Clinical Validation of the Unparalleled Sensitivity of the Novel Allele-Discriminating Priming System Technology-Based EGFR Mutation Assay in Patients with Operable Non-Small Cell Lung Cancer.

PURPOSE: Recently, we developed allele-discriminating priming system (ADPS) technology. This method increases the sensitivity of conventional quantitative polymerase chain reaction up to 100 folds, with limit of detection, 0.01%, with reinforced specificity. This prospective study aimed to develop and validate the accuracy of ADPS epidermal growth factor receptor (EGFR) Mutation Test Kit using clinical specimens. MATERIALS AND METHODS: In total 189 formalin-fixed paraffin-embedded tumor tissues resected from patients with non-small cell lung cancer were used to perform a comparative evaluation of the ADPS EGFR Mutation Test Kit versus the cobas EGFR Mutation Test v2, which is the current gold standard. When the two methods had inconsistent results, next-generation sequencing-based CancerSCAN was utilized as a referee. RESULTS: The overall agreement of the two methods was 97.4% (93.9%-99.1%); the positive percent agreement, 95.0% (88.7%-98.4%); and the negative percent agreement, 100.0% (95.9%-100.0%). EGFR mutations were detected at a frequency of 50.3% using the ADPS EGFR Mutation Test Kit and 52.9% using the cobas EGFR Mutation Test v2. There were 10 discrepant mutation calls between the two methods. CancerSCAN reproduced eight ADPS results. In two cases, mutant allele fraction was ultra-low at 0.02% and 0.06%, which are significantly below the limit of detection of the cobas assay and CancerSCAN. Based on the EGFR genotyping by ADPS, the treatment options could be switched in five patients. CONCLUSION: The highly sensitive and specific ADPS EGFR Mutation Test Kit would be useful in detecting the patients who have lung cancer with EGFR mutation, and can benefit from the EGFR targeted therapy.

Evaluation of Combined Cancer Markers With Lactate Dehydrogenase and Application of Machine Learning Algorithms for Differentiating Benign Disease From Malignant Ovarian Cancer.

BACKGROUND: The differential diagnosis of ovarian cancer is important, and there has been ongoing research to identify biomarkers with higher performance. This study aimed to evaluate the diagnostic utility of combinations of cancer markers classified by machine learning algorithms in patients with early stage ovarian cancer, which has rarely been reported. METHODS: In total, 730 serum samples were assayed for lactate dehydrogenase (LD), neutrophil-to-lymphocyte ratio (NLR), human epididymis protein 4 (HE4), cancer antigen 125 (CA125), and risk of ovarian malignancy algorithm (ROMA). Among them, 53 were diagnosed with early stage ovarian cancer, and the remaining 677 were diagnosed with benign disease. RESULTS: The areas under the receiver operating characteristic curves (ROC-AUCs) of the ROMA, HE4, CA125, LD, and NLR for discriminating ovarian cancer from non-cancerous disease were .707, .680, .643, .657, and .624, respectively. ROC-AUC of the combination of ROMA and LD (.709) was similar to that of single ROMA in the total population. In the postmenopausal group, ROC-AUCs of HE4 and CA125 combined with LD presented the highest value (.718). When machine learning algorithms were applied to ROMA combined with LD, the ROC-AUC of random forest was higher than that of other applied algorithms in the total population (.757), showing acceptable performance. CONCLUSION: Our data suggest that the combinations of ovarian cancer-specific markers with LD classified by random forest may be a useful tool for predicting ovarian cancer, particularly in clinical settings, due to easy accessibility and cost-effectiveness. Application of an optimal combination of cancer markers and algorithms would facilitate appropriate management of ovarian cancer patients.

Accurate Prognosis Prediction of Pancreatic Ductal Adenocarcinoma Using Integrated Clinico-Genomic Data of Endoscopic Ultrasound-Guided Fine Needle Biopsy.

The aim of this study was to investigate the clinical utility of minimal specimens acquired from endoscopic ultrasound-guided fine-needle biopsy (EUS-FNB) and perform targeted deep sequencing as a prognosis prediction tool for pancreatic ductal adenocarcinoma (PDAC). A total of 116 specimens with pathologically confirmed PDAC via EUS-FNB were tested using CancerSCAN® panel for a customized targeted deep sequencing. Clinical prognostic factors significantly associated with survival in PDACs were as follows: stage, tumor mass size, tumor location, metastasis, chemotherapy, and initial CA19-9 level. A total of 114 patients (98.3%) had at least a single genetic alteration, and no mutations were detected in two patients, although they were qualified for the targeted deep sequencing. The frequencies of major gene mutations responsible for PDACs were KRAS 90%, CDKN2A 31%, TP53 77%, and SMAD4 29%. A somatic point mutation of NF1, copy number alteration of SMAD4, and loss-of-function of CDKN2A were significantly associated genetic factors for overall survival. Moreover, BRCA2 point mutation was related to liver metastasis. Finally, a clinico-genomic model was developed to estimate the prognosis of patients with PDAC based on clinical parameters and genetic alterations affecting survival in patients; 20 single nucleotide variants and three copy number variations were selected. Targeted deep sequencing on minimal specimens of PDACs was performed, and it was applied to establish a clinico-genomic model for prognosis prediction.

Modification of thoracoscopic surgery for spontaneous pneumothorax.

Morbidity, use of analgesics, postoperative drainage, and hospital stay are reduced after video-assisted thoracoscopic surgery for pneumothorax. However, some surgeons prefer a minithoracotomy because the rate of recurrence after thoracoscopic surgery is 5%-10%. A modified thoracoscopic bullectomy is described, which has the advantages of both conventional video-assisted thoracoscopic surgery and a minithoracotomy. Of 69 patients who underwent surgery for pneumothorax from January 2002 to February 2003, 13 were treated by conventional video-assisted thoracoscopic surgery and 21 by the modified thoracoscopic bullectomy. The mean ages were 20.6 years in the conventional group and 23.0 years in the modified group, with follow-up of 25.8 +/- 1.8 months in the conventional group and 20.6 +/- 1.3 months in the modified group. The duration of operation was similar in both groups (49.3 +/- 16.0 vs. 44.2 +/- 19.2 min). Significantly fewer staples were used in the modified group (1.62 +/- 0.74 vs. 2.92 +/- 1.19). The duration of chest tube drainage and postoperative hospital stay were significantly reduced in the modified group. The modified thoracoscopic bullectomy is an effective procedure for the treatment of primary spontaneous pneumothorax.