Identification and validation of key genes in gastric cancer: insights from in silico analysis, clinical samples, and functional assays.

INTRODUCTION: The underlying mechanisms of gastric cancer (GC) remain unknown. Therefore, in this study, we employed a comprehensive approach, combining computational and experimental methods, to identify potential key genes and unveil the underlying pathogenesis and prognosis of GC. METHODS: Gene expression profiles from GEO databases (GSE118916, GSE79973, and GSE29272) were analyzed to identify DEGs between GC and normal tissues. A PPI network was constructed using STRING and Cytoscape, followed by hub gene identification with CytoHubba. Investigations included expression and promoter methylation analysis, survival modeling, mutational and miRNA analysis, gene enrichment, drug prediction, and in vitro assays for cellular behaviors. RESULTS: A total of 83 DEGs were identified in the three datasets, comprising 41 up-regulated genes and 42 down-regulated genes. Utilizing the degree and MCC methods, we identified four hub genes that were hypomethylated and up-regulated: COL1A1, COL1A2, COL3A1, and FN1. Subsequent validation of their expression and promoter methylation on clinical GC samples through targeted bisulfite sequencing and RT-qPCR analysis further confirmed the hypomethylation and overexpression of these genes in local GC patients. Furthermore, it was observed that these hub genes regulate tumor proliferation and metastasis in in vivo and exhibited mutations in GC patients. CONCLUSION: We found four potential diagnostic and prognostic biomarkers, including COL1A1, COL1A2, COL3A1, and FN1 that may be involved in the occurrence and progression of GC.

Deep Learning for Automatic Gross Tumor Volumes Contouring in Esophageal Cancer Based on Contrast-Enhanced Computed Tomography Images: A Multi-Institutional Study.

PURPOSE: To develop and externally validate an automatic artificial intelligence (AI) tool for delineating gross tumor volume (GTV) in patients with esophageal squamous cell carcinoma (ESCC), which can assist in neo-adjuvant or radical radiation therapy treatment planning. METHODS AND MATERIALS: In this multi-institutional study, contrast-enhanced CT images from 580 eligible ESCC patients were retrospectively collected. The GTV contours delineated by 2 experts via consensus were used as ground truth. A 3-dimensional deep learning model was developed for GTV contouring in the training cohort and internally and externally validated in 3 validation cohorts. The AI tool was compared against 12 board-certified experts in 25 patients randomly selected from the external validation cohort to evaluate its assistance in improving contouring performance and reducing variation. Contouring performance was measured using dice similarity coefficient (DSC) and average surface distance. Additionally, our previously established radiomics model for predicting pathologic complete response was used to compare AI-generated and ground truth contours, to assess the potential of the AI contouring tool in radiomics analysis. RESULTS: The AI tool demonstrated good GTV contouring performance in multicenter validation cohorts, with median DSC values of 0.865, 0.876, and 0.866 and median average surface distance values of 0.939, 0.789, and 0.875 mm, respectively. Furthermore, the AI tool significantly improved contouring performance for half of 12 board-certified experts (DSC values, 0.794-0.835 vs 0.856-0.881, P = .003-0.048), reduced the intra- and interobserver variations by 37.4% and 55.2%, respectively, and saved contouring time by 77.6%. In the radiomics analysis, 88.7% of radiomic features from ground truth and AI-generated contours demonstrated stable reproducibility, and similar pathologic complete response prediction performance for these contours (P = .430) was observed. CONCLUSIONS: Our AI contouring tool can improve GTV contouring performance and facilitate radiomics analysis in ESCC patients, which indicates its potential for GTV contouring during radiation therapy treatment planning and radiomics studies.

A pilot study of anlotinib with third-generation epidermal growth factor receptor tyrosine kinase inhibitors in untreated EGFR-mutant patients with advanced non-small cell lung cancer.

Background: In recent years, osimertinib, a third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), has been recommended as a first-line treatment for EGFR-mutant advanced non-small cell lung cancer (NSCLC). A phase III study (AENEAS) to assess the efficacy and safety of aumolertinib, another third-generation EGFR-TKI, vs. gefitinib as a first-line treatment in patients with locally advanced or metastatic NSCLC harboring EGFR mutations has also achieved positive results. Despite the improvements in progression-free survival (PFS) and overall survival (OS) of third- vs. first-generation EGFR-TKIs, combined treatment strategies to postpone drug resistance and further prolong survival benefits remain to be explored. Methods: We conducted a nonrandomized phase II trial (ChiCTR2000035140) of an oral multitarget antiangiogenic TKI (anlotinib) with third-generation EGFR-TKIs (osimertinib or aumolertinib) in untreated patients with EGFR mutation and advanced NSCLC. Anlotinib and the third-generation EGFR-TKIs were orally administrated (anlotinib at a dose of 12 mg once every other day and osimertinib at 80 mg once daily or aumolertinib at 110 mg once daily). The primary end point of the study was the objective response rate (ORR). Secondary endpoints included the disease control rate (DCR), OS, PFS, and safety of the combined treatment. Results: Enrollment was ceased due to treatment-related adverse events (trAEs) after 11 of 35 planned patients were treated. Among these 11 patients, two were lost to follow-up, and the treatment of five of the remaining nine patients was discontinued due to trAEs, including stomachache, rash, hyponatremia, pulmonary embolism, and interstitial pneumonia. AEs of grade 3 or worse were observed in five patients, but no treatment-related death occurred in these patients. Conclusions: Combining anlotinib and third-generation EGFR-TKIs in untreated EGFR-mutant patients with advanced NSCLC demonstrated significantly increased toxicity, suggesting that the combined treatment strategy was an inappropriate therapeutic choice in this setting.

Concurrent chemoradiotherapy with or without neoadjuvant chemotherapy in pediatric patients with stage III-IVa nasopharyngeal carcinoma: a real-world propensity score-matched cohort study.

OBJECTIVES: To compare neoadjuvant chemotherapy (NAC) plus concurrent chemoradiotherapy (CCRT) to CCRT alone in children and adolescents (age ≤ 18 years) with locoregionally advanced nasopharyngeal carcinoma (CA-LANPC, stage III-IVA). MATERIALS AND METHODS: 195 CA-LANPC patients who were treated through CCRT with or without NAC between 2008 and 2018 were enrolled in this study. A matched cohort composed of CCRT patients and NAC-CCRT patients was generated by propensity score matching (PSM) at a 1:2 ratio. Survival outcomes and toxicities were compared between the CCRT group and NAC-CCRT group. RESULTS: Of the 195 patients, 158 (81%) received NAC plus CCRT, and 37 (19%) received CCRT alone. The NAC-CCRT group had higher EBV DNA levels (≥ 4000 copy/mL), more advanced TNM stage (stage IV disease), and lower incidence of a high radiation dose (> 6600 cGy) than the CCRT group. To avoid bias in treatment selection within retrospectively analysis, 34 patients from the CCRT group were matched with 68 patients from the NAC-CCRT group. In the matched cohort, the 5-year DMFS rate was 94.0% in the NAC-CCRT group versus 82.4% in the CCRT group, with marginal statistical significance (HR = 0.31; 95%CI 0.09-1.10; P = 0.055). During treatment, the accumulate incidence of severe acute toxicities (65.8% vs 45.9%; P = 0.037) in the NAC-CCRT group was higher than the CCRT group. However, the CCRT group had significantly higher accumulate incidence of severe late toxicities (30.3% vs 16.8%; P = 0.041) than the NAC-CCRT group. CONCLUSIONS: Addition of NAC to CCRT tended to improve long-term DMFS in CA-LANPC patients with acceptable toxicity. However, relative randomized clinical trial is still needed in the future.

Targeting the KRT16-vimentin axis for metastasis in lung cancer.

Lung cancer is the most diagnosed malignant cancer and the leading cause of cancer-related deaths worldwide, with advanced stage and metastasis being a major issue. The mechanism leading to metastasis is not yet understood. Here, we found that KRT16 is upregulated in metastatic lung cancer tissues and correlated with poor overall survival. Knockdown of KRT16 inhibits metastasis of lung cancer both in vitro and in vivo. Mechanistically, KRT16 interacts with vimentin, and depletion of KRT16 leads to downregulation of vimentin. KRT16 acquired its oncogenic ability by stabilizing vimentin, and vimentin is required for KRT16-driven metastasis. FBXO21 mediates the polyubiquitination and degradation of KRT16, and vimentin inhibits KRT16 ubiquitination and degradation by impairing its interaction with FBXO21. Significantly, IL-15 inhibits metastasis of lung cancer in a mouse model through upregulation of FBXO21, and the level of IL-15 in circulating serum was significantly higher in nonmetastatic lung cancer patients than in metastatic patients. Our findings indicate that targeting the FBXO21/KRT16/vimentin axis may benefit lung cancer patients with metastasis.

Simultaneous Quantitation of Anlotinib and Osimertinib by Isotope-Labeled UHPLC-MS/MS in Human Plasma: Application in NSCLC Patients.

Anlotinib and osimertinib are a class of tyrosine kinase inhibitors for the treatment of malignant tumor. The combination of anlotinib and osimertinib is currently used for treating non-small cell lung cancer (NSCLC) patients. This study aimed to develop a simple and rapid isotope-labeled UHPLC-MS/MS method for the simultaneous determination of anlotinib and osimertinib in human plasma. The analytes were extracted by protein precipitation with acetonitrile and were then separated on a Shim-pack GIST C18 column. The detection was performed on Shimadzu 8050 triple quadruple mass spectrometer in the positive electrospray ionization mode with multiple reaction monitoring. The precursor-to-product ion transitions were m/z 408.10→ 339.75, 500.25→ 72.20 and 413.50 â†’ 344.50 for anlotinib, osimertinib and D5-anlotinib, respectively. Validation is based on US Food and Drug Administration guidelines. The linearity ranges were 0.5-100 ng/mL for anlotinib and were 1-500 ng/mL for osimertinib with the correlation coefficients (r  2) ≥ 0.99. Accuracy and precision, matrix effect, extraction recovery and stability of anlotinib and osimertinib were acceptable after validation. The UHPLC-MS/MS method was successfully validated and was applied to monitor the concentration of anlotinib and osimertinib in NSCLC patients.

Application of Dynamic 18F-FDG PET/CT for Distinguishing Intrapulmonary Metastases from Synchronous Multiple Primary Lung Cancer.

It has been a big challenge to distinguish synchronous multiple primary lung cancer (sMPLC) from primary lung cancer with intrapulmonary metastases (IPM). We aimed to assess the clinical application of dynamic 18F-FDG PET/CT in patients with multiple lung cancer nodules. We enrolled patients with multiple pulmonary nodules who had undergone dynamic 18F-FDG PET/CT and divided them into sMPLC and IPM groups based on comprehensive features. The SUVmax, fitted K i value based on dynamic scanning, and corresponding maximum diameter (D max) from the two largest tumors were determined in each patient. We determined the absolute between-tumor difference of SUVmax/D max and K i /D max (ΔSUVmax/D max; ΔK i /D max) and assessed the between-group differences. Further, the diagnostic accuracy was evaluated by ROC analysis and the correlation between ΔSUVmax/D max and ΔK i /Dmax from all groups was determined. There was no significant difference for ΔSUVmax/D max between the IPM and sMPLC groups, while the IPM group had a significantly higher ΔK i /Dmax than the sMPLC group. The AUC of ΔK i /D max for differentiating sMPLC from IPM was 0.80 (cut-off value of K i = 0.0059, sensitivity 79%, specificity 75%, p < 0.001). There was a good correlation (Pearson r = 0.91, 95% CI: 0.79-0.96, p < 0.0001) between ΔSUVmax/D max and ΔK i /D max in the IPM group but not in the sMPLC group (Pearson r = 0.45, p > 0.05). Dynamic 18F-FDG PET/CT could be a useful tool for distinguishing sMPLC from IPM. K i calculation based on Patlak graphic analysis could be more sensitive than SUVmax in discriminating IPM from sMPLC in patients with multiple lung cancer nodules.

Safety and efficacy of nivolumab plus recombinant human endostatin in previously treated advanced non-small-cell lung cancer.

Background: Evidence of the efficacy of immune checkpoint inhibitors (ICIs) plus antiangiogenic drugs in previously treated patients with advanced non-small-cell lung cancer (NSCLC) is still insufficient, so we investigated the safety and efficacy of nivolumab plus recombinant human (rh)-endostatin in such patients. Methods: Patients without epithelial growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) targetable mutations in advanced NSCLC who did not respond to previous treatment were enrolled. Eligible patients received nivolumab (3 mg/kg, i.v. drip, day 1) every 2 weeks and rh-endostatin (210 mg, continuous i.v. infusion for 168 h) every 4 weeks until disease progression or discontinuation. The primary endpoint was the objective response rate (ORR). The secondary endpoints included disease control rate (DCR), duration of response (DOR), clinical benefit response rate (CBR), progression-free survival (PFS), overall survival (OS) and safety. Results: A total of 34 patients received a median of 4 cycles of therapy. In all, 14 patients achieved confirmed partial response (PR) with an ORR of 41.2% [14/34; 95% confidence interval (CI): 23.7-58.6%], DCR of 64.7% (22/34; 95% CI: 47.8-81.6%), CBR of 44.1% (95% CI: 26.5-61.7%), and a DOR of 6.9 (95% CI: 4.4-9.4) months. Median follow-up was 12.2 (range, 2.3-18.1) months. Median PFS (mPFS) was 6.8 (95% CI: 1.1-12.1) months, median OS (mOS) was 17.1 (95% CI: 6.6-27.6) months, and 12-month survival rate of 64.4% (95% CI: 46.2-82.6%). In all, 18 (18/34, 52.9%) patients experienced at least one treatment-related adverse event (TRAE), and Grade 3 TRAEs occurred in 4 (4/34, 11.8%) of them. Conclusions: This study is first to assess nivolumab plus rh-endostatin in previously treated patients with advanced NSCLC. In view of its favorable efficacy and safety profile, this combination represents a promising treatment regimen in this patient population.

Transcription factor CDX2 up-regulates proto-oncogenic miR-744 via a promoter activation mechanism in non-small-cell lung cancer.

BACKGROUND: The role of caudal-related homeobox 2 (CDX2) in the pathogenesis of non-small cell lung cancer (NSCLC) is unclear. The purpose of this study was to investigate the mRNA (message RNA) expression of CDX2 in NSCLC, and to determine its relationship with miR-744 (microRNA744) and its potential as a biomarker of NSCLC. METHODS: MiR-744 is overexpressed in A549, H460, and H1299 cell lines. Real-time quantitative polymerase chain reaction (qRT-PCR) was used to detect the mRNA expression. A chromatin immunoprecipitation (ChIP) essay was performed to determine the CDX2 binding sites. We then conducted a luciferase reporter essay to analyze interaction between MiR-744 and 3'UTRs (the 3' untranslated sequences). The migration and Boyden chamber method were used to study cell mobility. RESULTS: In this study, we found that ectopic CDX2 increased the expression of miR-744, while the attenuation of CDX2 reduced the expression of miR-744 by qRT-PCR. Chromatin immunoprecipitation experiments confirmed that CDX2 directly binds to the promoter of miR-744. The luciferase reporter assay further verified the binding sites of -347 to -358 bp in the most likely promoter like sequence of miR-744. CDX2-induced up-regulation of miR-744 can significantly promote the migration and invasion of NSCLC cells, while overexpression CDX2 is sufficient to rescue the migration and invasion capacity of these cells following knockdown of miR-744. CONCLUSIONS: In summary, our results confirmed for the first time the regulatory mechanism of CDX2 on miR-744 transcription and provided a potential mechanism for CDX2 as an oncogene in lung cancer.

Clinical observation of pulmonary lymphoepithelioma-like carcinoma.

BACKGROUND: Lymphoepithelioma-like carcinoma (LELC) of the lung is a rare type of non-small cell lung cancer (NSCLC), and researches of it are still not enough. METHODS: In this study, we retrospectively analyzed 36 patients with LELC diagnosed in the Fifth Affiliated Hospital of Sun Yat-sen University and Zhaoqing First People's Hospital from January 2014 to June 2021, to investigate the clinical manifestations, tumor markers, treatment, and prognosis of LELC. Clinical data including age, gender, smoking history, family history of cancers, Epstein-Barr virus (EBV) encoding RNA (EBER) status, gene mutations, programmed death-ligand 1 (PD-L1) expression, treatment, and prognosis. RESULTS: There was a total of 36 participants in this study, 16 males and 20 females, the median age was 57 years (37-76 years). A total of 22 cases (61.1%) were advanced (stage III and IV), and EBER was 94.4% positive. Most patients were treated with surgery, platinum chemotherapy, or radiotherapy. At the time of 31 June 2021, 33 participants had survived, and the longest survival time was 72 months. Lung LELC was more common in old participants (≥59 years) and was not associated with smoking history. Expression of PD-L1 was positive in the majority (27 cases, 75%) and participants with positive PD-L1 expression tended to have longer progression-free survival (PFS) and overall survival (OS) time than those with negative PD-L1 expression. CONCLUSIONS: Pulmonary LELC usually occurs in non-smoking patients and is associated with EBV infection. Common treatments for tumors include multimodal therapy. The expression of PD-1 may be related to the prognosis of LELC, but more studies are needed to support further optimization of the treatment of LELC.