Abstract 131P
Background
Molecular profiling helps determine eligibility for administering targeted inhibitors in non-small cell lung cancers (NSCLC). Biopsy is critical for IHC/NGS analysis, however imaging biomarkers are being increasingly used for this purpose. We explored the potential value of FDG PET in predicting molecular targets like EGFR & ALK and PDL1 overexpression in NSCLC patients.
Methods
Retrospective analysis of FDG PET & molecular data of biopsy proven NSCLC patients was performed. Whole body MTV & TLG and SUVmax of the primary, nodes and distant metastases were determined. Statistical analysis done using independent-samples t-test & one-way ANOVA and logistic regression for estimation of OR and 95% CI.
Results
Data of 266 patients was analysed with 34 ALK1-positive (n=241) and 81 EGFR-positive (n=253) cases; 68 cases with PDL1 strong expression (TPS ≥50%) & 127 with moderate (TPS 1-49%) (n=265). ALK1 & EGFR positive tumors had lower pSUVmax compared to negative counterparts (p<0.05) with high tendency to harbor EGFR mutated tumor below the cutoff 20.48 (p<0.05). Odds of having ALK1 positive tumor was higher with pSUVmax ≤10.66, but not statistically significant. Tumors with strong PDL1 expression had higher pSUVmax & nSUVmax compared to non-expressing tumors, with cut-offs ≥20.71 & ≥14.99, respectively (p<0.05, Sp- 83.25% & NPV- 79.6%). PDL1 expressing SqCC displayed significantly higher pSUVmax and wbTLG as compared to non-SqCC. pSUVmax cut-off in purely EGFR mutated tumors with PDL1 negative status was lowered to ≤10.66, below which risk of harboring EGFR mutation driven tumor was even higher (Sp- 77.5%, NPV- 94%). mSUVmax and wbMTV did not correlate with any of the molecular features.
Table: 131P
Regression analysis of PDL1xEGFR co-expression with pSUVmax (ref: both negative)
| pSUVmax | OR | p-value | |
| Positive EGFR- Positive PDL1 | <= 10.665 vs >20.51 | 1.714 | 0.409 |
| Positive EGFR- Negative PDL1 | <= 10.665 vs >20.51 | 15.714 | 0.017* |
| Negative EGFR- Positive PDL1 | <= 10.665 vs >20.51 | 1.107 | 0.853 |
Conclusions
Molecular spectrum encompassing oncogenic drivers and immune checkpoints in NSCLCs resulted in variegated metabolic features. Metabolic parameters on FDG PET can provide valuable information about tumor molecular profile and can potentially act as effective non-invasive imaging biomarker.
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.