Prediction of antimicrobial resistance in Klebsiella pneumoniae using genomic and metagenomic next-generation sequencing data.

OBJECTIVES: Klebsiella pneumoniae is a significant pathogen with increasing resistance and high mortality rates. Conventional antibiotic susceptibility testing methods are time-consuming. Next-generation sequencing has shown promise for predicting antimicrobial resistance (AMR). This study aims to develop prediction models using whole-genome sequencing data and assess their feasibility with metagenomic next-generation sequencing data from clinical samples. METHODS: On the basis of 4170 K. pneumoniae genomes, the main genetic characteristics associated with AMR were identified using a LASSO regression model. Consequently, the prediction model was established, validated and optimized using clinical isolate read simulation sequences. To evaluate the efficacy of the model, clinical specimens were collected. RESULTS: Four predictive models for amikacin, ciprofloxacin, levofloxacin, and piperacillin/tazobactam, initially had positive predictive values (PPVs) of 92%, 98%, 99%, 94%, respectively, when they were originally constructed. When applied to clinical specimens, their PPVs were 96%, 96%, 95%, and 100%, respectively. Meanwhile, there were negative predictive values (NPVs) of 100% for ciprofloxacin and levofloxacin, and 'not applicable' (NA) for amikacin and piperacillin/tazobactam. Our method achieved antibacterial phenotype classification accuracy rates of 95.92% for amikacin, 96.15% for ciprofloxacin, 95.31% for levofloxacin and 100% for piperacillin/tazobactam. The sequence-based prediction antibiotic susceptibility testing (AST) reported results in an average time of 19.5 h, compared with the 67.9 h needed for culture-based AST, resulting in a significant reduction of 48.4 h. CONCLUSIONS: These preliminary results demonstrated that the performance of prediction model for a clinically significant antimicrobial-species pair was comparable to that of phenotypic methods, thereby encouraging the expansion of sequence-based susceptibility prediction and its clinical validation and application.

High utility of bronchoalveolar lavage fluid metagenomic next-generation sequencing approach for etiological diagnosis of pneumonia.

BACKGROUND: For patients with pneumonia, the rapid detection of pathogens is still a major global problem in clinical practice because traditional diagnostic techniques for infection are time-consuming and insensitive. Metagenomic next-generation sequencing (mNGS) is a novel technique that has the potential to improve pathogen diagnosis. This study aimed to investigate the microbiological diagnostic ability of mNGS compared with conventional culture and to determine the optimal time to test patients for pneumonia. METHODS: A prospective study using data from June 2020 to June 2021 was performed at a tertiary teaching hospital in China. We included 56 patients from all adult patients with a clinical diagnosis of pneumonia. Blood and bronchoalveolar lavage fluid (BALF) samples were taken for simultaneous mNGS and conventional culture testing. RESULTS: All 56 patients underwent both conventional culture and mNGS. Of these patients, 37 were diagnosed with severe pneumonia and 17 were diagnosed with non-severe pneumonia. The top three pathogenic bacteria detected by mNGS were Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. Enterococcus faecium was detected more frequently in the non-severe pneumonia group (4 vs. 0, p < 0.05). The findings revealed that the detection rate of mNGS (84%) was superior to that of conventional culture methods (48%). Notably, the percentage of mNGS-positive BALF samples (46/56, 82.14%) was significantly greater than that of blood samples (27/56, 48.21%). The etiological comparison demonstrated that mNGS-positive samples, which received clinical approval, tended to be associated with a more normalized temperature, lower PCO2 levels, and a higher SOFA score than mNGS-negative samples (p = 0.022, p = 0.0.028, and p = 0.038, respectively). CONCLUSIONS: In this study, we discovered that the etiology of lung infections frequently involves multiple pathogens. The use of mNGS in BALF is instrumental for detecting nonviral pathogens associated with lung infections. Although the rate of positive blood NGS results is significantly influenced by various clinical factors, for patients suspected of having viral, Legionella, or tsutsugamushi infections, plasma mNGS could serve as a complementary diagnostic tool.

Application of metagenomic next-generation sequencing in the clinical diagnosis of infectious diseases after allo-HSCT: a single-center analysis.

BACKGROUND: We investigated the value of metagenomic next-generation sequencing (mNGS) in diagnosing infectious diseases in patients receiving allogeneic hematopoietic stem cell transplantation (allo-HSCT). METHODS: Fifty-four patients who had fever following allo-HSCT from October 2019 to February 2022 were enrolled. Conventional microbiological tests (CMTs) and mNGS, along with imaging and clinical manifestations, were used to diagnose infection following allo-HSCT. The clinical diagnostic value of mNGS was evaluated. RESULTS: A total of 61 mNGS tests were performed, resulting in the diagnosis of 46 cases of infectious diseases. Among these cases, there were 22 cases of viral infection, 13 cases of fungal infection, and 11 cases of bacterial infection. Moreover, 27 cases (58.7%) were classified as bloodstream infections, 15 (32.6%) as respiratory infections, 2 (4.3%) as digestive system infections, and 2 (4.3%) as central nervous system infections. Additionally, there were 8 cases with non-infectious diseases (8/54, 14.81%), including 2 cases of interstitial pneumonia, 2 cases of bronchiolitis obliterans, 2 cases of engraftment syndrome, and 2 cases of acute graft-versus-host disease. The positive detection rates of mNGS and CMT were 88.9% and 33.3%, respectively, with significant differences (P < 0.001). The sensitivity of mNGS was 97.82%, the specificity was 25%, the positive predictive value was 93.75%, and the negative predictive value was 50%. Following treatment, 51 patients showed improvement, and 3 cases succumbed to multidrug-resistant bacterial infections. CONCLUSIONS: mNGS plays an important role in the early clinical diagnosis of infectious diseases after allo-HSCT, which is not affected by immunosuppression status, empiric antibiotic therapy, and multi-microbial mixed infection.

Direct prediction of carbapenem resistance in Pseudomonas aeruginosa by whole genome sequencing and metagenomic sequencing.

Carbapenem resistance is a major concern in the management of antibiotic-resistant Pseudomonas aeruginosa infections. The direct prediction of carbapenem-resistant phenotype from genotype in P. aeruginosa isolates and clinical samples would promote timely antibiotic therapy. The complex carbapenem resistance mechanism and the high prevalence of variant-driven carbapenem resistance in P. aeruginosa make it challenging to predict the carbapenem-resistant phenotype through the genotype. In this study, using whole genome sequencing (WGS) data of 1,622 P. aeruginosa isolates followed by machine learning, we screened 16 and 31 key gene features associated with imipenem (IPM) and meropenem (MEM) resistance in P. aeruginosa, including oprD(HIGH), and constructed the resistance prediction models. The areas under the curves of the IPM and MEM resistance prediction models were 0.906 and 0.925, respectively. For the direct prediction of carbapenem resistance in P. aeruginosa from clinical samples by the key gene features selected and prediction models constructed, 72 P. aeruginosa-positive sputum samples were collected and sequenced by metagenomic sequencing (MGS) based on next-generation sequencing (NGS) or Oxford Nanopore Technology (ONT). The prediction applicability of MGS based on NGS outperformed that of MGS based on ONT. In 72 P. aeruginosa-positive sputum samples, 65.0% (26/40) of IPM-insensitive and 63.2% (24/38) of MEM-insensitive P. aeruginosa were directly predicted by NGS-based MGS with positive predictive values of 0.897 and 0.889, respectively. By the direct detection of the key gene features associated with carbapenem resistance of P. aeruginosa, the carbapenem resistance of P. aeruginosa could be directly predicted from cultured isolates by WGS or from clinical samples by NGS-based MGS, which could assist the timely treatment and surveillance of carbapenem-resistant P. aeruginosa.

Novel Clinical mNGS-Based Machine Learning Model for Rapid Antimicrobial Susceptibility Testing of Acinetobacter baumannii.

Multidrug-resistant (MDR) bacteria are important public health problems. Antibiotic susceptibility testing (AST) currently uses time-consuming culture-based procedures, which cause treatment delays and increased mortality. We developed a machine learning model using Acinetobacter baumannii as an example to explore a fast AST approach using metagenomic next-generation sequencing (mNGS) data. The key genetic characteristics associated with antimicrobial resistance (AMR) were selected through a least absolute shrinkage and selection operator (LASSO) regression model based on 1,942 A. baumannii genomes. The mNGS-AST prediction model was accordingly established, validated, and optimized using read simulation sequences of clinical isolates. Clinical specimens were collected to evaluate the performance of the model retrospectively and prospectively. We identified 20, 31, 24, and 3 AMR signatures of A. baumannii for imipenem, ceftazidime, cefepime, and ciprofloxacin, respectively. Four mNGS-AST models had a positive predictive value (PPV) greater than 0.97 for 230 retrospective samples, with negative predictive values (NPVs) of 100% (imipenem), 86.67% (ceftazidime), 86.67% (cefepime), and 90.91% (ciprofloxacin). Our method classified antibacterial phenotypes with an accuracy of 97.65% for imipenem, 96.57% for ceftazidime, 97.64% for cefepime, and 98.36% for ciprofloxacin. The average reporting time of mNGS-based AST was 19.1 h, in contrast to the 63.3 h for culture-based AST, thus yielding a significant reduction of 44.3 h. mNGS-AST prediction results coincided 100% with the phenotypic AST results when testing 50 prospective samples. The mNGS-based model could be used as a rapid genotypic AST approach to identify A. baumannii and predict resistance and susceptibility to antibacterials and could be applicable to other pathogens and facilitate rational antimicrobial usage.

Circulating tumor DNA functions as an alternative for tissue to overcome tumor heterogeneity in advanced gastric cancer.

Overcoming tumor heterogeneity is a major challenge for personalized treatment of gastric cancer, especially for human epidermal growth factor receptor-2 targeted therapy. Analysis of circulating tumor DNA allows a more comprehensive analysis of tumor heterogeneity than traditional biopsies in lung cancer and breast cancer, but little is known in gastric cancer. We assessed mutation profiles of ctDNA and primary tumors from 30 patients with advanced gastric cancer, then performed a comprehensive analysis of tumor mutations by multiple biopsies from five patients, and finally analyzed the concordance of HER2 amplification in ctDNA and paired tumor tissues in 70 patients. By comparing with a single tumor sample, ctDNA displayed a low concordance of mutation profile, only approximately 50% (138/275) somatic mutations were found in paired tissue samples, however, when compared with multiple biopsies, most DNA mutations in ctDNA were also shown in paired tumor tissues. ctDNA had a high concordance (91.4%, Kappa index = 0.784, P < 0.001) of HER2 amplification with tumor tissues, suggesting it might be an alternative for tissue. It implied that ctDNA-based assessment could partially overcome the tumor heterogeneity, and might serve as a potential surrogate for HER2 analysis in gastric cancer.

Dysbiosis of lower respiratory tract microbiome are associated with proinflammatory states in non-small cell lung cancer patients.

BACKGROUND: The lung has a sophisticated microbiome, and respiratory illnesses are greatly influenced by the lung microbiota. Despite the fact that numerous studies have shown that lung cancer patients have a dysbiosis as compared to healthy people, more research is needed to explore the association between the microbiota dysbiosis and immune profile within the tumor microenvironment (TME). METHODS: In this study, we performed metagenomic sequencing of tumor and normal tissues from 61 non-small cell lung cancer (NSCLC) patients and six patients with other lung diseases. In order to characterize the impact of the microbes in TME, the cytokine concentrations of 24 lung tumor and normal tissues were detected using a multiple cytokine panel. RESULTS: Our results showed that tumors had lower microbiota diversity than the paired normal tissues, and the microbiota of NSCLC was enriched in Proteobacteria, Firmicutes, and Actinobacteria. In addition, proinflammatory cytokines such as IL-8, MIF, TNF- α, and so on, were significantly upregulated in tumor tissues. CONCLUSION: We discovered a subset of bacteria linked to host inflammatory signaling pathways and, more precisely, to particular immune cells. We determined that lower airway microbiome dysbiosis may be linked to the disruption of the equilibrium of the immune system causing lung inflammation. The spread of lung cancer may be linked to specific bacteria.

Clinical metagenomic sequencing of plasma microbial cell-free DNA for febrile neutropenia in patients with acute leukaemia.

OBJECTIVES: To evaluate the diagnostic performance and clinical impact of metagenomic next-generation sequencing (mNGS) of plasma microbial cell-free DNA (mcfDNA) in febrile neutropenia (FN). METHODS: In a 1-year, multicentre, prospective study, we enrolled 442 adult patients with acute leukaemia with FN and investigated the usefulness of mNGS of plasma mcfDNA for identification of infectious pathogens. The results of mNGS were available to clinicians in real time. The performance of mNGS testing was evaluated in comparison with blood culture (BC) and a composite standard that incorporated standard microbiological testing and clinical adjudication. RESULTS: In comparison with BC, the positive and negative agreements of mNGS were 81.91% (77 of 94) and 60.92% (212 of 348), respectively. By clinical adjudication, mNGS results were categorized by infectious diseases specialists as definite (n = 76), probable (n = 116), possible (n = 26), unlikely (n = 7), and false negative (n = 5). In 225 mNGS-positive cases, 81 patients (36%) underwent antimicrobials adjustment, resulting in positive impact on 79 patients and negative impact on two patients (antibiotics overuse). Further analysis indicated that mNGS was less affected by prior antibiotics exposure than BC. DISCUSSION: Our results indicate that mNGS of plasma mcfDNA increased the detection of clinically significant pathogens and enabled early optimization of antimicrobial therapy in patients with acute leukaemia with FN.

Rapid inference of antibiotic resistance and susceptibility for Klebsiella pneumoniae by clinical shotgun metagenomic sequencing.

OBJECTIVES: The study aimed to develop a genotypic antimicrobial resistance testing method for Klebsiella pneumoniae using metagenomic sequencing data. METHODS: We utilized Lasso regression on assembled genomes to identify genetic resistance determinants for six antibiotics (Gentamicin, Tobramycin, Imipenem, Meropenem, Ceftazidime, Trimethoprim/Sulfamethoxazole). The genetic features were weighted, grouped into clusters to establish classifier models. Origin species of detected antibiotic resistant gene (ARG) was determined by novel strategy integrating "possible species," "gene copy number calculation" and "species-specific kmers." The performance of the method was evaluated on retrospective case studies. RESULTS: Our study employed machine learning on 3928 K. pneumoniae isolates, yielding stable models with AUCs > 0.9 for various antibiotics. GenseqAMR, a read-based software, exhibited high accuracy (AUC 0.926-0.956) for short-read datasets. The integration of a species-specific kmer strategy significantly improved ARG-species attribution to an average accuracy of 96.67%. In a retrospective study of 191 K. pneumoniae-positive clinical specimens (0.68-93.39% genome coverage), GenseqAMR predicted 84.23% of AST results on average. It demonstrated 88.76-96.26% accuracy for resistance prediction, offering genotypic AST results with a shorter turnaround time (mean ± SD: 18.34 ± 0.87 hours) than traditional culture-based AST (60.15 ± 21.58 hours). Furthermore, a retrospective clinical case study involving 63 cases showed that GenseqAMR could lead to changes in clinical treatment for 24 (38.10%) cases, with 95.83% (23/24) of these changes deemed beneficial. CONCLUSIONS: In conclusion, GenseqAMR is a promising tool for quick and accurate AMR prediction in Klebsiella pneumoniae, with the potential to improve patient outcomes through timely adjustments in antibiotic treatment.

Establishment of a human colorectal cancer cell line P6C with stem cell properties and resistance to chemotherapeutic drugs.

AIM: Cancer stem cells have the capacity to initiate and sustain tumor growth. In this study, we established a CD44(+) colorectal cancer stem cell line with particular emphasis on its self-renewal capacity, enhanced tumor initiation and drug resistance. METHODS: Fresh colon cancer and paired normal colon tissues were collected from 13 patients who had not received chemotherapy or radiotherapy prior to surgery. Among the 6 single-cell derived clones, only the P6C cell line was cultured for more than 20 passages in serial culture and formed holoclones with high efficiency, and then the stemness gene expression, colony formation, tumorigenicity and drug sensitivities of the P6C cell line were examined. RESULTS: Stemness proteins, including c-Myc, Oct3/4, Nanog, Lgr5, and SOX2, were highly expressed in the P6C cell line. Oct3/4-positive P6C cells mostly generated holoclones through symmetric division, while a small number of P6C cells generated meroclones through asymmetric division. P6C cells stably expressed CD44 and possessed a high capacity to form tumor spheres. A single cell-derived sphere was capable of generating xenograft tumors in nude mice. Compared to SW480 and HCT116 colorectal cancer cells, P6C cells were highly resistant to Camptothecin and 5-fluorouracil, the commonly used chemotherapeutic agents to treat colorectal cancers. CONCLUSION: We established a colorectal cancer stem cell line P6C with a high tumorigenic capacity and the characteristics of normal stem cells. It will benefit the mechanistic studies on cancer stem cells and the development of drugs that specifically target the cancer stem cells.

Mutant GTF2I induces cell transformation and metabolic alterations in thymic epithelial cells.

The pathogenesis of thymic epithelial tumors (TETs) is poorly understood. Recently we reported the frequent occurrence of a missense mutation in the GTF2I gene in TETs and hypothesized that GTF2I mutation might contribute to thymic tumorigenesis. Expression of mutant TFII-I altered the transcriptome of normal thymic epithelial cells and upregulated several oncogenic genes. Gtf2i L424H knockin cells exhibited cell transformation, aneuploidy, and increase tumor growth and survival under glucose deprivation or DNA damage. Gtf2i mutation also increased the expression of several glycolytic enzymes, cyclooxygenase-2, and caused modifications of lipid metabolism. Elevated cyclooxygenase-2 expression by Gtf2i mutation was required for survival under metabolic stress and cellular transformation of thymic epithelial cells. Our findings identify GTF2I mutation as a new oncogenic driver that is responsible for transformation of thymic epithelial cells.

Clinical metagenomic sequencing for diagnosis of pulmonary tuberculosis.

OBJECTIVES: The aim of this study is to investigate the clinical usefulness of metagenomic Next-generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) samples to discriminate pulmonary tuberculosis (PTB) from Non-TB community-acquired pneumonia (CAP) in PTB suspects. METHODS: We investigate the performance of mNGS on BALF samples from 110 PTB suspects, in comparison with conventional microbiological testing (solid media culture, acid-fast bacilli staining (AFS), Xpert) of BALF or sputum samples and final clinical diagnosis. RESULTS: We finally clinically diagnosed 48 cases of pulmonary tuberculosis patients and 62 cases of non-tuberculosis patients. Comparing to the final clinical diagnosis, mNGS produced a sensitivity of 47.92%, which was similar to that of Xpert (45.83%) and culture (46.81%), but much higher than that of AFS (29.17%) for TB diagnosis in BALF samples. Apart from detecting Mycobacterium tuberculosis, mNGS also identified mixed infections in PTB patients, including 3 fungal cases and 1 bacteria case. Meanwhile, mNGS efficiently identified 14 of 22 (63.63%) cases of non-tuberculous mycobacteria (NTM), 7 cases of fungi, 1 case of viral infection, and other common bacterial pathogens in Non-PTB group. Finally, mNGS identified 67.23% infection cases within 3 days, while the conventional methods identified 49.58% infection cases for over 90 days. CONCLUSION: Our data show that mNGS of BALF represents a potentially effective tool for the rapid diagnosis of PTB suspects.

Evaluation of Next Generation Sequencing for Detecting HER2 Copy Number in Breast and Gastric Cancers.

Amplicon-based next generation sequencing (NGS) approaches have been preferentially adopted by the clinical laboratories on the basis of a short turnaround time (TAT) and small DNA input needs. However, little work has been done to assess the amplicon-based NGS methods for copy number variation (CNV) detection in comparison with current standard methods like immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH). The correlation between NGS based CNV detection and the later standard methods has remained unexplored. We developed an amplicon-based panel to detect human epidermal receptor growth factor (HER2) amplification in formalin-fixed paraffin-embedded (FFPE) tumor tissue samples from 280 breast cancer and 50 gastric cancer patients. Assessment by IHC and FISH was conducted in parallel, and descriptive statistics were used to assess the concordance. The copy number detected by NGS was correlated with either the average HER2 copy number (signals/cell) (r = 0.844; p < 0.001) or the HER2/CEP17 ratio (r = 0.815; p < 0.001). We determined a cut-off value for NGS to categorize HER2 amplification status by using 151 HER2 non-amplified FFPE samples. In breast cancer patients, the cut-off value was 2.910, with 95.35%, 98.67% and 97.29% sensitivity, specificity and concordance, respectively. However, this cut-off value displayed low sensitivity in gastric cancer patients (64.71%), and the following macrodissection procedure was not effective for increasing sensitivity (57.14%). Evaluation of HER2 copy number with NGS in our study was comparable with IHC and FISH in breast cancer patients, but concordance in gastric cancer was only moderate. The greater discordance in gastric cancer may reflect the underlying biological mechanisms, and further study is warranted. NGS-based HER2 assessment may decrease the equivocal HER2 determinations in breast cancer patients assessed by FISH/IHC.

Acquired SETD2 mutation and impaired CREB1 activation confer cisplatin resistance in metastatic non-small cell lung cancer.

Resistance to chemotherapy remains a critical barrier to effective cancer treatment. Although cisplatin is one of the most commonly used chemotherapeutic agents in the treatment of non-small cell lung cancer (NSCLC), mechanisms of resistance to this drug are not fully understood. Here, we report a novel cisplatin-resistance mechanism involving SET Domain Containing 2 (SETD2), a histone H3 lysine 36 (H3K36) trimethyltransferase, and cAMP-responsive element-binding protein 1 (CREB1). A549 cells selected in vivo to give brain metastases exhibited cisplatin resistance and decreased expression of phosphorylated CREB1. Next-generation sequencing (NGS) analysis identified a missense mutation in SETD2 (p.T1171K), and we demonstrated that SETD2-mediated trimethylation of H3K36 (H3K36me3) and CREB1 phosphorylation are critical for cellular sensitivity to cisplatin. Moreover, we showed that suppression of SETD2 or CREB1 and ectopic expression of mutant SETD2 conferred cisplatin resistance through inhibition of H3K36me3 and ERK activation in NSCLC cells. Our results provide evidence that SETD2 and CREB1 contribute to cisplatin cytotoxicity via regulation of the ERK signaling pathway, and their inactivation may lead to cisplatin resistance.

Checkpoint Kinase 1 Inhibition Enhances Cisplatin Cytotoxicity and Overcomes Cisplatin Resistance in SCLC by Promoting Mitotic Cell Death.

INTRODUCTION: Platinum-based chemotherapy remains the standard treatment for patients with SCLC, but the benefit of the treatment is often hampered by rapid development of drug resistance. Thus far, there is no targeted therapy available for SCLC. More than 90% of SCLC tumors harbor mutations in the tumor suppressor gene tumor protein p53 (p53), an important DNA damage checkpoint regulator, and these tumor cells rely predominantly on the checkpoint kinases to control DNA damage response. METHODS: We examined whether and how inhibition of checkpoint kinase 1 (Chk1) affects cisplatin cytotoxicity in SCLC cells with and without p53 mutations, and evaluated the effect of Chk1 inhibitor and cisplatin combination in cisplatin-sensitive and -resistant preclinical models. RESULTS: Inhibition of Chk1 synergized with cisplatin to induce mitotic cell death in the p53-deficeint SCLC cells. The effect was regulated in part through activation of caspase 2 and downregulation of E2F transcription factor 1 (E2F1). Furthermore, Chk1 inhibitors prexasertib and AZD7762 enhanced cisplatin antitumor activity and overcame cisplatin resistance in SCLC preclinical models in vitro an in vivo. We also observed that higher expression of Chk1 was associated with poorer overall survival of patients with SCLC. CONCLUSIONS: Our data account Chk1 as a potential therapeutic target in SCLC, and rationalize clinical development of Chk1 inhibitor and cisplatin combinational strategy for the treatment of SCLC.

Dasatinib sensitises KRAS-mutant cancer cells to mitogen-activated protein kinase kinase inhibitor via inhibition of TAZ activity.

PURPOSE: Oncogenic KRAS mutations occur frequently in solid tumours, but no clinically applicable targeted strategy is yet available for treating human cancers with mutant KRAS. Here we aimed to identify a strategy for the treatment of KRAS-driven cancers. EXPERIMENTAL DESIGN: Cell viability and colony forming assays were used to assess the in vitro effect of dasatinib and trametinib as single agents or in combination. Western blot was used to analyse the phosphorylated protein and total protein levels. Xenograft models were used to evaluate the in vivo effect of drug combination on KRAS-driven tumour growth. RESULTS: Here, we report the discovery of a synergistic interaction between dasatinib (ABL and SRC family kinase inhibitor) and the mitogen-activated protein kinase kinase (MEK) inhibitor trametinib in KRAS-mutant cancer cells. We demonstrated that dasatinib enhanced the antitumour effect of trametinib against the KRAS-mutant cancer models both in vitro and in vivo, and the combination resulted in a significant reduction of cytoplasmic and nucleic TAZ protein level, and therefore decreased downstream protein levels of YAP/TAZ signalling pathway. Furthermore, direct knockdown of TAZ by small interfering RNA was able to increase the sensitivity of KRAS-mutant cells to trametinib treatment. CONCLUSION: These results indicate that dasatinib enhances the antitumour activity of MEK inhibitor through inhibition of TAZ activity and identify dasatinib and trametinib combination as a potential strategy for the treatment of KRAS-driven cancers.

RAS/BRAF Circulating Tumor DNA Mutations as a Predictor of Response to First-Line Chemotherapy in Metastatic Colorectal Cancer Patients.

Background: Since circulating tumor DNA (ctDNA) offers clear advantages as a minimally invasive method for tumor monitoring compared with tumor tissue, we aimed to evaluate genotyping ctDNA using a next-generation sequencing- (NGS-) based panel to identify the prognostic value of mutation status in metastatic colorectal cancer (mCRC) patients with primary tumor resected and with subsequent lines of treatment in this study. Methods: 76 mCRC patients treated in Beijing Chao-Yang Hospital from 2011 to 2017 were enrolled. Genotyping of RAS/BRAF in tumor tissue and ctDNA was determined by ARMS PCR and with a 40-gene panel using NGS, respectively. Patient clinicopathologic features and RAS/BRAF gene mutation status were evaluated by survival analysis for disease-free survival (DFS) and progression-free survival (PFS). Results: Among 76 patients, KRAS distributions were not significantly correlated with any clinicopathologic features. The concordance between tumor tissue and ctDNA KRAS mutation was 81.25%. Mutations of RAS/BRAF had no significant impact on DFS after surgery (hazard ratio (HR), 1.205; 95% CI, 0.618 to 2.349; P = 0.5837) but prognosticated poorer PFS in subsequent first-line therapy (HR, 3.351; 95% CI, 1.172 to 9.576; P = 0.024). Conclusion: ctDNA was comparable with tumor tissue for mutation detection. RAS/BRAF mutations detected in ctDNA predict a worse PFS in mCRC patients with first-line chemotherapy. Our results provide support for the prognostic value of RAS/BRAF ctDNA mutation detection in mCRC patients.

Evaluation of digital PCR for detecting low-level EGFR mutations in advanced lung adenocarcinoma patients: a cross-platform comparison study.

Emerging evidence has indicated that circulating tumor DNA (ctDNA) from plasma could be used to analyze EGFR mutation status for NSCLC patients; however, due to the low level of ctDNA in plasma, highly sensitive approaches are required to detect low frequency mutations. In addition, the cutoff for the mutation abundance that can be detected in tumor tissue but cannot be detected in matched ctDNA is still unknown. To assess a highly sensitive method, we evaluated the use of digital PCR in the detection of EGFR mutations in tumor tissue from 47 advanced lung adenocarcinoma patients through comparison with NGS and ARMS. We determined the degree of concordance between tumor tissue DNA and paired ctDNA and analyzed the mutation abundance relationship between them. Digital PCR and Proton had a high sensitivity (96.00% vs. 100%) compared with that of ARMS in the detection of mutations in tumor tissue. Digital PCR outperformed Proton in identifying more low abundance mutations. The ctDNA detection rate of digital PCR was 87.50% in paired tumor tissue with a mutation abundance above 5% and 7.59% in paired tumor tissue with a mutation abundance below 5%. When the DNA mutation abundance of tumor tissue was above 3.81%, it could identify mutations in paired ctDNA with a high sensitivity. Digital PCR will help identify alternative methods for detecting low abundance mutations in tumor tissue DNA and plasma ctDNA.

Inhibition of AKT1 signaling promotes invasion and metastasis of non-small cell lung cancer cells with K-RAS or EGFR mutations.

Accumulating evidence supports a role of the PI3K-AKT pathway in the regulation of cell motility, invasion and metastasis. AKT activation is known to promote metastasis, however under certain circumstances, it also shows an inhibitory activity on metastatic processes, and the cause of such conflicting results is largely unclear. Here we found that AKT1 is an important regulator of metastasis and down-regulation of its activity is associated with increased metastatic potential of A549 cells. Inhibition of AKT1 enhanced migration and invasion in KRAS- or EGFR-mutant non-small cell lung cancer (NSCLC) cells. The allosteric AKT inhibitor MK-2206 promoted metastasis of KRAS-mutated A549 cells in vivo. We next identified that the phosphorylation of Myristoylated alanine-rich C-kinase substrate (MARCKS) and LAMC2 protein level were increased with AKT1 inhibition, and MARCKS or LAMC2 knockdown abrogated migration and invasion induced by AKT1 inhibition. This study unravels an anti-metastatic role of AKT1 in the NSCLC cells with KRAS or EGFR mutations, and establishes an AKT1-MARCKS-LAMC2 feedback loop in this regulation.