A gene expression platform to predict benefit from adjuvant external beam radiation in resected non-small cell lung cancer
Ahmed, K.; Creelan, B.; Peacock, J.; Mellon, E.; Kim, Y.; Grass, G. D.; Perez, B.; Rosenberg, S.; Dilling, T.; Eschrich, S.; Chiappori, A.; Torres-Roca, J.
Show abstract
BackgroundWe hypothesized that the radiosensitivity index (RSI), would classify non-small cell lung cancer (NSCLC) patients into radioresistant (RR) or radiosensitive (RS). MethodsWe identified resected pathologic stage III NSCLC. For the radiation group (RT) group, at least 45 Gy of external beam radiation was required. mRNA was extracted from primary tumor. The predefined cut-point was the median RSI with a primary endpoint of local control. Similar criteria were then applied to two extramural datasets (E1; E2) with progression free survival as the primary endpoint. ResultsMedian follow-up from diagnosis was 23.5 months (range: 4.8-169.6 months). RSI was associated with time to local failure in the RT group with a two-year rate of local control of 80% and 56% between RS and RR groups, respectively p=0.02. RSI was the only variable found to be significant on Cox local control analysis (HR 2.9; 95% CI: 1.2-8.2; p=0.02). There was no significance of RSI in predicting local control in patients not receiving RT, p=0.48. A cox regression model between receipt of radiotherapy and RSI combining E1 and E2 showed that the interaction term was significant for PFS (3.7; 95% CI 1.4-10; p=0.009). A summary measure combining E1 and E2 showed statistical significance for PFS between RR and RS patients treated with radiotherapy (HR 2.7l; 95% CI 1.3-5.6; p=0.007) but not in patients not treated with radiotherapy (HR 0.94; 95% CI 0.5-1.78; p=0.86). ConclusionsRSI appears to be predictive for benefit from adjuvant radiation. Prospective validation is required.
Matching journals
The top 1 journal accounts for 50% of the predicted probability mass.
Similar papers in this journal
- MET Inhibitor Capmatinib Radiosensitizes MET Exon 14-Mutated and MET-Amplified Non-Small Cell Lung Cancer 95%
- Risk of Clonal Hematopoiesis of Indeterminate Potential after Cancer Radiation Therapy 94%
- Contralateral Neck Recurrence Rates After Ipsilateral Neck Adjuvant Radiation in Head and Neck Carcinomas with a Pathologically Negative Contralateral Neck 94%
Similar papers in this journal
- Detection of Alteration in Carotid Artery Volumetry Using Standard-of-care Computed Tomography Surveillance Scans Following Unilateral Radiation Therapy for Early-stage Tonsillar Squamous Cell Carcinoma Survivors: A Cross-Sectional Internally-Matched Carotid Isodose Analysis 94%
- Re-irradiation to the Prostate using stereotactic body radiotherapy (SBRT) after initial definitive Radiotherapy – A systematic review and Meta-analysis of recent trials 93%
- Morphological changes after cranial fractionated photon radiotherapy: localized loss of white matter and grey matter volume with increasing dose 93%
Similar papers in this journal
- Avasopasem Manganese acts as both a Radioprotector and a Radiomitigator of Radiation-Induced Acute or Late Effects. 95%
- Meta-Analysis of Adenoviral p53 Gene Therapy Clinical Trials in Recurrent Head and Neck Squamous Cell Carcinoma 94%
- mTOR inhibitors as radiosensitizers in neuroendocrine neoplasms 92%
Similar papers in this journal
- Dysphagia and shortness-of-breath as markers for treatment failure and survival in oropharyngeal cancer after radiation 94%
- LITE SABR M1: a Phase I Trial of Lattice Stereotactic Body Radiotherapy for Large Tumors 93%
- Precision association of lymphatic disease spread with radiation-associated toxicity in oropharyngeal squamous carcinomas 93%
Similar papers in this journal
- Effectiveness of FLASH vs conventional dose rate radiotherapy in a model of orthotopic, murine breast cancer 93%
- NDRG1 expression is an independent prognostic factor in inflammatory breast cancer 92%
- Quality of life and patient-reported outcomes following proton therapy for oropharyngeal carcinoma: a systematic review 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.