The treatment in patients with unresectable locally advanced non-small cell lung cancer: Explorations on hot issues

Identification of a DNA-methylome-based signature for prognosis prediction in driver gene-negative lung adenocarcinoma

"Driver gene-negative" lung adenocarcinoma (LUAD) was of rare treatment options and a poor prognosis. Presently, for them, few biomarkers are available for stratification analysis to make appropriate treatment strategy. This study aimed to develop a DNA-methylome-based signature to realize the precise risk-stratifying. Here, an Illumina MethylationEPIC Beadchip was applied to obtain differentially methylated CpG sites (DMCs). A four-CpG-based signature, named as TLA, was successfully established, whose prognosis-predicting power was well verified in one internal (n = 78) and other external (n = 110) validation cohorts. Patients with high-risk scores had shorter overall survival (OS) in all cohorts [hazard ratio (HR): 11.79, 5.16 and 2.99, respectively]. Additionally, it can effectively divide patients into low-risk and high-risk groups, with significantly different OS in the diverse subgroups stratified by the standard clinical parameters. As an independent prognostic factor, TLA may assist in improving the nomogram's 5-year OS-predicting ability (AUC 0.756, 95% CI:0.695-0.816), superior to TNM alone (AUC 0.644, 95% CI: 0.590-0.698). Additionally, the relationship of TLA-related genes, TAC1, LHX9, and ALX1, with prognosis and tumour invasion made them serve as potential therapy targets for driver gene-negative LUAD.

Nomogram-based prognostic tool for stage IIIB/IV non-small cell lung cancer patients undergoing traditional Chinese medicine treatment

Objective

Given the significant impact of long-term traditional Chinese medicine (TCM) treatment on the prognosis of patients with non-small cell lung cancer (NSCLC), we aimed to develop nomograms, with or without consideration of TCM treatment duration, to accurately predict the overall survival (OS) of patients with stage IIIB/IV NSCLC treated with TCM.

Methods

Nomograms were developed from a training cohort comprised of 292 patients diagnosed with NSCLC, using univariate and multivariate Cox regression analyses to screen for various prognostic factors with and without TCM treatment. The nomograms were evaluated using the concordance index (C-index), calibration curve, and decision curve analysis (DCA), after which they were validated, using the bootstrap self-sampling method for internal validation, and a validation cohort comprised of 175 patients for external validation. Bootstrap validation is a resampling technique that involves randomly selecting and replacing data from the original dataset to make statistical inferences, thereby circumventing the issue of sample reduction that can arise from cross-validation.

Results

We identified seven significant prognostic factors for OS. For nomogram A (excluding TCM treatment time), the C-indexes (95 % confidence interval [CI]) were 0.674 (0.635-0.712) and 0.660 (0.596-0.724) for the training and validation cohorts, respectively. For nomogram B (including TCM treatment time), the C-indices (95 % CI) were 0.846 (0.822-0.870) and 0.783 (0.730-0.894), for the training and validation cohorts, respectively, indicating that nomogram B was superior to nomogram A. Both the calibration curves and DCA results exhibited favorable clinical concordance and usefulness.

Conclusion

The nomogram B yielded precise prognostic predictions for patients with advanced NSCLC treated with TCM.

Targeting IL-6/STAT3 signaling abrogates EGFR-TKI resistance through inhibiting Beclin-1 dependent autophagy in HNSCC

Head and neck squamous cell carcinoma (HNSCC) is featured by notorious EGFR tyrosine kinase inhibitor (TKI) resistance attributable to activation of parallel pathways. The numerous phase I/II trials have rarely shown encouraging clinical outcomes of EGFR-TKIs during treatment in HNSCC patients with advanced tumors. A unique IL-6/STAT3 signaling axis is reported to regulate multiple cancer-related pathways, but whether this signaling is correlated with reduced EGFR-TKI responsiveness is unclear. Here, we found that STAT3 signaling is compensatorily upregulated after EGFR-TKI exposure and confers anti-EGFR therapy resistance during HNSCC therapy. Targeting STAT3 using small molecule inhibitors promotes complete recovery or sustained elimination of HNSCC tumors through combination with EGFR-TKIs both in vitro and in diverse animal models. Mechanistically, phosphorylated STAT3 was proven to enhance oncogenic autophagic flux, protecting cancer cells and preventing EGFR-TKI-induced tumor apoptosis. Thus, blockade of STAT3 signaling simultaneously disrupts several key interactions during tumor progression and remodels the autophagic degradation system, thereby rendering advanced HNSCC eradicable through combination with EGFR-TKI therapy. These findings provide a clinically actionable strategy and suggest STAT3 as a predictive biomarker with therapeutic potential for EGFR-TKI resistant HNSCC patients.