Qinfang Deng’s research while affiliated with Tongji Medical University and other places

Background m6A modification has close connection with the occurrence, development, and prognosis of tumors. This study aimed to explore the roles of m6A modification and its related mechanisms in non-small cell lung cancer (NSCLC). Methods NSCLC tissues and their corresponding para-cancerous tissues were collected to determine the m6A levels of total RNA/lncRNAs and the expression of m6A modification-related genes/lncRNAs. Then, A549 cells were transfected with si-METTL14 or oe-METTL14, and the cell transfection efficiency was assessed. Subsequently, the viability, apoptosis, cell colony formation, migration and invasion of the different cells were determined. Finally, the nude mouse tumorigenicity experiments were performed to observe the effects of METTL14 in vivo. Results Compared to the para-NSCLC tissues, the m6A level and METTL14 expression were both significantly increased in the NSCLC tissues (P < 0.05). Based on the expression of METTL14 in the different cell lines, A549 cells were chosen for further experiments. Then, the A549 cells with METTL14 knockdown and overexpression were successfully established, as well as it was found that METTL14 knockdown could inhibit the viability, colony formation, migration, and invasion of A549 cells, while facilitate their apoptosis. In vivo experiments also showed that METTL14 knockdown could inhibit tumor formation and growth. Additionally, the m6A level of MSTRG.292666.16 was higher in the NSCLC tissues; and after METTL14 knockdown, the expression and m6A level of MSTRG.292666.16 were both significantly reduced in A549 cells, and vice versa. Conclusion METTL14 may promote the progression of NSCLC through up-regulating MSTRG.292666.16 and enhance its m6A modification level.

Introduction Despite the benefit of adjuvant systemic therapy for patients with resected non-small cell lung cancer (NSCLC), the risk of postoperative recurrence remains high. Our objective was to characterize temporal genetic heterogeneity between primary resected and recurrent tumors, and its impact on treatment outcomes. Methods In this study, next-generation sequencing (NGS) testing was performed on tissue specimens and circulating tumor DNA (ctDNA) collected at postoperative recurrence, and results were compared to the genotypes of initial surgical specimens. Results Of forty-five patients with matched primary and post-operative recurrent tumors, EGFR status switched in 17 patients (37.8%) at post-operative recurrence and 28 patients (62.2%) had no genotype change (17 mutant, 11 wild-type). Based on the changes of EGFR status, patients were divided into 4 groups. Following subsequent treatment with EGFR TKI o chemotherapy: In group A, with sustained sensitive mutation, the percentage achieving partial response (PR) was the highest, at 72.2%, the median progression-free survival (PFS) was 17 months, and the median overall survival (OS) was 44.0 months respectively; In group B, with genotype changed from wild-type to mutant, 50% achieved PR, PFS was 10 months, and OS was 35 months; In group C, in which mutant status shifted to wild-type or new co-mutation emerged, the percentage achieving PR was 30%, PFS was 9 months, and OS was 35 months. In group D, with sustained wild type, the percentage achieving PR was 27.3%, PFS was 8 months, and OS was 22 months. Discussion Genotypic shift between paired primary and post-operative recurrent tumors was not infrequent, and this temporal genomic heterogeneity substantially impacted subsequent treatment outcomes.

Though immunotherapy has to some extent improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), only a few patients benefit. Furthermore, immunotherapy efficacy is affected by inflammatory and nutritional status of patients. To investigate whether dynamics of inflammatory and nutritional indexes were associated with prognosis, two hundred and twenty-three patients were analyzed retrospectively. The inflammatory indexes of interest were neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) while prognostic nutritional index (PNI) and the hemoglobin, albumin, lymphocyte and platelet (HALP) score were considered as nutritional indexes. Patients were divided into high and low groups or into 'increase' and 'decrease' groups based on pre-treatment cut-off values and index dynamics after six-week follow-up respectively. High pre-treatment PLR (OR =2.612) and increase in NLR during follow-up (OR =2.516) were significantly associated with lower objective response rates. Using multivariable analysis, high pre-treatment PLR (HR, 2.319) and increase in SII (HR, 1.731) predicted shorter progression-free survival, while high pre-treatment NLR (HR, 1.635), increase in NLR (HR, 1.663) and PLR (HR, 1.691) and decrease in PNI (HR, 0.611) predicted worse overall survival. The nomogram's c-index in inside validation was 0.718 (95% CI: 0.670-0.766). Our results indicated both nutritional and inflammatory indexes are associated with survival outcomes. Inflammatory indexes were additionally linked to treatment response. Index dynamics are better predictors than baseline values in predicting survival in advanced NSCLC patients receiving PD-1 inhibitor combined with chemotherapy as first-line. This article is protected by copyright. All rights reserved.

Background Low baseline prognostic nutritional index (PNI) scores are associated with poor survival for various malignancies; however, they vary based on the cohort and time resulting in inaccurate results. We determined the predictive value of the PNI score variations in addition to the baseline PNI scores for patients with advanced non-small cell lung cancer (NSCLC) who received programmed cell death protein 1 (PD-1) inhibitor. Methods We retrospectively analysed 115 patients with advanced NSCLC who received PD-1 inhibitor. The median follow-up period was 28 months. Patients were clustered into four groups based on the combined PNI scores (combination of baseline and variation of PNI scores): ΔPNI-L-L, ΔPNI-L-H, ΔPNI-H-L, and ΔPNI-H-H subgroups. For instance, if PNI scores of patients with high baseline PNI score increased from baseline to 6 weeks after treatment, they were included in the ΔPNI-H-H subgroup. Cox regression models were used to identify the factors associated with survival. Results The baseline PNI score was only related to the overall survival (OS) (P = .026), and not to the overall response rate (ORR) (P = .299) and progression-free survival (PFS) (P = .207). The ORR was associated with the combined PNI scores (P = .017). A multivariable Cox regression analysis confirmed that the combined PNI scores were independent factors for PFS (ΔPNI-L-H, 12 months, hazard ratio [HR] = 0.449, P = .009; ΔPNI-H-L, 14 months, HR = 0.500, P = .019; and ΔPNI-H-H, 17 months, HR = 0.390, P = .012; vs ΔPNI-L-L, 8 months) and OS (ΔPNI-L-H, 27 months, HR = 0.403, P = .019; ΔPNI-H-L, 28 months, HR = 0.369, P = .010; and ΔPNI-H-H, not reached, HR = 0.087, P = .002; vs ΔPNI-L-L, 15 months). Conclusions Patients with high baseline PNI and increased PNI score had the better survival outcome. On dynamic monitoring and comprehensive assessment, the combined PNI scores significantly enhanced the survival predictive ability of patients with NSCLC treated with PD-1 inhibitor.

Background Osimertinib resistance limits the treatment of epidermal growth factor receptor-(EGFR)-mutated non-small-cell lung carcinoma (NSCLC). The mechanisms of osimertinib resistance need to be elucidated to determine alternative treatment strategies. This study explores the role of M2 type tumor-associated macrophage (TAM)-derived exosomal MSTRG.292666.16 in osimertinib resistance, and its related competing endogenous RNA (ceRNA) mechanism. Methods M2 type TAMs were induced with 200 ng/mL phorbol 12-myristate 13-acetate, 20 ng/mL IL-4 and IL-13, and M2 type macrophage markers were measured by RT-qPCR. Next, the exosomes were isolated and characterized. Tumor formation in nude mice was conducted using H1975 cells under different treatment conditions. Small RNA sequencing was performed on exosomes derived from sensitive and resistant plasma, and ceRNA networks were constructed. Fluorescence in situ hybridization was used to observe the localization of MSTRG.292666.16, and a ceRNA network (MSTRG.292666.16-miR-6836-5p-MAPK8IP3) was selected for further validation. Results M2 type TAMs, and M2 type TAM-derived exosomes were successfully induced and isolated. Nude mice results showed that M2 type TAM-derived exosomes and MSTRG.292666.16 overexpression significantly increased tumor volume after administration of osimertinib for 4 weeks. M2 type TAMs were found in the resistant plasma, and MSTRG.292666.16 localized in the cytoplasm of H1975 cells. In addition, the genes in the ceRNA networks were significantly enriched in eight GO terms and seven KEGG pathways, including the MAPK signaling pathway. Subsequently, the levels of MSTRG.292666.16 and MAPK8IP3 significantly increased in both resistant plasma-derived exosomes and M2 type TAM-derived exosomes, while miR-6836-5p levels were significantly reduced. Finally, MSTRG.292666.16, miR-6836-5p, and MAPK8IP3 were part of the same network. Conclusions M2 type TAM-derived exosomes promoted osimertinib resistance in NSCLC by regulating the MSTRG.292666.16/miR-6386-5p/MAPK8IP3 axis.

Acquired resistance of osimertinib is encountered in clinic treatment of non-small cell lung cancer (NSCLC). However, the molecular mechanisms of osimertinib resistance are not fully revealed. This study aimed to investigate the roles of exosomes in delivering osimertinib resistance in NSCLC. Exosomes were successfully isolated. LncRNA sequencing identified a total of 123 differentially expressed lncRNAs, including 45 upregulated lncRNAs and 78 downregulated lncRNAs. The relative expression level of lncRNA MSTRG.292666.16 was significantly upregulated in osimertinib-resistant plasma, osimertinib-resistant H1975R cells and their derived exosomes, compared with those in osimertinib- sensitive plasma, H1975 cells and exosomes (P < 0.05). Besides, osimertinib-resistant exosomes could regulate gene expressions induced by osimertinib, including miRNA-21, miRNA-125b, TGFβ, ARF6 and c-Kit. Osimertinib-resistant exosomes could be taken up by osimertinib-sensitive H1975 cells and resulting in osimertinib-resistance in vivo. Knockdown of lncRNA MSTRG.292666.16 decreased osimertinib resistance of H1975R cells. Our results suggest that exosomal lncRNA MSTRG.292666.16 might be associated with osimertinib resistance in NSCLC.

Background: Hybrid capture-based next-generation sequencing of DNA has been widely applied in the detection of circulating tumor DNA (ctDNA). Various methods have been proposed for ctDNA detection, but low-allelic-fraction (AF) variants are still a great challenge. In addition, no panel-wide calling algorithm is available, which hiders the full usage of ctDNA based 'liquid biopsy'. Thus, we developed the VBCALAVD (Virtual Barcode-based Calling Algorithm for Low Allelic Variant Detection) in silico to overcome these limitations. Results: Based on the understanding of the nature of ctDNA fragmentation, a novel platform-independent virtual barcode strategy was established to eliminate random sequencing errors by clustering sequencing reads into virtual families. Stereotypical mutant-family-level background artifacts were polished by constructing AF distributions. Three additional robust fine-tuning filters were obtained to eliminate stochastic mutant-family-level noises. The performance of our algorithm was validated using cell-free DNA reference standard samples (cfDNA RSDs) and normal healthy cfDNA samples (cfDNA controls). For the RSDs with AFs of 0.1, 0.2, 0.5, 1 and 5%, the mean F1 scores were 0.43 (0.25~0.56), 0.77, 0.92, 0.926 (0.86~1.0) and 0.89 (0.75~1.0), respectively, which indicates that the proposed approach significantly outperforms the published algorithms. Among controls, no false positives were detected. Meanwhile, characteristics of mutant-family-level noise and quantitative determinants of divergence between mutant-family-level noises from controls and RSDs were clearly depicted. Conclusions: Due to its good performance in the detection of low-AF variants, our algorithm will greatly facilitate the noninvasive panel-wide detection of ctDNA in research and clinical settings. The whole pipeline is available at https://github.com/zhaodalv/VBCALAVD.

Introduction: Next-generation sequencing (NGS) and digital polymerase chain reaction (PCR) based platforms have been used to detect EGFR mutations in plasma circulating tumor DNA (ctDNA) with high accuracy. Generally, molecular testing is performed after histopathological analysis. However, many patients with suspected advanced nonsmall cell lung cancer are unable to undergo biopsy thus forgoing potential treatment with highly effective tyrosine kinase inhibitors (TKIs) in patients with sensitizing EGFR mutations. We examined the utility of ctDNA testing to detect EGFR mutations in patients' plasma, where tissue biopsy is not feasible. Methods: We conducted a single-center, prospective study of 30 Chinese patients with suspected advanced lung cancer, who were unable to undergo a biopsy for initial diagnosis due to comorbidities or poor performance status. Patients with plasma EGFR sensitizing mutations were treated with first-generation EGFR TKIs. Results: Twenty of 30 patients enrolled had sensitizing EGFR mutations in ctDNA and were started on EGFR TKIs. After a median follow-up of 12 months, median progression-free survival (PFS) was 10 months and median overall survival (OS) was not reached. The median OS for the 10 untreated patients was 3 months. Conclusions: In our study, patients with plasma EGFR mutations treated with TKIs showed disease control rate (DCR) and PFS similar to historical controls that were treated based on tissue testing. This is the first prospective study showing that ctDNA genotyping provides a feasible diagnostic approach for frail lung cancer patients who are unable to undergo biopsy, which subsequently leads to EGFR-targeted therapy, and improved outcomes in this subgroup of patients.

Background Hybrid capture-based next-generation sequencing of DNA has been widely applied in the detection of circulating tumor DNA (ctDNA). Various methods have been proposed for ctDNA detection, but low-allelic-fraction (AF) variants are still a great challenge. In addition, no panel-wide calling algorithm is available, which hiders the full usage of ctDNA based ‘liquid biopsy’. Thus, we developed the VBCALAVD (Virtual Barcode-based Calling Algorithm for Low Allelic Variant Detection) i n silico to overcome these limitations. Results Based on the understanding of the nature of ctDNA fragmentation, a novel platform-independent virtual barcode strategy was established to eliminate random sequencing errors by clustering sequencing reads into virtual families.Stereotypical mutant-family-level background artifacts were polished by constructing AF distributions. Three additional robust fine-tuning filters were obtained to eliminate stochastic mutant-family-level noises. The performance of our algorithm was validated using cell-free DNA reference standard samples (cfDNA RSDs) and normal healthy cfDNA samples (cfDNA controls). For the RSDs with AFs of 0.1%, 0.2%, 0.5%, 1% and 5%, the mean F1 scores were 0.43 (0.25~0.56), 0.77, 0.92, 0.926 (0.86~1.0) and 0.89 (0.75~1.0), respectively, which indicates that the proposed approach significantly outperforms the published algorithms. Among controls, no false positives were detected. Meanwhile, characteristics of mutant-family-level noise and quantitative determinants of divergence between mutant-family-level noises from controls and RSDs were clearly depicted. Conclusions Due to its good performance in the detection of low-AF variants, our algorithm will greatly facilitate the noninvasive panel-wide detection of ctDNA in research and clinical settings. The whole pipeline is available at https://github.com/zhaodalv/VBCALAVD.

Background and objective: Chemotherapy remains the basis of the treatment of lung cancer, and screening biomarkers with predictive value for chemotherapy is of great interest. We focused on status of genes methylation in NSCLC patients receiving pemetrexed- or gemcitabine-based chemotherapy. Patients and methods: Promoter methylation of Ras association domain family (RASSF1A) and short stature homeobox 2 (SHOX2) was examined in bronchoalveolar lavage (BAL) from 117 NSCLC patients treated with chemotherapy. Multivariate analysis was used to identify the predictive value of gene methylation. Progression-free survival (PFS) rather than overall survival (OS) was used as the clinical outcome to minimize the impact of chemotherapy on gene methylation. Results: The methylation of RASSF1A and SHOX2 was significantly associated with shorter PFS (RASSF1A: HR = 2.355, 95% CI: 1.533-3.617, P< 0.0001; SHOX2: HR = 2.123, 95% CI: 1.392-3.236, P= 0.0004). After adjusting for confounding factors, RASSF1A methylation was still a predictive factor for PFS (HR = 1.765, 95% CI: 1.064-2.928, P= 0.0278). In the pemetrexed group, unmethylated RASSF1A could be used to predict longer PFS (P= 0.0001), and no predictive value was found in the gemcitabine group. Conclusion: Unmethylated RASSF1A is a favorable prognostic indicator for patients receiving pemetrexed doublets. Because of the promoting effect of most chemotherapeutic drugs on gene methylation, unmethylated RASSF1A is not suitable as a predictor for gemcitabine doublets.