. L.G. Ahronian: Data curation, formal analysis, investigation, writing–review and editing. G. Mauri: Data curation, formal analysis, investigation, writing–review and editing. J. Tian: Data curation, formal analysis, investigation, writing–review and editing. B.L. Norden: Formal analysis, investigation, writing–review and editing. A.G. Michel: Formal analysis, investigation, writing–review and editing. E.E. Van Seventer: Data curation, formal analysis, investigation, writing–review and editing. G. Siravegna: Data curation, formal analysis, investigation, writing–review and editing. K. Camphausen: Data curation, formal analysis, investigation, writing–review and editing. G. Chi: Data curation, formal analysis, investigation, writing–review and editing. I.J. Fetter: Formal analysis, investigation, writing–review and editing. J.S. Brugge: Formal analysis, supervision, investigation, writing–review and editing. H. Chen: Formal analysis, supervision, investigation, writing–review and editing. N. Takebe: Supervision, investigation, writing–review and editing. R.T. Penson: Supervision, investigation, writing–review and editing. D. Juric: Supervision, investigation, writing–review and editing. K.T. Flaherty: Investigation, writing–review and editing. R.J. Sullivan: Investigation, writing–review and editing. J.W. Clark: Investigation, writing–review and editing. R.S. Heist: Data curation, formal analysis, investigation, writing–review and editing. U.A. Matulonis: Data curation, formal analysis, investigation, writing–review and editing. J.F. Liu: Data curation, formal analysis, investigation, writing–review and editing. G.I. Shapiro: Data curation, formal analysis, investigation, writing–review and editing.