Ludwig Enterprises Announces Publication of ASCO Abstract Detailing Novel Non-Invasive mRNA Signals that Scan for Breast Cancer
Ludwig Enterprises (LUDG) has published an abstract on the ASCO website detailing a novel breast cancer screening method that analyzes mRNA from non-invasively collected buccal (cheek) cells combined with machine learning algorithms. The study, conducted across 40 U.S. clinical centers, developed a custom microarray chip analyzing 48 mRNA-based cytokine biomarkers.
The research identified two high-performing six-biomarker combinations, achieving impressive metrics with F-scores ≥0.85. The first system achieved precision of 0.892, recall of 0.913, and an AUC of 0.897, while the second system showed precision of 0.888, recall of 0.902, and an AUC of 0.849. These results suggest potential clinical utility for early breast cancer detection using this non-invasive screening approach.
Ludwig Enterprises (LUDG) ha pubblicato un abstract sul sito ASCO che descrive un nuovo metodo di screening per il cancro al seno basato sull'analisi dell'mRNA estratto da cellule buccali (dalla guancia) raccolte in modo non invasivo, combinato con algoritmi di apprendimento automatico. Lo studio, condotto in 40 centri clinici negli Stati Uniti, ha sviluppato un microarray personalizzato per analizzare 48 biomarcatori di citochine basati su mRNA.
La ricerca ha individuato due combinazioni di sei biomarcatori con alte prestazioni, ottenendo risultati notevoli con F-score ≥0,85. Il primo sistema ha raggiunto una precisione di 0,892, un richiamo (recall) di 0,913 e un AUC di 0,897, mentre il secondo ha mostrato una precisione di 0,888, un richiamo di 0,902 e un AUC di 0,849. Questi risultati indicano un potenziale utilizzo clinico per la rilevazione precoce del cancro al seno tramite questo approccio di screening non invasivo.
Ludwig Enterprises (LUDG) ha publicado un resumen en el sitio web de ASCO que detalla un novedoso método de detección de cáncer de mama que analiza el ARNm de células bucales (mejilla) recolectadas de forma no invasiva junto con algoritmos de aprendizaje automático. El estudio, realizado en 40 centros clínicos en EE.UU., desarrolló un microarray personalizado que analiza 48 biomarcadores de citoquinas basados en ARNm.
La investigación identificó dos combinaciones de seis biomarcadores con alto rendimiento, logrando métricas impresionantes con puntuaciones F ≥0,85. El primer sistema alcanzó una precisión de 0,892, una sensibilidad (recall) de 0,913 y un AUC de 0,897, mientras que el segundo mostró una precisión de 0,888, sensibilidad de 0,902 y un AUC de 0,849. Estos resultados sugieren un potencial uso clínico para la detección temprana del cáncer de mama mediante este método de cribado no invasivo.
Ludwig Enterprises (LUDG)는 ASCO 웹사이트에 비침습적으로 채취한 구강 점막(볼) 세포의 mRNA를 분석하고 기계 학습 알고리즘을 결합한 새로운 유방암 선별 검사 방법에 대한 초록을 발표했습니다. 이 연구는 미국 내 40개 임상 센터에서 수행되었으며, 48개의 mRNA 기반 사이토카인 바이오마커를 분석하는 맞춤형 마이크로어레이 칩을 개발했습니다.
연구에서는 두 가지 고성능 6 바이오마커 조합을 확인했으며, F-점수 ≥0.85의 뛰어난 성능을 보였습니다. 첫 번째 시스템은 정밀도 0.892, 재현율 0.913, AUC 0.897을 달성했으며, 두 번째 시스템은 정밀도 0.888, 재현율 0.902, AUC 0.849을 나타냈습니다. 이 결과는 비침습적 선별 검사 방법을 활용한 유방암 조기 발견에 임상적 활용 가능성을 시사합니다.
Ludwig Enterprises (LUDG) a publié un résumé sur le site de l'ASCO présentant une nouvelle méthode de dépistage du cancer du sein qui analyse l'ARNm provenant de cellules buccales (joue) collectées de manière non invasive, combinée à des algorithmes d'apprentissage automatique. L'étude, menée dans 40 centres cliniques aux États-Unis, a développé une puce microarray personnalisée analysant 48 biomarqueurs de cytokines basés sur l'ARNm.
La recherche a identifié deux combinaisons performantes de six biomarqueurs, obtenant des scores F impressionnants de
Ludwig Enterprises (LUDG) hat auf der ASCO-Website eine Zusammenfassung veröffentlicht, die eine neuartige Brustkrebsvorsorgemethode beschreibt. Diese analysiert mRNA aus nicht-invasiv gewonnenen Wangenzellen kombiniert mit maschinellen Lernalgorithmen. Die Studie, die an 40 klinischen Zentren in den USA durchgeführt wurde, entwickelte einen maßgeschneiderten Mikroarray-Chip zur Analyse von 48 mRNA-basierten Zytokin-Biomarkern.
Die Forschung identifizierte zwei leistungsstarke Kombinationen aus jeweils sechs Biomarkern mit beeindruckenden Kennzahlen von F-Scores ≥0,85. Das erste System erreichte eine Präzision von 0,892, eine Sensitivität (Recall) von 0,913 und eine AUC von 0,897, während das zweite System eine Präzision von 0,888, einen Recall von 0,902 und eine AUC von 0,849 zeigte. Diese Ergebnisse deuten auf einen potenziellen klinischen Nutzen für die Früherkennung von Brustkrebs mittels dieses nicht-invasiven Screening-Ansatzes hin.
- Development of a novel, non-invasive breast cancer screening method using cheek cell samples
- Strong performance metrics with F-scores ≥0.85 in both biomarker systems
- Research conducted across 40 U.S. clinical centers, indicating broad study scope
- Potential for earlier and less invasive breast cancer detection
- Technology still in research phase, not yet commercially available
- Further validation studies likely needed before regulatory approval
MIAMI, FL / ACCESS Newswire / May 29, 2025 / Ludwig Enterprises (LUDG) today announced the publication of an abstract on the American Society of Clinical Oncology (ASCO) website in connection with the ASCO 2025 Annual Meeting, previously under embargo, detailing a novel, non-invasive scanning test for breast cancer. The research combines the analysis of messenger RNA (mRNA) from non-invasively collected buccal (cheek) cells with machine learning algorithms.
The abstract, titled "Non-invasively-collected buccal cell mRNA reveals novel breast cancer signal," highlights the potential of this approach to screen for breast cancer. Breast cancer remains the most frequently diagnosed cancer globally. While DNA genetic testing is widely used, mRNA analysis can offer complementary diagnostic insights, particularly concerning inflammatory pathways linked to cancer development. The study underscores that intercellular mRNA communication is a key characteristic of chronic inflammation associated with cancer development.
"Ludwig Enterprises is pleased to now share these encouraging findings with the broader scientific community and the public, following the lifting of the ASCO embargo," said Marvin S. Hausman, MD, Chief Science Officer at Ludwig Enterprises. "This research represents a potential step forward in developing less invasive screening options that could aid in the earlier detection of breast cancer."
Study Highlights:
METHODS Buccal cheek swab samples were collected non-invasively from breast cancer patients and controls across 40 U.S. clinical centers, and a custom microarray chip was developed to analyze 48 mRNA-based cytokine biomarkers, selected for their association with inflammatory pathways and cancer development. Next-generation sequencing was performed using Thermo Fisher Genestudio S-5 following cDNA target amplification. We then used these data to train a linear support vector machine to classify subjects with respect to their cancer status. We were particularly interested in identifying a small subset of these biomarkers that could yield significant results to create a lower-dimensional, efficient classification approach.
RESULTS Our analysis identified a collection of six-biomarker combinations yielding excellent results (F-score ≥0.85). We present the two top-performing biomarker combinations (see table), along with their respective performance metrics.
CONCLUSION Our results demonstrate the potential of mRNA biomarker panels, combined with machine learning, to generate a signal for detecting breast cancer from non-invasively collected samples. The high precision and recall values suggest clinical utility for early detection.
System | BM1 | BM2 | BM3 | BM4 | BM5 | BM6 | P | R | F1 | AUC |
SYSTEM 1 | CASP9 | ILIB | IL6 | RGS2 | SLC40A1 | STK11 | 0.892 | 0.913 | 0.9 | 0.897 |
SYSTEM 2 | HAMP | ILIO | RGS2 | SLC22A4 | STK11 | TGFB1 | 0.888 | 0.902 | 0.892 | 0.849 |
About Ludwig Enterprises, Inc.
Ludwig Enterprises, Inc. (which is in the process of changing its name to Revealia Diagnostics, Inc.), a biotech and healthcare holding company, is a global innovator in mRNA genomics and machine learning AI technology. Our mission is to identify, monitor, and create solutions to mitigate chronic inflammation, the causative agent of illnesses such as cancer and heart disease, which are responsible for more than
For more information, please visit: http://www.ludwigent.com.
SAFE HARBOR
Forward-looking statements in this release are made under the "safe harbor" provision of the Private Securities Litigation Reform Act of 1995. Ludwig Enterprises Inc.'s forward-looking statements do not guarantee future performance. This news release includes forward-looking statements concerning the future level of business for the parties. These statements are necessarily subject to risk and uncertainty. Actual results could differ materially from those projected in these forward-looking statements due to certain risk factors that could cause results to differ materially from estimated results. Management cautions that all statements as to future results of operations are necessarily subject to risks, uncertainties, and events that may be beyond the control of Ludwig Enterprises, Inc., and no assurance can be given that such results will be achieved. Potential risks and uncertainties include, but are not limited to, the ability to procure, appropriately price, retain, and complete projects and changes in products and competition.
FOR FURTHER INFORMATION:
CONTACT:
Ludwig Enterprises, Inc.
www.ludwigent.com
Twitter: @LUDG_inc
IR@revealia.com
References:
Hausman, Marvin (2025, May 28). Non-invasively collected buccal cell mRNA and potential for a novel breast cancer signal. ASCO. https://meetings.asco.org/abstracts-presentations/244635
SOURCE: Ludwig Enterprises Inc.
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