Genome-wide loss of heterozygosity predicts aggressive, treatment-refractory behavior in pituitary neuroendocrine tumors

Pituitary neuroendocrine tumors (PitNETs) exhibiting aggressive, treatment-refractory behavior are the rare subset that progress after surgery, conventional medical therapies, and an initial course of radiation and are characterized by unrelenting growth and/or metastatic dissemination. Two groups of patients with PitNETs were sequenced: a prospective group of patients (n = 66) who consented to sequencing prior to surgery and a retrospective group (n = 26) comprised of aggressive/higher risk PitNETs. A higher mutational burden and fraction of loss of heterozygosity (LOH) was found in the aggressive, treatment-refractory PitNETs compared to the benign tumors (p = 1.3 × 10-10 and p = 8.5 × 10-9, respectively). Within the corticotroph lineage, a characteristic pattern of recurrent chromosomal LOH in 12 specific chromosomes was associated with treatment-refractoriness (occurring in 11 of 14 treatment-refractory versus 1 of 14 benign corticotroph PitNETs, p = 1.7 × 10-4). Across the cohort, a higher fraction of LOH was identified in tumors with TP53 mutations (p = 3.3 × 10-8). A machine learning approach identified loss of heterozygosity as the most predictive variable for aggressive, treatment-refractory behavior, outperforming the most common gene-level alteration, TP53, with an accuracy of 0.88 (95% CI: 0.70-0.96). Aggressive, treatment-refractory PitNETs are characterized by significant aneuploidy due to widespread chromosomal LOH, most prominently in the corticotroph tumors. This LOH predicts treatment-refractoriness with high accuracy and represents a novel biomarker for this poorly defined PitNET category.

Developing Novel Genomic Risk Stratification Models in Soft Tissue and Uterine Leiomyosarcoma

PURPOSE

Leiomyosarcomas (LMS) are clinically and molecularly heterogeneous tumors. Despite recent large-scale genomic studies, current LMS risk stratification is not informed by molecular alterations. We propose a clinically applicable genomic risk stratification model.

EXPERIMENTAL DESIGN

We performed comprehensive genomic profiling in a cohort of 195 soft tissue LMS (STLMS), 151 primary at presentation, and a control group of 238 uterine LMS (ULMS), 177 primary at presentation, with at least 1-year follow-up.

RESULTS

In STLMS, French Federation of Cancer Centers (FNCLCC) grade but not tumor size predicted progression-free survival (PFS) or disease-specific survival (DSS). In contrast, in ULMS, tumor size, mitotic rate, and necrosis were associated with inferior PFS and DSS. In STLMS, a 3-tier genomic risk stratification performed well for DSS: high risk: co-occurrence of RB1 mutation and chr12q deletion (del12q)/ATRX mutation; intermediate risk: presence of RB1 mutation, ATRX mutation, or del12q; low risk: lack of any of these three alterations. The ability of RB1 and ATRX alterations to stratify STLMS was validated in an external AACR GENIE cohort. In ULMS, a 3-tier genomic risk stratification was significant for both PFS and DSS: high risk: concurrent TP53 mutation and chr20q amplification/ATRX mutations; intermediate risk: presence of TP53 mutation, ATRX mutation, or amp20q; low risk: lack of any of these three alterations. Longitudinal sequencing showed that most molecular alterations were early clonal events that persisted during disease progression.

CONCLUSIONS

Compared with traditional clinicopathologic models, genomic risk stratification demonstrates superior prediction of clinical outcome in STLMS and is comparable in ULMS.

Nivolumab for mismatch-repair-deficient or hypermutated gynecologic cancers: a phase 2 trial with biomarker analyses

Programmed death-1 (PD-1) inhibitors are approved for therapy of gynecologic cancers with DNA mismatch repair deficiency (dMMR), although predictors of response remain elusive. We conducted a single-arm phase 2 study of nivolumab in 35 patients with dMMR uterine or ovarian cancers. Co-primary endpoints included objective response rate (ORR) and progression-free survival at 24 weeks (PFS24). Secondary endpoints included overall survival (OS), disease control rate (DCR), duration of response (DOR) and safety. Exploratory endpoints included biomarkers and molecular correlates of response. The ORR was 58.8% (97.5% confidence interval (CI): 40.7-100%), and the PFS24 rate was 64.7% (97.5% one-sided CI: 46.5-100%), meeting the pre-specified endpoints. The DCR was 73.5% (95% CI: 55.6-87.1%). At the median follow-up of 42.1 months (range, 8.9-59.8 months), median OS was not reached. One-year OS rate was 79% (95% CI: 60.9-89.4%). Thirty-two patients (91%) had a treatment-related adverse event (TRAE), including arthralgia (n = 10, 29%), fatigue (n = 10, 29%), pain (n = 10, 29%) and pruritis (n = 10, 29%); most were grade 1 or grade 2. Ten patients (29%) reported a grade 3 or grade 4 TRAE; no grade 5 events occurred. Exploratory analyses show that the presence of dysfunctional (CD8+PD-1+) or terminally dysfunctional (CD8+PD-1+TOX+) T cells and their interaction with programmed death ligand-1 (PD-L1)+ cells were independently associated with PFS24. PFS24 was associated with presence of MEGF8 or SETD1B somatic mutations. This trial met its co-primary endpoints (ORR and PFS24) early, and our findings highlight several genetic and tumor microenvironment parameters associated with response to PD-1 blockade in dMMR cancers, generating rationale for their validation in larger cohorts.ClinicalTrials.gov identifier: NCT03241745 .

A Phase I Study of KIN-3248, an Irreversible Small-molecule Pan-FGFR Inhibitor, in Patients with Advanced FGFR2/3-driven Solid Tumors

PURPOSE

Despite efficacy of approved FGFR inhibitors, emergence of polyclonal secondary mutations in the FGFR kinase domain leads to acquired resistance. KIN-3248 is a selective, irreversible, orally bioavailable, small-molecule inhibitor of FGFR1-4 that blocks both primary oncogenic and secondary kinase domain resistance FGFR alterations.

EXPERIMENTAL DESIGN

A first-in-human, phase I study of KIN-3248 was conducted in patients with advanced solid tumors harboring FGFR2 and/or FGFR3 gene alterations (NCT05242822). The primary objective was determination of MTD/recommended phase II dose (RP2D). Secondary and exploratory objectives included antitumor activity, pharmacokinetics, pharmacodynamics, and molecular response by circulating tumor DNA (ctDNA) clearance.

RESULTS

Fifty-four patients received doses ranging from 5 to 50 mg orally daily across six cohorts. Intrahepatic cholangiocarcinoma (48.1%), gastric (9.3%), and urothelial (7.4%) were the most common tumors. Tumors harbored FGFR2 (68.5%) or FGFR3 (31.5%) alterations-23 (42.6%) received prior FGFR inhibitors. One dose-limiting toxicity (hypersensitivity) occurred in cohort 1 (5 mg). Treatment-related, adverse events included hyperphosphatemia, diarrhea, and stomatitis. The MTD/RP2D was not established. Exposure was dose proportional and concordant with hyperphosphatemia. Five partial responses were observed; 4 in FGFR inhibitor naïve and 1 in FGFR pretreated patients. Pretreatment ctDNA profiling confirmed FGFR2/3 alterations in 63.3% of cases and clearance at cycle 2 associated with radiographic response.

CONCLUSION

The trial was terminated early for commercial considerations; therefore, RP2D was not established. Preliminary clinical data suggest that KIN-3248 is a safe, oral FGFR1-4 inhibitor with favorable pharmacokinetic parameters, though further dose escalation was required to nominate the MTD/RP2D.

SIGNIFICANCE

KIN-3248 was a rationally designed, next generation selective FGFR inhibitor, that was effective in interfering with both FGFR wild-type and mutant signaling. Clinical data indicate that KIN-3248 is safe with a signal of antitumor activity. Translational science support the mechanism of action in that serum phosphate was proportional with exposure, paired biopsies suggested phospho-ERK inhibition (a downstream target of FGFR2/3), and ctDNA clearance may act as a RECIST response surrogate.

Discovery and Clinical Proof-of-Concept of RLY-2608, a First-in-Class Mutant-Selective Allosteric PI3Kα Inhibitor That Decouples Antitumor Activity from Hyperinsulinemia

PIK3CA (PI3Kα) is a lipid kinase commonly mutated in cancer, including ∼40% of hormone receptor-positive breast cancer. The most frequently observed mutants occur in the kinase and helical domains. Orthosteric PI3Kα inhibitors suffer from poor selectivity leading to undesirable side effects, most prominently hyperglycemia due to inhibition of wild-type (WT) PI3Kα. Here, we used molecular dynamics simulations and cryo-electron microscopy to identify an allosteric network that provides an explanation for how mutations favor PI3Kα activation. A DNA-encoded library screen leveraging electron microscopy-optimized constructs, differential enrichment, and an orthosteric-blocking compound led to the identification of RLY-2608, a first-in-class allosteric mutant-selective inhibitor of PI3Kα. RLY-2608 inhibited tumor growth in PIK3CA-mutant xenograft models with minimal impact on insulin, a marker of dysregulated glucose homeostasis. RLY-2608 elicited objective tumor responses in two patients diagnosed with advanced hormone receptor-positive breast cancer with kinase or helical domain PIK3CA mutations, with no observed WT PI3Kα-related toxicities.

SIGNIFICANCE

Treatments for PIK3CA-mutant cancers are limited by toxicities associated with the inhibition of WT PI3Kα. Molecular dynamics, cryo-electron microscopy, and DNA-encoded libraries were used to develop RLY-2608, a first-in-class inhibitor that demonstrates mutant selectivity in patients. This marks the advance of clinical mutant-selective inhibition that overcomes limitations of orthosteric PI3Kα inhibitors. See related commentary by Gong and Vanhaesebroeck, p. 204 . See related article by Varkaris et al., p. 227 . This article is featured in Selected Articles from This Issue, p. 201.

Clinical and Genomic Landscape of FGFR3-Altered Urothelial Carcinoma and Treatment Outcomes with Erdafitinib: A Real-World Experience

PURPOSE

Erdafitinib is the only FDA-approved targeted therapy for FGFR2/3-altered metastatic urothelial cancer. We characterized the genetic landscape of FGFR-altered urothelial carcinoma and real-world clinical outcomes with erdafitinib, including on-treatment genomic evolution.

EXPERIMENTAL DESIGN

Prospectively collected clinical data were integrated with institutional genomic data to define the landscape of FGFR2/3-altered urothelial carcinoma. To identify mechanisms of erdafitinib resistance, a subset of patients underwent prospective cell-free (cf) DNA assessment.

RESULTS

FGFR3 alterations predictive of erdafitinib sensitivity were identified in 39% (199/504) of patients with non-muscle invasive, 14% (75/526) with muscle-invasive, 43% (81/187) with localized upper tract, and 26% (59/228) with metastatic specimens. One patient had a potentially sensitizing FGFR2 fusion. Among 27 FGFR3-altered cases with a primary tumor and metachronous metastasis, 7 paired specimens (26%) displayed discordant FGFR3 status. Erdafitinib achieved a response rate of 40% but median progression-free and overall survival of only 2.8 and 6.6 months, respectively (n = 32). Dose reductions (38%, 12/32) and interruptions (50%, 16/32) were common. Putative resistance mutations detected in cfDNA involved TP53 (n = 5), AKT1 (n = 1), and second-site FGFR3 mutations (n = 2).

CONCLUSIONS

FGFR3 mutations are common in urothelial carcinoma, whereas FGFR2 alterations are rare. Discordance of FGFR3 mutational status between primary and metastatic tumors occurs frequently and raises concern over sequencing archival primary tumors to guide patient selection for erdafitinib therapy. Erdafitinib responses were typically brief and dosing was limited by toxicity. FGFR3, AKT1, and TP53 mutations detected in cfDNA represent putative mechanisms of acquired erdafitinib resistance.

Assessing the Genomic Landscape of Cervical Cancers: Clinical Opportunities and Therapeutic Targets

PURPOSE

Tumor genomic profiling is increasingly used to guide treatment strategy in patients with cancer. We integrated tumor genomic, clinical demographic, and treatment response data to assess how prospective tumor-normal sequencing impacted treatment selection in patients with cervical cancer.

EXPERIMENTAL DESIGN

Cervical cancers were prospectively analyzed using the MSK-IMPACT (Memorial Sloan Kettering Cancer Center - Integrated Mutation Profiling of Actionable Cancer Targets) next-generation sequencing panel. Clinical data, including histology, stage at diagnosis, treatment history, clinical trial enrollment and outcomes, date of last follow-up, and survival status were obtained from medical records.

RESULTS

A total of 177 patients with cervical cancer (squamous, 69; endocervical adenocarcinoma, 50; gastric type, 22; adenosquamous, 21; and other, 15) underwent MSK-IMPACT testing. The most prevalent genomic alterations were somatic mutations or amplifications in PIK3CA (25%), ERBB2 (12%), KMT2C (10%), and KMT2D (9%). Furthermore, 13% of patients had high tumor mutational burden (TMB >10 mut/Mb), 3 of which were also microsatellite instability-high (MSI-H). Thirty-seven percent of cases had at least one potentially actionable alteration designated as a level 3B mutational event according to the FDA-recognized OncoKB tumor mutation database and treatment classification system. A total of 30 patients (17%) were enrolled on a therapeutic clinical trial, including 18 (10%) who were matched with a study based on their MSK-IMPACT results. Twenty patients (11%) participated in an immune checkpoint inhibition study for metastatic disease; 2 remain progression free at >5 years follow-up.

CONCLUSIONS

Tumor genomic profiling can facilitate the selection of targeted/immunotherapies, as well as clinical trial enrollment, for patients with cervical cancer.

Single-cell genotypic and phenotypic analysis of measurable residual disease in acute myeloid leukemia

Measurable residual disease (MRD), defined as the population of cancer cells that persist following therapy, serves as the critical reservoir for disease relapse in acute myeloid leukemia and other malignancies. Understanding the biology enabling MRD clones to resist therapy is necessary to guide the development of more effective curative treatments. Discriminating between residual leukemic clones, preleukemic clones, and normal precursors remains a challenge with current MRD tools. Here, we developed a single-cell MRD (scMRD) assay by combining flow cytometric enrichment of the targeted precursor/blast population with integrated single-cell DNA sequencing and immunophenotyping. Our scMRD assay shows high sensitivity of approximately 0.01%, deconvolutes clonal architecture, and provides clone-specific immunophenotypic data. In summary, our scMRD assay enhances MRD detection and simultaneously illuminates the clonal architecture of clonal hematopoiesis/preleukemic and leukemic cells surviving acute myeloid leukemia therapy.

Determinants of Survival with Combined HER2 and PD-1 Blockade in Metastatic Esophagogastric Cancer

PURPOSE

We report updated clinical outcomes from a phase II study of pembrolizumab, trastuzumab, and chemotherapy (PTC) in metastatic esophagogastric cancer in conjunction with outcomes from an independent Memorial Sloan Kettering (MSK) cohort.

PATIENTS AND METHODS

The significance of pretreatment 89Zr-trastuzumab PET, plasma circulating tumor DNA (ctDNA) dynamics, and tumor HER2 expression and whole exome sequencing was evaluated to identify prognostic biomarkers and mechanisms of resistance in patients treated on-protocol with PTC. Additional prognostic features were evaluated using a multivariable Cox regression model of trastuzumab-treated MSK patients (n = 226). Single-cell RNA sequencing (scRNA-seq) data from MSK and Samsung were evaluated for mechanisms of therapy resistance.

RESULTS

89Zr-trastuzumab PET, scRNA-seq, and serial ctDNA with CT imaging identified how pre-treatment intrapatient genomic heterogeneity contributes to inferior progression-free survival (PFS). We demonstrated that the presence of intensely avid lesions by 89Zr-trastuzumab PET declines in tumor-matched ctDNA by 3 weeks, and clearance of tumor-matched ctDNA by 9 weeks were minimally invasive biomarkers of durable PFS. Paired pre- and on-treatment scRNA-seq identified rapid clearance of HER2-expressing tumor clones with expansion of clones expressing a transcriptional resistance program, which was associated with MT1H, MT1E, MT2A, and MSMB expression. Among trastuzumab-treated patients at MSK, ERBB2 amplification was associated with improved PFS, while alterations in MYC and CDKN2A/B were associated with inferior PFS.

CONCLUSIONS

These findings highlight the clinical relevance of identifying baseline intrapatient heterogeneity and serial ctDNA monitoring of HER2-positive esophagogastric cancer patients to identify early evidence of treatment resistance, which could guide proactive therapy escalation or deescalation.

OX40L-expressing recombinant modified vaccinia virus Ankara induces potent antitumor immunity via reprogramming Tregs

Effective depletion of immune suppressive regulatory T cells (Tregs) in the tumor microenvironment without triggering systemic autoimmunity is an important strategy for cancer immunotherapy. Modified vaccinia virus Ankara (MVA) is a highly attenuated, non-replicative vaccinia virus with a long history of human use. Here, we report rational engineering of an immune-activating recombinant MVA (rMVA, MVA∆E5R-Flt3L-OX40L) with deletion of the vaccinia E5R gene (encoding an inhibitor of the DNA sensor cyclic GMP-AMP synthase, cGAS) and expression of two membrane-anchored transgenes, Flt3L and OX40L. Intratumoral (IT) delivery of rMVA (MVA∆E5R-Flt3L-OX40L) generates potent antitumor immunity, dependent on CD8+ T cells, the cGAS/STING-mediated cytosolic DNA-sensing pathway, and type I IFN signaling. Remarkably, IT rMVA (MVA∆E5R-Flt3L-OX40L) depletes OX40hi regulatory T cells via OX40L/OX40 interaction and IFNAR signaling. Single-cell RNA-seq analyses of tumors treated with rMVA showed the depletion of OX40hiCCR8hi Tregs and expansion of IFN-responsive Tregs. Taken together, our study provides a proof-of-concept for depleting and reprogramming intratumoral Tregs via an immune-activating rMVA.

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes

PURPOSE

To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes.

EXPERIMENTAL DESIGN

We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival.

RESULTS

We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy.

CONCLUSIONS

Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.

Multimodal integration of radiology, pathology and genomics for prediction of response to PD-(L)1 blockade in patients with non-small cell lung cancer

Immunotherapy is used to treat almost all patients with advanced non-small cell lung cancer (NSCLC); however, identifying robust predictive biomarkers remains challenging. Here we show the predictive capacity of integrating medical imaging, histopathologic and genomic features to predict immunotherapy response using a cohort of 247 patients with advanced NSCLC with multimodal baseline data obtained during diagnostic clinical workup, including computed tomography scan images, digitized programmed death ligand-1 immunohistochemistry slides and known outcomes to immunotherapy. Using domain expert annotations, we developed a computational workflow to extract patient-level features and used a machine-learning approach to integrate multimodal features into a risk prediction model. Our multimodal model (area under the curve (AUC) = 0.80, 95% confidence interval (CI) 0.74-0.86) outperformed unimodal measures, including tumor mutational burden (AUC = 0.61, 95% CI 0.52-0.70) and programmed death ligand-1 immunohistochemistry score (AUC = 0.73, 95% CI 0.65-0.81). Our study therefore provides a quantitative rationale for using multimodal features to improve prediction of immunotherapy response in patients with NSCLC using expert-guided machine learning.

Mitonuclear genotype remodels the metabolic and microenvironmental landscape of Hürthle cell carcinoma

Hürthle cell carcinomas (HCCs) display two exceptional genotypes: near-homoplasmic mutation of mitochondrial DNA (mtDNA) and genome-wide loss of heterozygosity (gLOH). To understand the phenotypic consequences of these genetic alterations, we analyzed genomic, metabolomic, and immunophenotypic data of HCC and other thyroid cancers. Both mtDNA mutations and profound depletion of citrate pools are common in HCC and other thyroid malignancies, suggesting that thyroid cancers are broadly equipped to survive tricarboxylic acid cycle impairment, whereas metabolites in the reduced form of NADH-dependent lysine degradation pathway were elevated exclusively in HCC. The presence of gLOH was not associated with metabolic phenotypes but rather with reduced immune infiltration, indicating that gLOH confers a selective advantage partially through immunosuppression. Unsupervised multimodal clustering revealed four clusters of HCC with distinct clinical, metabolomic, and microenvironmental phenotypes but overlapping genotypes. These findings chart the metabolic and microenvironmental landscape of HCC and shed light on the interaction between genotype, metabolism, and the microenvironment in cancer.

Tumor-induced double positive T cells display distinct lineage commitment mechanisms and functions

Transcription factors ThPOK and Runx3 regulate the differentiation of "helper" CD4+ and "cytotoxic" CD8+ T cell lineages respectively, inducing single positive (SP) T cells that enter the periphery with the expression of either the CD4 or CD8 co-receptor. Despite the expectation that these cell fates are mutually exclusive and that mature CD4+CD8+ double positive (DP) T cells are present in healthy individuals and augmented in the context of disease, yet their molecular features and pathophysiologic role are disputed. Here, we show DP T cells in murine and human tumors as a heterogenous population originating from SP T cells which re-express the opposite co-receptor and acquire features of the opposite cell type's phenotype and function following TCR stimulation. We identified distinct clonally expanded DP T cells in human melanoma and lung cancer by scRNA sequencing and demonstrated their tumor reactivity in cytotoxicity assays. Our findings indicate that antigen stimulation induces SP T cells to differentiate into DP T cell subsets gaining in polyfunctional characteristics.

Semisupervised Training of a Brain MRI Tumor Detection Model Using Mined Annotations

Background Artificial intelligence (AI) applications for cancer imaging conceptually begin with automated tumor detection, which can provide the foundation for downstream AI tasks. However, supervised training requires many image annotations, and performing dedicated post hoc image labeling is burdensome and costly. Purpose To investigate whether clinically generated image annotations can be data mined from the picture archiving and communication system (PACS), automatically curated, and used for semisupervised training of a brain MRI tumor detection model. Materials and Methods In this retrospective study, the cancer center PACS was mined for brain MRI scans acquired between January 2012 and December 2017 and included all annotated axial T1 postcontrast images. Line annotations were converted to boxes, excluding boxes shorter than 1 cm or longer than 7 cm. The resulting boxes were used for supervised training of object detection models using RetinaNet and Mask region-based convolutional neural network (R-CNN) architectures. The best-performing model trained from the mined data set was used to detect unannotated tumors on training images themselves (self-labeling), automatically correcting many of the missing labels. After self-labeling, new models were trained using this expanded data set. Models were scored for precision, recall, and F1 using a held-out test data set comprising 754 manually labeled images from 100 patients (403 intra-axial and 56 extra-axial enhancing tumors). Model F1 scores were compared using bootstrap resampling. Results The PACS query extracted 31 150 line annotations, yielding 11 880 boxes that met inclusion criteria. This mined data set was used to train models, yielding F1 scores of 0.886 for RetinaNet and 0.908 for Mask R-CNN. Self-labeling added 18 562 training boxes, improving model F1 scores to 0.935 (P < .001) and 0.954 (P < .001), respectively. Conclusion The application of semisupervised learning to mined image annotations significantly improved tumor detection performance, achieving an excellent F1 score of 0.954. This development pipeline can be extended for other imaging modalities, repurposing unused data silos to potentially enable automated tumor detection across radiologic modalities. © RSNA, 2022 Online supplemental material is available for this article.

Tumor fraction-guided cell-free DNA profiling in metastatic solid tumor patients

BACKGROUND

Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth.

METHODS

Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. Plasma samples with no somatic alterations detected by cf-IMPACT were triaged based on sWGS-estimated tumor fraction for analysis with either a less comprehensive but more sensitive assay (MSK-ACCESS) or broader whole exome sequencing (WES).

RESULTS

cfDNA profiling using cf-IMPACT identified somatic mutations in 55/76 (72%) patients for whom MSK-IMPACT tumor profiling data were available. A significantly higher concordance of mutational profiles and tumor mutational burden (TMB) was observed between plasma and tumor profiling for plasma samples with a high tumor fraction (z-score≥5). In the 42 patients from whom tumor data was not available, cf-IMPACT identified mutations in 16/42 (38%). In total, cf-IMPACT analysis of plasma revealed mutations in 71/118 (60%) patients, with clinically actionable alterations identified in 30 (25%), including therapeutic targets of FDA-approved drugs. Of the 47 samples without alterations detected and low tumor fraction (z-score<5), 29 had sufficient material to be re-analyzed using a less comprehensive but more sensitive assay, MSK-ACCESS, which revealed somatic mutations in 14/29 (48%). Conversely, 5 patients without alterations detected by cf-IMPACT and with high tumor fraction (z-score≥5) were analyzed by WES, which identified mutational signatures and alterations in potential oncogenic drivers not covered by the cf-IMPACT panel. Overall, we identified mutations in 90/118 (76%) patients in the entire cohort using the three complementary plasma profiling approaches.

CONCLUSIONS

cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.

Rare BRAF mutations in pancreatic neuroendocrine tumors may predict response to RAF and MEK inhibition

The clinical significance of BRAF alterations in well-differentiated (WD) metastatic pancreatic neuroendocrine tumor (panNET) is unknown, but BRAF-mutated panNET could represent a subset characterized by an identifiable and clinically actionable driver. Following the identification of two patients with WD metastatic panNET whose tumors harbored BRAF mutations, we queried the MSK-IMPACT series of 80 patients with WD metastatic panNET for additional mutations in BRAF, and in other genes involved in RAS/ RTK/ PI3K signaling pathways. BRAF mutations were identified in six samples (7.5%): two tumors harbored V600E mutations, one tumor each expressed K601E, T599K, and T310I mutations, and one tumor expressed both G596D and E451K BRAF. Few additional actionable driver alterations were identified. To determine the ERK activating capability of four BRAF mutations not previously characterized, mutant constructs were tested in model systems. Biochemical characterization of BRAF mutations revealed both high and low activity mutants. Engineered cells expressing BRAF K601E and V600E were used for in vitro drug testing of RAF and MEK inhibitors currently in clinical use. BRAF K601E demonstrated reduced sensitivity to dabrafenib compared to BRAF V600E, but the combination of RAF plus MEK inhibition was effective in cells expressing this mutation. Herein, we describe the clinical course of a patient with BRAF K601E and a patient with BRAF V600E WD metastatic panNET, and the identification of four mutations in BRAF not previously characterized. The combined clinical and biochemical data support a potential role for RAF and MEK inhibitors, or a combination of these, in a selected panNET population.