Evidence map›Paper›PMID 40674592›Full record

Observational studyThe oncologist2025

ENIGMA+: a national, decentralized, remote consent study for clinical data and biospecimen collection in patients with ALK-positive advanced NSCLC.

Joyce Liang, Sarah Waliany, Andrew Do, Jennifer L Peterson, Paige Roberts, Elizabeth A Kennedy, Emily S Venanzi, Justin F Gainor, Jessica J Lin

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in The oncologist, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04881916 (Elucidating Novel Immune and Genomic Markers for ALK), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04881916 active not recruitingnot on this map

Elucidating Novel Immune and Genomic Markers for ALK (ENIGMA+)

Typeobservational_patient_registrySponsorMassachusetts General HospitalRan2021 to 2027Enrolled100ConditionsAnaplastic Lymphoma Kinase Gene Translocation, Non-Small Cell Lung Cancer
3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Joyce LiangDepartment of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, United States.
Sarah WalianyDepartment of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, United States.
Andrew DoDepartment of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, United States.
Jennifer L PetersonDepartment of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, United States.
Paige RobertsDepartment of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, United States.ORCID 0009-0005-8302-3076
Elizabeth A KennedyDepartment of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, United States.
Emily S VenanziALK Positive, Inc., Atlanta, GA, 30328, United States.
Justin F GainorDepartment of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, United States.ORCID 0000-0001-8697-4081
Jessica J LinDepartment of Medicine and Cancer Center, Massachusetts General Hospital, Boston, MA, United States.ORCID 0000-0001-7373-3916

Funding

Project 3P50CA265826 · NCI · DANA-FARBER CANCER INST · PI David A Barbie · 2022 to 2026
$13.7M
Overcoming Resistance Mechanisms to Anaplastic Lymphoma Kinase InhibitorsR01CA164273 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI Aaron N Hata, Jessica Jiyeong Lin · 2012 to 2026
$5.5M
NCI NIH HHS P50 CA265826NCI NIH HHS R01 CA164273NCI NIH HHS R01CA164273Targeting a Cure for Lung Cancer Research FundVenanzi Fund
6 · The paper itself

Abstract

objectiveDespite advances in ALK inhibitors for ALK fusion-positive (ALK+) non-small-cell lung cancer (NSCLC), drug resistance remains a challenge. Studies of treatment outcomes and resistance biomarkers are imperative for drug development, yet patient representation can be limited. This study evaluated the feasibility of a decentralized research infrastructure to establish a clinical and biospecimen repository, broadening patient access and inclusion. PATIENTS AND

methodsPatients with advanced ALK+ NSCLC across the United States were enrolled through remote informed consent. Clinical history and tumor molecular profiling data were collected at baseline and during remote follow-ups. Archival tumor and saliva biospecimens (for germline sampling) were obtained for analysis.

resultsOf 87 eligible patients, 80 (92%) completed remote consent and enrolled. The clinical data collection rate was 100%, with archival tumor acquired from 80% and saliva samples from 65%. Patients represented 31 states, with 94% residing outside the study center's state and 90% receiving care elsewhere. Next-generation sequencing was conducted on 55 treatment-naïve and 18 treatment-resistant biopsies, all of whom received at least one prior second-generation ALK inhibitor, and 9 received lorlatinib. ALK resistance mutations were identified in 54% of treatment-resistant biopsies; other commonly co-altered genes included TP53 (18%) and CDKN2A/B (16%).

conclusionsThis study highlights the feasibility of a decentralized design to enhance the inclusion of a broader patient population with ALK+ NSCLC. This establishes a scalable framework that may help overcome barriers to patient participation in research, with the goal of improving therapy development and patient outcomes. The Elucidating Novel Immune and Genomic Markers for ALK+ study accrual and analysis continue (NCT04881916).

Indexed as

Anaplastic Lymphoma KinaseCarcinoma, Non-Small-Cell LungLung NeoplasmsAdultAgedBiological Specimen BanksBiomarkers, TumorFemaleHumansInformed ConsentMaleMiddle AgedUnited StatesALK protein, humanAnaplastic Lymphoma KinaseBiomarkers, TumorALKNSCLCpatient diversityremote consentresistance

Identifiers

PMID40674592
PMCPMC12404294

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.