Case Report Details Aumolertinib Rechallenge Following Osimertinib-Induced Interstitial Lung Disease in Lung Adenocarcinoma
Can lung cancer drugs be restarted after severe lung injury?
This case report describes a 73-year-old male with stage IV lung adenocarcinoma and EGFR exon 19 deletions who experienced interstitial lung…
Doctors successfully restarted a powerful lung cancer drug after a patient's lungs healed from a dangerous reaction to the first one.
Case report and literature review on T-SMARCA4-DUT diagnosis and treatment response in a single patient
A Rare Tumor That Fooled Doctors at Every Step — Until One Test Changed Everything
This case report and literature review describes a 64-year-old male with thoracic SMARCA4-deficient undifferentiated tumor initially misdiag…
A rare chest tumor mimicking lung cancer was misdiagnosed until a specific genetic test revealed the true cause, proving one marker can prev…
Review describes Virtual Spectral Decomposition framework for cancer imaging analysis
AI Now Reads Tumor Slides Like a Radiologist — and Shows Its Work
This review/commentary outlines a Virtual Spectral Decomposition (VSD) methodological framework for analyzing digital pathology and imaging …
A new AI system reads cancer slides like a doctor and explains exactly which biological features drove each diagnosis.
Gene expression programs associated with survival and recurrence in early-stage lung adenocarcinoma patients
Why Your Lung Cancer Risk Is Not The Same As Your Neighbor's
This retrospective cohort study evaluated gene expression programs in early-stage (IA/IB) lung adenocarcinoma patients. The analysis utilize…
Hidden immune signals in early lung cancer act like a weather forecast, predicting who will stay well and who faces a quick return of the di…
NR2F2 expression in CAFs linked to poor prognosis and enhanced tumor progression in lung adenocarcinoma models.
A Hidden Cell Type in Lung Cancer May Hold a New Target
This preclinical and computational study analyzed public databases and performed in vitro experiments to evaluate cancer-associated fibrobla…
A hidden protein in support cells around lung tumors may drive cancer growth, pointing to a new treatment target for lung adenocarcinoma.
Predictive nomogram with spectral CT radiomics and deep learning features improves preoperative STAS prediction in surgically resected lung adenocarcinoma.
A Simple Scan May Now Predict a Hidden Lung Cancer Danger Before Surgery
This cohort study evaluated a predictive nomogram combining spectral dual-layer detector CT radiomics, deep learning features, and pleural i…
Doctors may soon use artificial intelligence to find a hidden sign of aggressive lung cancer before a patient ever goes into the operating r…
AM.score predicts lung adenocarcinoma outcomes and immunotherapy response in a cohort of 1,720 patients.
A Simple Blood Test Could Predict Your Lung Cancer Treatment Success
This preprint describes an observational cohort study involving 1,720 lung adenocarcinoma patients, with validation across additional cohort…
A new blood test score predicts which lung cancer patients will respond to immunotherapy, helping doctors avoid ineffective treatments for a…
CT-based radiomics shows variable accuracy for predicting occult lymph node metastasis in early-stage lung adenocarcinoma
CT scan analysis shows promise for predicting hidden cancer spread in early lung cancer
A meta-analysis of 10 studies including 6,349 patients with early-stage lung adenocarcinoma found CT-based radiomics had pooled sensitivity …
Computer analysis of regular CT scans can spot hidden cancer spread in early lung cancer with about 85% accuracy when tested in the same hos…
Radiomics-ML model predicts invasiveness in subcentimeter subsolid lung adenocarcinoma
AI model shows promise for predicting cancer invasiveness in small lung nodules
A two-center retrospective cohort study of 260 patients with surgically confirmed subcentimeter subsolid lung adenocarcinoma developed and v…
An AI model predicts whether tiny, hazy lung spots are invasive cancer with 79% accuracy, offering a new tool for doctors to spot dangerous …