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Purpose: Although gefitinib prolonged the progression-free survival (PFS) of patients with non–small cell lung cancer (NSCLC), unpredictable resistance limited its clinical efficacy. Novel predictive biomarkers with explicit mechanisms are urgently needed. Experimental Design: A total of 282 patients with NSCLC with gefitinib treatment were randomly assigned in a 7:3 ratio to exploratory (n = 192) and validation (n = 90) cohorts. The candidate polymorphisms were selected with Haploview4.2 in Hapmap and genotyped by a MassARRAY system, and the feature variables were identified through Randomforest Survival analysis. Tanswell and clonogenic assays, base editing and cell-derived tumor xenograft model were performed to uncover the underlying mechanism. Results: We found that the germline missense polymorphism rs3742076 (A>G, S628P), located in transactivation domain of FOXM1, was associated with PFS in exploratory (median PFS: GG vs. GA&AA, 9.20 vs. 13.37 months, P = 0.00039, HR = 2.399) and validation (median PFS: GG vs. GA&AA, 8.13 vs. 13.80 months, P = 0.048, HR = 2.628) cohorts. We elucidated that rs3742076_G conferred resistance to gefitinib by increasing protein stability of FOXM1 and facilitating an aggressive phenotype in vitro and in vivo through activating wnt/β-catenin signaling pathway. Meanwhile, FOXM1 level was highly associated with prognosis in patients with EGFR-mutant NSCLC. Mechanistically, FOXM1 rs3742076_G upregulated wnt/β-catenin activity by directly binding to β-catenin in cytoplasm and promoting transcription of β-catenin in nucleus. Remarkably, inhibition of β-catenin markedly reversed rs3742076_G-induced gefitinib resistance and aggressive phenotypes. Conclusions: These findings characterized rs3742076_G as a gain-of-function polymorphism in mediating gefitinib resistance and tumor aggressiveness, and highlighted the variant as a predictive biomarker in guiding gefitinib treatment.

Purpose:Although gefitinib prolonged the progression-free survival (PFS) of patients with non–small cell lung cancer (NSCLC), unpredictable resistance limited its clinical efficacy. Novel predictive biomarkers with explicit mechanisms are urgently needed.Experimental Design:A total of 282 patients with NSCLC with gefitinib treatment were randomly assigned in a 7:3 ratio to exploratory (n = 192) and validation (n = 90) cohorts. The candidate polymorphisms were selected with Haploview4.2 in Hapmap and genotyped by a MassARRAY system, and the feature variables were identified through Randomforest Survival analysis. Tanswell and clonogenic assays, base editing and cell-derived tumor xenograft model were performed to uncover the underlying mechanism.Results:We found that the germline missense polymorphism rs3742076 (A>G, S628P), located in transactivation domain of FOXM1, was associated with PFS in exploratory (median PFS: GG vs. GA&AA, 9.20 vs. 13.37 months, P = 0.00039, HR = 2.399) and validation (median PFS: GG vs. GA&AA, 8.13 vs. 13.80 months, P = 0.048, HR = 2.628) cohorts. We elucidated that rs3742076_G conferred resistance to gefitinib by increasing protein stability of FOXM1 and facilitating an aggressive phenotype in vitro and in vivo through activating wnt/β-catenin signaling pathway. Meanwhile, FOXM1 level was highly associated with prognosis in patients with EGFR-mutant NSCLC. Mechanistically, FOXM1 rs3742076_G upregulated wnt/β-catenin activity by directly binding to β-catenin in cytoplasm and promoting transcription of β-catenin in nucleus. Remarkably, inhibition of β-catenin markedly reversed rs3742076_G-induced gefitinib resistance and aggressive phenotypes.Conclusions:These findings characterized rs3742076_G as a gain-of-function polymorphism in mediating gefitinib resistance and tumor aggressiveness, and highlighted the variant as a predictive biomarker in guiding gefitinib treatment.

Supplementary Figure from FOXM1 Variant Contributes to Gefitinib Resistance via Activating Wnt/β-Catenin Signal Pathway in Patients with Non–Small Cell Lung Cancer

Supplementary Table from FOXM1 Variant Contributes to Gefitinib Resistance via Activating Wnt/β-Catenin Signal Pathway in Patients with Non–Small Cell Lung Cancer

Aberrant DNA methylation plays a pivotal role in tumor development and metastasis, and is regarded as a valuable non-invasive cancer biomarker. However, the sensitive and accurate quantification of DNA methylation from clinical samples remains a challenge. Herein, we propose an easy-to-operate Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas system Assisted Methylation (CAM) approach for the sensitive detection of DNA methylation through the integration of rolling circle amplification and CRISPR-Cas12a-assisted cascade amplification. Briefly, bisulfite was employed to prepare the clinical samples so that the methylated DNA sequences trigger the subsequent triple signal amplifications, whilst the normal counterparts do not. The triple signal amplification procedure consists of methylated DNA sequence-based rolling circle amplification for a preliminary signal enhancement, a nicking enzyme-initiated target cleavage for a secondary amplification, and CRISPR-Cas12a enzyme-mediated trans-cleavage for a tertiary signal enhancement. This proposed approach reveals high sensitivity, which can even distinguish as low as 0.01% methylation levels from mixtures, paving the way towards the acceleration of methylation-based cancer diagnostics and management.

Objective. Type C fracture is a complete intra-articular fracture, and the mainstay of treatment remains open reduction and internal fixation. The purpose of the study is to observe the clinical effect of an anterior ankle C approach (ankle-C) combined with minimal invasive plate osteosystems (MIPO) for tibial pilon fractures (AO/OTA 43C, combined with fibula fractures). Methods. A retrospective comparative analysis was performed on the clinical data of 33 patients with C-type pilon fractures (combined fibula fractures) admitted to our department from July 2018 to July 2021, including 12 cases treated with ankle-C (a-C) approach and 21 cases with conventional approach (including combined approach). All patients were followed up for over 6 months. Visual Analogue Scale (VAS), AOFAS Ankle-Hindfoot Scale (AOFAS-AHS), wound healing time, fracture healing time, and complications were used to evaluate the clinical efficacy. Results. The scores of VAS and AOFAS in the a-C group scored better than the conventional group ( P < 0.05 ), especially in the extent of limited range of motion (LROM) of ankle dorsiflexion-plantarflexion in 1 month after operation and at the last follow-up ( P < 0.01 ). Bone healing was achieved in both groups 6 months after operation, with no implant exposure or infection. Among them, 4 cases in the conventional approach group had wound healing time exceeding 2 weeks. Conclusions. For type C pilon fractures (combined with fibula fractures), ankle-C approach combined with MIPO technique has certain advantages in ankle function recovery and soft tissue repair, which provides an alternative for the treatment of type C pilon fractures.

Drug-induced liver injury (DILI) remains a critical clinical issue and has been a treatment challenge today as it was in the past. However, the traditional biomarkers or indicators are insufficient to predict the risks and outcome of patients with DILI due to its poor specificity and sensitivity. Recently, the development of high-throughput technologies, especially omics and multiomics has sparked growing interests in identification of novel clinical DILI biomarkers, many of which also provide a mechanistic insight. Accordingly, in this minireview, we summarize recent advances in novel clinical biomarkers for DILI prediction, diagnosis, and prognosis and highlight the limitations or challenges involved in biomarker discovery or its clinical translation. Although huge work has been done, most reported biomarkers lack comprehensive information and more specific DILI biomarkers are still needed to complement the traditional biomarkers such as alanine aminotransferase (ALT) or aspartate transaminase (AST) in clinical decision-making. SIGNIFICANCE STATEMENT: This current review outlines an overview of novel clinical biomarkers for drug-induced liver injury (DILI) identified in clinical retrospective or prospective clinical analysis. Many of these biomarkers provide a mechanistic insight and are promising to complement the traditional DILI biomarkers. This work also highlights the limitations or challenges involved in biomarker discovery or its clinical translation.

Highlights • BAIAP2L2 participated in the development of human osteosarcoma. • BAI1 activity was altered during the development, proliferation and apoptosis of tumor cells. • Expression of BAIAP2L2 and Ki67 was greatly down-regulated by knockdown of BAIAP2L2., Background Osteosarcoma is the most common bone cancer that significantly affects the quality of life of patients. Studies have shown that overexpression of BAIAP2L2 elevates the proliferation and growth of some types of cancer cells. However, the role of BAIAP2L2 in osteosarcoma is unclear. This study aimed to investigate the functions of BAIAP2L2 in the development of osteosarcoma. Methods We used immunohistochemical and Western blot analysis to determine the expression levels of endogenic BAIAP2L2 in osteosarcoma cells. Cell counting kit-8 assay and colony formation assay were performed to investigate cell proliferation of tumor cells. Transwell assay was performed to detect cell migration. Flow cytometry assay was used to analyze cell apoptosis. The role of BAIAP2L2 in tumor growth was further explored in vivo. Results We found that BAIAP2L2 was significantly upregulated in human osteosarcoma, and inhibition of BAIAP2L2 suppressed the proliferation of osteosarcoma cells. In addition, down-regulation of BAIAP2L2 could lead to osteosarcoma cancer cell apoptosis, inhibit cell migration and invasion, and induce the inactivation of the Wnt/β-catenin pathway. In addition, down-regulation of BAIAP2L2 inhibited tumor growth in vivo. Conclusion In conclusion, down-regulation of BAIAP2L2 inhibited the proliferation, migration, and invasion of osteosarcoma associated with the Wnt/β-catenin pathway.

e21046 Background: Gefitinib-induced diarrhea can be severe, if not properly handled, and can result in severe dose reductions and treatment interruptions or discontinuation. However, the mechanism of gefitinib-induced diarrhea remains unclear. STAT6 promotes disruption of epithelial tight junction integrity, intestinal inflammation and allergic disorders in intestine. Therefore, we explored the correlation between variations in STAT6 and gefitinib-induced diarrhea in advanced non-small cell lung cancer (NSCLC) patients. Methods: A total of 160 advanced NSCLC patients carrying EGFR mutations were enrolled. 8 tag single nucleotide polymorphisms (SNP) in STAT6, including rs10876963, rs167769, rs3122929, rs3024975, rs841718, rs324013, rs324015 and rs703817, were selected by Heploview 4.2 and sequenced by Agena MassARRAY System. The associations between tag SNPs of STAT6 and diarrhea were analyzed by Chi square test and multivariate logistic regression. This study was approved by the ethical committee of Sun Yat-Sen University Cancer Center. Results: 71 patients (44.4%) suffered at least grade 1 gefitinib-induced diarrhea. We found rs167769 was associated with gefitinib- induced diarrhea in NSCLC patients. STAT6 rs167769 TT carriers were all suffering from gefitinib-induced diarrhea (OR = 2.4*1010, p = 0.999). Patients with STAT6 rs167769 TT have higher risk of developing severe (grade ≥ 2) diarrhea than those with STAT6 rs167769 CC/CT. Conclusions: STAT6 rs167769 is a predictive biomarker for gefitinib-induced diarrhea and the analysis of polymorphisms of STAT6 rs167769 might be beneficial to optimize gefitinib treatment. Further studies are needed to clarify the underlying mechanisms. Clinical trial information: NCT01994057.

e21041 Background: Gefitinib is first-line therapy for patients with EGFR-activating mutation in non-small cell lung cancer (NSCLC). Meanwhile, ̃30% patients were progression within 12 months even harboring EGFR-activating mutation. Furthermore, integrative scoring models for prediction of gefitinib outcomes are still lacking. Variations in genes of DNA repair and cell cycle pathway may have potential impacts on proliferation, migration and invasion of tumor cells. Therefore, we investigated a series of single nucleotide polymorphisms (SNP) in DNA repair and cell cycle genes based on an efficient algorithm machine learning algorithm for establishing an integrative scoring system for survival prediction following gefitinib therapy in NSCLC patients. Methods: A total of 282 patients with activating EGFR mutations were enrolled and divided into train cohort and test cohort, randomly. 125 SNPs in 47 candidate genes were selected by Heploview 4.2 and sequenced by Agena MassARRAY System. Predictive features were selected by randomForestSRC, an efficient algorithm machine learning algorithm to analyze survival data, for PFS following gefitinib therapy. The top candidate variables were presented into COX regression models with hazard ratio as weight for each predictor (HR = 1-1.49 = 1; HR = 1.5-2.49 = 2; HR = 2.5-3.49 = 3), providing p < 0.1. This study was approved by the ethical committee of Sun Yat-Sen University Cancer Center. Results: The progression risk predictive model was established by random forest survival and validated by COX regression analysis, included XRCC1 rs3213263(CT vs CC, RR = 1.997, 95%CI = 1.314-3.036, p = 0.001), FOXO3 rs75544369(GA vs GG, RR = 1.942, 95%CI = 1.139-3.309, p = 0.012), FOXM1 rs2302257(CC vs GG, RR = 2.889, 95%CI = 1.477-5.691, p = 0.002) and ERCC1 rs10408989(TT vs GT, RR = 1.735, 95%CI = 1.152-2.613, p = 0.008; GG vs GT, RR = 3.788, 95%CI = 1.625-8.832, p = 0.002). The progression risk score ranged from 0-10. 49 patients (25.52%) and 20 patients (22.22%) were scored 0, 18(9.38%) and 10(11.11%) patients were scored more than 5 in train cohort and test cohort, respectively. According to the risk score of patients, we divided the patients into four groups, the median PFS were 26.23(95%CI:14.23-35.37), 16.80(95%CI:12.87-23.60), 11.13(95%CI:8.87-16.70) and 6.25 (95% CI:4.43-11.67) months for 0, 2, 3&4 and ≥5 group (p < 0.0001) in the train cohort. Meanwhile, the median PFS were 18.80(95%CI:11.80-64.53),13.60(95%CI:9.17-27.33), 13.47(95%CI:9.83-18.40), 13.47(95%CI:9.83-18.40) and 7.40(95%CI:3.33- NA) months for 0, 2, 3&4 and ≥5 group in validation cohort (p = 0.0017). Conclusions: The risk score system is a simple tool for risk stratification in patients undergoing gefitinib. Widespread application of the score system will require further independent validation.