[Application of deep convolutional neural networks in the diagnosis of laryngeal squamous cell carcinoma based on narrow band imaging endoscopy].

Objective: To explore the possibility of using artificial intelligence (AI) technology based on convolutional neural network (CNN) to assist the clinical diagnosis of laryngeal squamous cell carcinoma (LSCC) through deep learning algorithm. Methods: A deep CNN was developed and applied in narrow band imaging (NBI) endoscopy of 4 799 patients with laryngeal lesions, including 3 168 males and 1 631 females, aged from 21 to 87 years, from 2015 to 2017 in Beijing Tongren Hospital, Capital Medical University. A simple randomization method was used to select the laryngeal NBI images of 2 427 patients (1 388 benign lesions and 1 039 LSCC lesions) for the training and correction the CNN model. The remaining laryngeal NBI images of 2 372 patients (including 1 276 benign lesions and 1 096 LSCC lesions) were used as validation data set to compare performance between CNN and otolaryngologists. SPSS 21.0 software was used for Chi-square test to calculate the accuracy, sensitivity and specificity of AI and otolaryngologists. The area under the curve (AUC) of receiver operating curve (ROC) was used to evaluate the diagnostic ability of the algorithm for NBI images. Results: The accuracy, sensitivity and specificity for NBI predictions were respectively 90.91% (AUC=0.96), 90.12% and 91.53%, which were equivalent to those for otolaryngologists' predictions (accuracy, sensitivity and specificity were (91.93±3.20)%, (91.33±3.25)% and (93.02±2.59)%, t values were 0.64, 0.75 and 1.17, and P values were 0.32, 0.28 and 0.21, respectively). The diagnostic efficiency of CNN was significantly higher than that of otolaryngologists (0.01 vs. 5.50, t =9.15, P<0.001). Conclusion: AI based on deep CNN is effective for using in the laryngeal NBI image diagnosis, showing a good application prospect in the diagnosis of LSCC.

No common denominator for breast cancer lymph node metastasis.

The axillary lymph node status is the most powerful prognostic factor for breast cancer patients to date. The molecular mechanisms that control lymph node metastasis, however, remain poorly understood. To define patterns of genes or gene regulatory pathways that drive breast cancer lymph node metastasis, we compared the gene expression profiles of 15 primary breast carcinomas and their matching lymph node metastases using microarrays. In general, primary breast carcinomas and lymph node metastases do not differ at the transcriptional level by a common subset of genes. No classifier or single gene discriminating the group of primary tumours from those of the lymph node metastases could be identified. Also, in a series of 295 breast tumours, no classifier predicting lymph node metastasis could be developed. However, subtle differences in the expression of genes involved in extracellular-matrix organisation and growth factor signalling are detected in individual pairs of matching primary and metastatic tumours. Surprisingly, however, different sets of these genes are either up- or downregulated in lymph node metastases. Our data suggest that breast carcinomas do not use a shared gene set to accomplish lymph node metastasis.

Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer.

We describe a flexible system for gene expression profiling using arrays of tens of thousands of oligonucleotides synthesized in situ by an ink-jet printing method employing standard phosphoramidite chemistry. We have characterized the dependence of hybridization specificity and sensitivity on parameters including oligonucleotide length, hybridization stringency, sequence identity, sample abundance, and sample preparation method. We find that 60-mer oligonucleotides reliably detect transcript ratios at one copy per cell in complex biological samples, and that ink-jet arrays are compatible with several different sample amplification and labeling techniques. Furthermore, results using only a single carefully selected oligonucleotide per gene correlate closely with those obtained using complementary DNA (cDNA) arrays. Most of the genes for which measurements differ are members of gene families that can only be distinguished by oligonucleotides. Because different oligonucleotide sequences can be specified for each array, we anticipate that ink-jet oligonucleotide array technology will be useful in a wide variety of DNA microarray applications.

Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles.

Genome-wide transcript profiling was used to monitor signal transduction during yeast pheromone response. Genetic manipulations allowed analysis of changes in gene expression underlying pheromone signaling, cell cycle control, and polarized morphogenesis. A two-dimensional hierarchical clustered matrix, covering 383 of the most highly regulated genes, was constructed from 46 diverse experimental conditions. Diagnostic subsets of coexpressed genes reflected signaling activity, cross talk, and overlap of multiple mitogen-activated protein kinase (MAPK) pathways. Analysis of the profiles specified by two different MAPKs-Fus3p and Kss1p-revealed functional overlap of the filamentous growth and mating responses. Global transcript analysis reflects biological responses associated with the activation and perturbation of signal transduction pathways.