AUTHOR=Sun Taotao , Huang Shujie , Jiang Yongluo , Yuan Hui , Wu Junhan , Liu Chao , Zhang Xiaochun , Tang Yong , Ben Xiaosong , Tang Jiming , Zhou Haiyu , Zhang Dongkun , Xie Liang , Chen Gang , Zhao Yumo , Wang Shuxia , Xu Hao , Qiao Guibin 

TITLE=Dynamic alteration in SULmax predicts early pathological tumor response and short-term prognosis in non-small cell lung cancer treated with neoadjuvant immunochemotherapy

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=10

YEAR=2022

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.1010672

DOI=10.3389/fbioe.2022.1010672

ISSN=2296-4185

ABSTRACT=<p><bold>Introduction:</bold> Biomarkers predicting tumor response to neoadjuvant immunochemotherapy in non-small cell lung cancer (NSCLC) are still lacking despite great efforts. We aimed to assess the effectiveness of the immune PET Response Criteria in Solid Tumors <italic>via</italic> SULmax (iPERCIST-max) in predicting tumor response to neoadjuvant immunochemotherapy and short-term survival in locally advanced NSCLC.</p><p><bold>Methods:</bold> In this prospective cohort study, we calculated SULmax, SULpeak, metabolic tumor volume (MTV), total lesion glycolysis (TLG) and their dynamic percentage changes in a training cohort. We then investigated the correlation between alterations in these parameters and pathological tumor responses. Subsequently, iPERCIST-max defined by the proportional changes in the SULmax response (△SULmax%) was constructed and internally validated using a time-dependent receiver operating characteristic (ROC) curve and the area under the curve (AUC) value. A prospective cohort from the Sun Yat-Sen University Cancer Center (SYSUCC) was also included for external validation. The relationship between the iPERCIST-max responsiveness and event-free survival in the training cohort was also investigated.</p><p><bold>Results:</bold> Fifty-five patients with NSCLC were included in this study from May 2019 to December 2021. Significant alterations in post-treatment SULmax (<italic>p</italic> &lt; 0.001), SULpeak (<italic>p</italic> &lt; 0.001), SULmean (<italic>p</italic> &lt; 0.001), MTV (<italic>p</italic> &lt; 0.001), TLG (<italic>p</italic> &lt; 0.001), and tumor size (<italic>p</italic> &lt; 0.001) were observed compared to baseline values. Significant differences in SULpeak, SULmax, and SULmean between major pathological response (mPR) and non-mPR statuses were observed. The optimal cutoff values of the SULmax response rate were −70.0% and −88.0% using the X-tile software. The univariate and multivariate binary logistic regression showed that iPERCIST-max is the only significant key predictor for mPR status [OR = 84.0, 95% confidence interval (CI): 7.84–900.12, <italic>p</italic> &lt; 0.001]. The AUC value for iPERCIST-max was 0.896 (95% CI: 0.776–1.000, <italic>p</italic> &lt; 0.001). Further, external validation showed that the AUC value for iPERCIST-max in the SYSUCC cohort was 0.889 (95% CI: 0.698–1.000, <italic>p</italic> = 0.05). Significantly better event-free survival (EFS) in iPERCIST-max responsive disease (31.5 months, 95% CI 27.9–35.1) than that in iPERCIST-max unresponsive disease (22.2 months, 95% CI: 17.3–27.1 months, <italic>p</italic> = 0.024) was observed.</p><p><bold>Conclusion:</bold> iPERCIST-max could better predict both early pathological tumor response and short-term prognosis of NSCLC treated with neoadjuvant immunochemotherapy than commonly used criteria. Furthermore, large-scale prospective studies are required to confirm the generalizability of our findings.</p>