Cooperation between artificial intelligence and endoscopists for diagnosing invasion depth of early gastric cancer.

BACKGROUND AND STUDY AIMS: The diagnostic ability of endoscopists to determine invasion depth of early gastric cancer is not favorable. We designed an artificial intelligence (AI) classifier for differentiating intramucosal and submucosal gastric cancers and examined it to establish a diagnostic method based on cooperation between AI and endoscopists. PATIENTS AND METHODS: We prepared 500 training images using cases of mainly depressed-type early gastric cancer from 250 intramucosal cancers and 250 submucosal cancers. We also prepared 200 test images each of 100 cancers from another institution. We designed an AI classifier to differentiate between intramucosal and submucosal cancers by deep learning. We examined the performance of the AI classifier and the majority vote of the endoscopists as high confidence and low confidence diagnostic probability, respectively, and cooperatively combined them to establish a diagnostic method providing high accuracy. RESULTS: Internal evaluation of the training images showed that accuracy, sensitivity, specificity, and F1 measure by the AI classifier were 77%, 76%, 78%, and 0.768, and those of the majority vote of the endoscopists were 72.6%, 53.6%, 91.6%, and 0.662, respectively. A diagnostic method based on cooperation between AI and the endoscopists showed that the respective values were 78.0%, 76.0%, 80.0%, and 0.776 for the test images. The value of F1 measure was especially higher than those by AI or the endoscopists alone. CONCLUSIONS: Cooperation between AI and endoscopists improved the diagnostic ability to determine invasion depth of early gastric cancer.

A novel prediction model of pancreatic fistula after pancreaticoduodenectomy using only preoperative markers.

BACKGROUND: Since clinically relevant postoperative pancreatic fistula (CR-POPF) can cause intra-abdominal hemorrhage and abscesses, leading to surgery-related deaths after pancreaticoduodenectomy (PD), its preoperative prediction is important to develop strategies for surgical procedures and perioperative management. This study aimed to establish a novel prediction model for CR-POPF using preoperative markers. METHODS: On a training set of 180 patients who underwent PD at the Yamaguchi University Hospital, a combination of CR-POPF predictors were explored using the leave-one-out method with a unique discrete Bayes classifier. This predictive model was confirmed using a validation set of 366 patients who underwent PD at the Osaka University Hospital. RESULTS: In the training set, CR-POPF occurred in 60 (33%)　of 180 patients and 130 (36%)　of 366 patients in the validation set using selected markers. In patients with pancreatic ductal adenocarcinoma (PDAC), the main pancreatic duct (MPD) index showed the highest prognostic performance and could differentiate CR-POPF with 87% sensitivity and 81% specificity among 84 patients in the training set. In the validation set, the sensitivity and specificity of the MPD index-based model for 130 PDAC samples were 93% and 87%, respectively. In patients with non-PDAC, the MPD index/body mass index (BMI) combination showed the highest prognostic performance and could differentiate CR-POPF with 84% sensitivity and 57% specificity among 96 patients in the training set. In the validation set, the sensitivity and specificity of the MPD index/BMI-based model for 236 non-PDAC samples were 85% and 53%, respectively. CONCLUSION: We developed a novel prediction model for pancreatic fistulas after PD using only preoperative markers. The MPD index and MPD index/BMI combination will be useful for CR-POPF assessment in PDAC and non-PDAC samples, respectively.

CD4 and FOXP3 as predictive markers for the recurrence of T3/T4a stage II colorectal cancer: applying a novel discrete Bayes decision rule.

BACKGROUND: We recently reported the relapse-free survival (RFS) significance of the combination of CD4+ and forkhead box P3+ (FOXP3) T-cell densities identified by immunohistochemistry in patients with stage I, II, and III colorectal cancer (CRC) who underwent curative resections. This study was designed to determine the optimal combination of markers that predict recurrence in patients with T factors of T3/T4a stage II CRC by applying a novel Bayes decision rule. METHODS: Using 137 cancer tissue specimens from T3/T4a stage II patients, 12 clinicopathologic and immune factors were analysed as predictive candidates for recurrence. RESULTS: Our study showed that the combination of low CD4+ and low FOXP3+ T-cell densities resulted in extremely poor RFS. CONCLUSIONS: Adjuvant chemotherapy may be considered for patients with a combination of low CD4+ and low FOXP3+ T-cell densities. The discovery of this new prognostic indicator is important for the appropriate management of patients undergoing curative resection for T3/T4a stage II CRC.

Image Correction Methods for Regions of Interest in Liver Cirrhosis Classification on CNNs.

The average error rate in liver cirrhosis classification on B-mode ultrasound images using the traditional pattern recognition approach is still too high. In order to improve the liver cirrhosis classification performance, image correction methods and a convolution neural network (CNN) approach are focused on. The impact of image correction methods on region of interest (ROI) images that are input into the CNN for the purpose of classifying liver cirrhosis based on data from B-mode ultrasound images is investigated. In this paper, image correction methods based on tone curves are developed. The experimental results show positive benefits from the image correction methods by improving the image quality of ROI images. By enhancing the image contrast of ROI images, the image quality improves and thus the generalization ability of the CNN also improves.

Serum LOX-1 is a novel prognostic biomarker of colorectal cancer.

BACKGROUND: Colorectal cancer is the third most common cancer worldwide. If biomarkers can be identified in liquid biopsy, diagnosis and treatment can be optimized even when cancerous tissues are not available. The purpose of this study was to identify proteins from liquid biopsy that would be useful as markers of poor prognosis. METHODS: First, we comprehensively analyzed serum proteins to identify potential biomarkers and focused on serum lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1). The relationship between LOX-1 and the prognosis of patients with colorectal cancer has not been reported. Next, we validated this marker using serum samples from 238 patients with colorectal cancer by ELISA and 100 tissue samples by immunohistochemical staining. RESULTS: The optimal cut-off value of serum LOX-1 was 538.7 pg/mL according to time-dependent receiver operating characteristics curve analysis. The overall survival of patients with high levels of serum LOX-1 was significantly poorer than that of individuals with low levels of LOX-1 in the training and test datasets. In multivariate analysis for overall survival, serum LOX-1 was an independent prognostic factor identified in liquid biopsy (hazard ratio = 1.729, p = 0.027). The prognosis of patients with high LOX-1 expression in tumor tissues was significantly poorer than that of individuals with low expression (p =0.047 ). Additionally, inflammatory factors such as white blood cell count, C-reactive protein level, neutrophil/lymphocyte ratio, and monocyte/lymphocyte ratio were significantly higher in the group with high serum LOX-1 levels. CONCLUSIONS: Serum LOX-1 might be a useful biomarker of poor prognosis in colorectal cancer.

Metastatic ability and the epithelial-mesenchymal transition in induced cancer stem-like hepatoma cells.

Cancer stem cells (CSCs) are thought to play important roles in cancer malignancy. Previously, we successfully induced sphere cancer stem-like cells (CSLCs) from several cell lines and observed the property of chemoresistance. In the present study, we examined the metastatic potential of these induced CSLCs. Sphere cancer stem-like cells were induced from a human hepatoma cell line (SK-HEP-1) in a unique medium containing neural survival factor-1. Splenic injection of cells into immune-deficient mice was used to assess hematogenous liver metastasis. Transcriptomic strand-specific RNA-sequencing analysis, quantitative real-time PCR, and flow cytometry were carried out to examine the expression of epithelial-mesenchymal transition (EMT)-related genes. Splenic injection of CSLCs resulted in a significantly increased frequency of liver metastasis compared to parental cancer cells (P < .05). In CSLCs, a mesenchymal marker, Vimentin, and EMT-promoting transcription factors, Snail and Twist1, were upregulated compared to parental cells. Correspondingly, significant enrichment of the molecular signature of the EMT in CSLCs relative to parental cancer cells was shown (q < 0.01) by RNA-sequencing analysis. This analysis also revealed differential expression of CD44 isoforms between CSLCs and parental cancer cells. Increasing CD44 isoforms containing an extra exon were observed, and the standard CD44 isoform decreased in CSLCs compared to parental cells. Interestingly, another CD44 variant isoform encoding a short cytoplasmic tail was also upregulated in CSLCs (11.7-fold). Our induced CSLCs possess an increased liver metastatic potential in which promotion of the EMT and upregulation of CD44 variant isoforms, especially short-tail, were observed.

miR-125b-1 and miR-378a are predictive biomarkers for the efficacy of vaccine treatment against colorectal cancer.

Many clinical trials of peptide vaccines have been conducted. However, these vaccines have provided clinical benefits in only a small fraction of patients. The purpose of the present study was to explore microRNAs (miRNAs) as novel predictive biomarkers for the efficacy of vaccine treatment against colorectal cancer. First, we carried out microarray analysis of pretreatment cancer tissues in a phase I study, in which peptide vaccines alone were given. Candidate miRNAs were selected by comparison of the better prognosis group with the poorer prognosis group. Next, we conducted microarray analysis of cancer tissues in a phase II study, in which peptide vaccines combined with chemotherapy were given. Candidate miRNAs were further selected by a similar comparison of prognosis. Subsequently, we carried out reverse-transcription PCR analysis of phase II cases, separating cancer tissues into cancer cells and stromal tissue using laser capture microdissection. Treatment effect in relation to overall survival (OS) and miRNA expression was analyzed. Three miRNA predictors were negatively associated with OS: miR-125b-1 in cancer cells (P = 0.040), and miR-378a in both cancer cells (P = 0.009) and stromal cells (P < 0.001). Multivariate analysis showed that expression of miR-378a in stromal cells was the best among the three predictors (HR, 2.730; 95% CI, 1.027-7.585; P = 0.044). In conclusion, miR-125b-1 and miR-378a expression might be considered as novel biomarkers to predict the efficacy of vaccine treatment against colorectal cancer.

An Automated Self-Learning Quantification System to Identify Visible Areas in Capsule Endoscopy Images.

Visibility in capsule endoscopic images is presently evaluated through intermittent analysis of frames selected by a physician. It is thus subjective and not quantitative. A method to automatically quantify the visibility on capsule endoscopic images has not been reported. Generally, when designing automated image recognition programs, physicians must provide a training image; this process is called supervised learning. We aimed to develop a novel automated self-learning quantification system to identify visible areas on capsule endoscopic images. The technique was developed using 200 capsule endoscopic images retrospectively selected from each of three patients. The rate of detection of visible areas on capsule endoscopic images between a supervised learning program, using training images labeled by a physician, and our novel automated self-learning program, using unlabeled training images without intervention by a physician, was compared. The rate of detection of visible areas was equivalent for the supervised learning program and for our automatic self-learning program. The visible areas automatically identified by self-learning program correlated to the areas identified by an experienced physician. We developed a novel self-learning automated program to identify visible areas in capsule endoscopic images.

Image quality of a novel light-emitting diode (LED)-illuminated colonoscope.

BACKGROUND AND STUDY AIMS: Light-emitting diodes (LEDs) are used widely for their high luminous efficiency and durability. We developed a novel prototype high definition endoscope with white LEDs and evaluated the image quality it produced against a commercial endoscope with conventional light source. PATIENTS AND METHODS: The specifications of both colonoscopes were identical, except for the LED light source at the tip of the prototype. We examined 20 patients with rectal or sigmoid colon lesions and the image quality was evaluated in 40 images (one image from the LED colonoscope and one from the conventional colonoscope for each lesion) by three endoscopists. We additionally evaluated the 17 videos recorded with the LED colonoscope that were available. Image quality, mucosal and vascular color, and luminous distribution and intensity were scored on a 5-point scale. RESULTS: The mean score for vascular color given by one evaluator was significantly higher using the LED colonoscope than using the conventional colonoscope. The mean scores for mucosal color and luminous intensity from another evaluator were significantly lower with the LED colonoscope than with the conventional colonoscope. There were no significant differences in the luminous distribution scores for any of the evaluators. The image quality of the videos was evaluated as being similar with both colonoscopes. CONCLUSIONS: Image quality from the LED and conventional colonoscopes were similar, although the luminous intensity of the LEDs is inferior to that of the conventional light source at the present time.

UGT1A1*6, 1A7*3, and 1A9*22 genotypes predict severe neutropenia in FOLFIRI-treated metastatic colorectal cancer in two prospective studies in Japan.

UNLABELLED: Retrospective studies have suggested that UDP-glucuronosyltransferase (UGT)1A1, UGT1A7, and UGT1A9 predict severe toxicity and efficacy of irinotecan-containing regimens. We prospectively evaluated the impact of UGT1A genotypes and haplotypes on severe toxicity and efficacy in patients treated with fluorouracil, leucovorin, and irinotecan combination chemotherapy (FOLFIRI) for metastatic colorectal cancer (mCRC) from the two prospective multicenter phase II studies in Japan. The FLIGHT1 study was a first-line FOLFIRI trial, and FLIGHT2 was a FOLFOX-refractory, second-line FOLFIRI trial. A total of 73 patients agreed to additional analysis, and were genotyped for UGT1A polymorphisms, UGT1A1*28 (TA6>TA7), UGT1A1*6 (211G>A), UGT1A1*27 (686C>A), UGT1A1*60 (-3279T>G), UGT1A1*93 (-3156G>A), UGT1A7 (-57T>G), UGT1A7*3 (387T>G, 622T>C), and UGT1A9*22 (T9>T10). Of 73 patients, 34 developed G3/4 severe hematological toxicities. The toxicities were significantly more frequent in patients with UGT1A1*6 (211A), UGT1A7 (387G), and UGT1A9*22 reference alleles (T9). Haplotype I, which consists of all favorable alleles, was associated with a significant reduction in hematologic toxicity (P = 0.031). In contrast, haplotype II, which contains four high-risk alleles, showed significantly higher hematologic toxicity than the other haplotypes (P = 0.010). Six out of seven patients who were homozygous for UGT1A1*28 or *6 experienced severe hematological toxicity despite the fact that their response rate was not impaired (42.9%). We concluded that UGT1A polymorphisms, especially UGT1A1*6, are important for the prediction of severe toxicity of FOLFIRI in northeast Asian populations. In this regard, haplotype analyses should substantially impact the prediction of severe hematological toxicities of FOLFIRI. ( CLINICAL TRIAL REGISTRATION: UMIN000002388 and UMIN000002476).

Association between a single nucleotide polymorphism in the R3HCC1 gene and irinotecan toxicity.

OBJECTIVE: Irinotecan is a useful anticancer drug for colorectal cancer treatment. UGT1A1*28 and *6 gene polymorphisms are known risk factors for irinotecan-associated toxicity. However, severe adverse effects due to irinotecan have been observed even in patients who do not harbor UGT1A1*28 or *6. We investigated gene polymorphisms in the whole exome to identify useful biomarkers for irinotecan toxicity other than UGT1A. METHODS: A total of 178 patients with metastatic colorectal cancer (mCRC) and 87 patients with pancreatic cancer were treated with FOLFIRI, FOLFOX, FOLFOXIRI, modified FOLFIRINOX, or gemcitabine plus nab-paclitaxel. Genome-wide screening was performed using whole-exome sequencing (WES), and validation analysis was performed using qPCR with a hydrolysis probe. RESULTS: Using WES after a doublet chemotherapy regimen comprising irinotecan and 5-fluorouracil (n = 15), seven single nucleotide polymorphisms (SNPs) were identified as candidate biomarkers for irinotecan-associated toxicity of neutropenia. Among the seven SNPs, an SNP in R3H domain and coiled-coil containing 1 (R3HCC1; c.919G > A, rs2272761) showed a significant association with neutropenia (>grade 3) after doublet chemotherapy. Patients receiving irinotecan including triplet chemotherapy, FOLFOXIRI for mCRC (n = 23) or modified FOLFIRINOX for pancreatic cancer (n = 40), also showed significant linear trends between R3HCC1 polymorphism and neutropenia (p = 0.017 and 0.046, respectively). No significant association was observed in patients treated with irinotecan-free regimens, FOLFOX for mCRC (n = 66), and gemcitabine plus nab-paclitaxel for pancreatic cancer (n = 47). CONCLUSION: Thus, an SNP in the R3HCC1 gene may be a useful biomarker for the toxicity of irinotecan-containing chemotherapy for mCRC and pancreatic cancer.

Objective evaluation of tongue diagnosis ability using a tongue diagnosis e-learning/e-assessment system based on a standardized tongue image database.

Background: In Kampo medicine, tongue examination is used to diagnose the pathological condition "Sho," but an objective evaluation method for its diagnostic ability has not been established. We constructed a tongue diagnosis electronic learning and evaluation system based on a standardized tongue image database. Purpose: This study aims to verify the practicality of this assessment system by evaluating the tongue diagnosis ability of Kampo specialists (KSs), medical professionals, and students. Methods: In the first study, we analyzed the answer data of 15 KSs in an 80-question tongue diagnosis test that assesses eight aspects of tongue findings and evaluated the (i) test score, (ii) test difficulty and discrimination index, (iii) diagnostic consistency, and (iv) diagnostic match rate between KSs. In the second study, we administered a 20-question common Kampo test and analyzed the answer data of 107 medical professionals and 56 students that assessed the tongue color discrimination ability and evaluated the (v) correct answer rate, (vi) test difficulty, and (vii) factors related to the correct answer rate. Result: In the first study, the average test score was 62.2 ± 10.7 points. Twenty-eight questions were difficult (correct answer rate, <50%), 34 were moderate (50%-85%), and 18 were easy (≥85%). Regarding intrarater reliability, the average diagnostic match rate of five KSs involved in database construction was 0.66 ± 0.08, and as for interrater reliability, the diagnostic match rate between the 15 KSs was 0.52 (95% confidence interval, 0.38-0.65) for Gwet's agreement coefficient 1, and the degree of the match rate was moderate. In the second study, the difficulty level of questions was moderate, with a correct rate of 81.3% for medical professionals and 82.1% for students. The discrimination index was good for medical professionals (0.35) and poor for students (0.06). Among medical professionals, the correct answer group of this question had a significantly higher total score on the Kampo common test than the incorrect answer group (85.3 ± 8.4 points vs. 75.8 ± 11.8 points, p < 0.01). Conclusion: This system can objectively evaluate tongue diagnosis ability and has high practicality. Utilizing this system can be expected to contribute to improving learners' tongue diagnosis ability and standardization of tongue diagnosis.

Interferon signaling and hypercytokinemia-related gene expression in the blood of antidepressant non-responders.

Only 50% of patients with depression respond to the first antidepressant drug administered. Thus, biomarkers for prediction of antidepressant responses are needed, as predicting which patients will not respond to antidepressants can optimize selection of alternative therapies. We aimed to identify biomarkers that could predict antidepressant responsiveness using a novel data-driven approach based on statistical pattern recognition. We retrospectively divided patients with major depressive disorder into antidepressant responder and non-responder groups. Comprehensive gene expression analysis was performed using peripheral blood without narrowing the genes. We designed a classifier according to our own discrete Bayes decision rule that can handle categorical data. Nineteen genes showed differential expression in the antidepressant non-responder group (n = 15) compared to the antidepressant responder group (n = 15). In the training sample of 30 individuals, eight candidate genes had significantly altered expression according to quantitative real-time polymerase chain reaction. The expression of these genes was examined in an independent test sample of antidepressant responders (n = 22) and non-responders (n = 12). Using the discrete Bayes classifier with the HERC5, IFI6, and IFI44 genes identified in the training set yielded 85% discrimination accuracy for antidepressant responsiveness in the 34 test samples. Pathway analysis of the RNA sequencing data for antidepressant responsiveness identified that hypercytokinemia- and interferon-related genes were increased in non-responders. Disease and biofunction analysis identified changes in genes related to inflammatory and infectious diseases, including coronavirus disease. These results strongly suggest an association between antidepressant responsiveness and inflammation, which may be useful for future treatment strategies for depression.

Microbiome biomarkers associated with the gut contraction response elicited by the Japanese traditional medicine daikenchuto.

Objective biomarkers are crucial in the development of personalized medicines, such as Japanese traditional medicine (Kampo). To date, some objective markers to predict the response of Kampo medicines have been reported, but the information is somewhat limited. The aim of this study was to search for objective markers and combinations thereof to estimate the effect of the Japanese traditional medicine daikenchuto (DKT) on colon contraction intensity in guinea pigs. Specifically, the microbiome biomarkers were employed as candidate, using the Fisher ratio and the nearest neighbor classifier for statistical pattern recognition. The combination of the ratio between gut microbes of family Ruminococcaceae/Rikenellaceae, Ruminococcaceae/Paraprevotellaceae, and genus Ruminococcus/unknown genus in family Rikenellaceae of guinea pig gut microbes was found to influence the activity of DKT with 0.8 accuracy for test samples. These findings suggest that statistical pattern recognition can contribute to identifying target markers of multi-target drugs such as Kampo.

Construction of a Standardized Tongue Image Database for Diagnostic Education: Development of a Tongue Diagnosis e-Learning System.

Tongue examination is an important diagnostic method for judging pathological conditions in Kampo (traditional Japanese medicine), but it is not easy for beginners to learn the diagnostic technique. One reason is that there are few objective diagnostic criteria for tongue examination findings, and the educational method for tongue examination is not standardized in Japan, warranting the need for a tongue image database for e-learning systems that could dramatically improve the efficiency of education. Therefore, we constructed a database comprising tongue images whose findings were determined on the basis of votes given by five Kampo medicine specialists (KMSs) and confirmed the educational usefulness of the database for tongue diagnosis e-learning systems. The study was conducted in the following five steps: development of a tongue imaging collection system, collection of tongue images, evaluation and annotation of tongue images, development of a tongue diagnosis e-learning system, and verification of the educational usefulness of this system. Five KMSs evaluated the tongue images obtained from 125 participants in the following eight aspects: (i) tongue body size, (ii) tongue body color, (iii) tongue body dryness and wetness, (iv) tooth marks on the edge of the tongue, (v) cracks on the surface of the tongue, (vi) thickness of tongue coating, (vii) color of tongue coating, and (viii) dryness and wetness of tongue coating. Medical students (MSs) were given a tongue diagnosis test using an e-learning system after a lecture on tongue diagnosis. The cumulative and individual match rates (%) (individual match rates of 100% (5/5), 80% (4/5), and 60% (3/5) are shown in parentheses, respectively) were as follows: (i) tongue body size: 92.8 (26.4/26.4/40.0); (ii) tongue body color: 83.2 (10.4/20.8/52.0); (iii) tongue body dryness and wetness: 88.8 (13.6/34.4/40.8); (iv) tooth marks on the edge of the tongue: 88.8 (6.4/35.2/47.2); (v) cracks on the surface of the tongue: 96.8 (24.0/35.2/37.6); (vi) thickness of tongue coating: 84.8 (7.2/21.6/56.0); (vii) color of tongue coating: 88.0 (15.2/37.6/35.2); and (viii) dryness and wetness of tongue coating: 74.4 (4.8/19.2/50.4). The test showed that the tongue diagnosis ability of MSs who attended a lecture on tongue diagnosis was almost the same as that of KMSs. We successfully constructed a tongue image database standardized for training specialists on tongue diagnosis and confirmed the educational usefulness of the e-learning system using a database. This database will contribute to the standardization and popularization of Kampo education.

New cine magnetic resonance imaging parameters for the differential diagnosis of chronic intestinal pseudo-obstruction.

Chronic intestinal pseudo-obstruction (CIPO) is a severe and refractory intestinal motility disorder whose diagnosis currently relies on subjective imaging assessments. Cine magnetic resonance imaging (MRI) may potentially improve the quantitative analysis of gastrointestinal motility; however, suitable CIPO detection parameters should be determined. Cine MRI was performed in seven patients with CIPO and 11 healthy controls. The logarithm of the Mahalanobis distance (x1) and distance variation per time (x2) were used as the original parameters to determine CIPO diagnostic thresholds. Furthermore, the correlation between cine MRI findings and CIPO severity was investigated. Threshold values of α = 1.10 and ß = 0.15 for x1 and x2, respectively, produced a CIPO diagnosis sensitivity of 1.00 (7/7) and specificity of 0.82 (9/11). The resulting error was 0.11 (2/18). The two parameters were correlated (Pearson's correlation coefficient: - 0.52). Any of the intestinal tracts of patients with severe CIPO requiring home parenteral nutrition belonged to the region defined by x1 ≥ 1.10 and x2 ≤ 0.15. Cine MRI is effective for the quantitative evaluation of small intestinal motility and CIPO diagnosis when using the abovementioned parameters and can be useful for treatment decision-making. However, these parameters have a wide distribution in healthy volunteers; this may complicate the detection of other disorders.

Distinct epigenetic signatures between adult-onset and late-onset depression.

The heterogeneity of major depressive disorder (MDD) is attributed to the fact that diagnostic criteria (e.g., DSM-5) are only based on clinical symptoms. The discovery of blood biomarkers has the potential to change the diagnosis of MDD. The purpose of this study was to identify blood biomarkers of DNA methylation by strategically subtyping patients with MDD by onset age. We analyzed genome-wide DNA methylation of patients with adult-onset depression (AOD; age ≥ 50 years, age at depression onset < 50 years; N = 10) and late-onset depression (LOD; age ≥ 50 years, age at depression onset ≥ 50 years; N = 25) in comparison to that of 30 healthy subjects. The methylation profile of the AOD group was not only different from that of the LOD group but also more homogenous. Six identified methylation CpG sites were validated by pyrosequencing and amplicon bisulfite sequencing as potential markers for AOD in a second set of independent patients with AOD and healthy control subjects (N = 11). The combination of three specific methylation markers achieved the highest accuracy (sensitivity, 64%; specificity, 91%; accuracy, 77%). Taken together, our findings suggest that DNA methylation markers are more suitable for AOD than for LOD patients.

Siglec-7 is a predictive biomarker for the efficacy of cancer vaccination against metastatic colorectal cancer.

Cancer immunotherapy, including vaccination, is considered a major scientific and medical breakthrough. However, cancer immunotherapy does not result in durable objective responses against colorectal cancer (CRC). To improve the efficacy of immunotherapy, the present study investigated several biomarkers for selecting patients who were expected to respond well to immunotherapy. Firstly, a comprehensive proteomic analysis was performed using tumor tissue lysates from patients enrolled in a phase II study, in which five human leukocyte antigen (HLA)-A*24:02-restricted peptides were administered. Sialic acid-binding immunoglobulin type lectin (Siglec)-7 was identified as a potential predictive biomarker. Subsequently, this biomarker was validated using western blot analysis, and immunofluorescence using tissue samples from the patients enrolled in the phase II study. The expression levels of Siglec-7 detected by immunofluorescence were quantified and their association with overall survival (OS) in patients treated with the peptide vaccine was examined. Furthermore, considering the important role of tumor-infiltrating lymphocytes (TILs) for CRC prognosis, the densities of CD3+, CD4+, CD8+ and forkhead box P3 (FOXP3)+ T cells in CRC tissues were examined and compared with Siglec-7 expression. The mean expression levels of Siglec-7 were significantly higher in patients with poor prognosis, with an OS of ≤2 years, as shown in comprehensive proteomic analysis (P=0.016) and western blot analysis (P=0.025). Immunofluorescence analysis demonstrated that Siglec-7 was expressed in intratumoral macrophages. The OS in patients with high Siglec-7 expression was significantly shorter than in that in patients with low Siglec-7 expression (P=0.017) in the HLA-A*24:02-matched patients. However, this difference was not observed in the HLA-unmatched patients. There was no significant difference in OS between patients according to the numbers of TILs, nor significant correlation between TILs and Siglec-7 expression. In conclusion, Siglec-7 expression in macrophages in tumor tissue may be a novel predictive biomarker for the efficacy of immunotherapy against metastatic CRC.

Exploration of the characteristics of chronotypes in upper gastrointestinal tract diseases: a multicenter study in Japan.

Characteristics of the chronotypes of patients with gastrointestinal disease are unknown. We evaluated chronotypes of patients with upper gastrointestinal diseases with the Munich ChronoType Questionnaire (MCTQ). A total of 2027 subjects from 29 institutions in Japan who had undergone esophagogastroduodenoscopy were asked to answer the MCTQ. The subjects' chronotypes were divided into three groups (early, intermediate, and late chronotype) using the sleep-corrected mid-point of sleep on free days (MSFSC) values. According to their endoscopic diagnosis and abdominal symptoms, the subjects were divided into the reflux esophagitis (RE) group, gastroduodenal ulcer (GDU) group, upper gastrointestinal carcinoma (CA) group, functional dyspepsia (FD) group, non-FD group, and control group. In total, 1128 subjects were eligible for the analysis. The MSFSC (average ± standard deviation, clock hours, h) of each disease group was as follows: control group: 02.51 ± 1.22, non-FD group: 02.69 ± 1.14, FD group: 02.91 ± 1.19, RE group: 02.58 ± 1.05, GDU group: 02.47 ± 1.31, and CA group: 02.11 ± 1.08 h. Compared to the control group, the rate of late chronotype of the FD group significantly increased to 33.3%, whereas that of early chronotype of the CA group significantly increased to 38.3% (P = .0177 and 0.0036, respectively). In both the FD and CA groups, chronotype was the independent factor related to the diseases. The adjusted odds ratio of late chronotype to early chronotype was 3.01 [95% CI, 1.23-7.35] in the FD group and 0.44 [95% CI, 0.23-0.85] in the CA group. In conclusion, late chronotype was common in patients with FD, and early chronotype was common in patients with upper gastrointestinal carcinoma.

Methylation of multiple genes as molecular markers for diagnosis of a small, well-differentiated hepatocellular carcinoma.

The current study was conducted to identify robust methylation markers and their combinations that may prove useful for the diagnosis of early hepatocellular carcinoma (HCC). To achieve this, we performed in silico CpG mapping, direct sequencing and pyrosequencing after bisulfite treatment, and quantitative methylation-specific PCR (MSP) in HCC and non-HCC liver tissues. In the filtering group (25 HCCs), our direct sequencing analysis showed that, among the 12 methylation genes listed by in silico CpG mapping, 7 genes (RASSF1A, CCND2, SPINT2, RUNX3, GSTP1, APC and CFTR) were aberrantly methylated in stages I and II HCCs. In the validation group (20 pairs of HCCs and the corresponding non-tumor liver tissues), pyrosequencing analysis confirmed that the 7 genes were aberrantly and strongly methylated in early HCCs, but not in any of the corresponding non- tumor liver tissues (p < 0.00001). The results obtained using our novel quantitative MSP assay correlated well with those observed using the pyrosequencing analysis. Notably, in MSP assay, RASSF1A showed the most robust performance for the discrimination of HCC and non-HCC liver tissues. Furthermore, a combination of RASSF1A, CCND2 and SPINT2 showed 89-95% sensitivity, 91-100% specificity and 89-97% accuracy in discriminating between HCC and non-HCC tissues, and correctly diagnosed all early HCCs. These results indicate that the combination of these 3 genes may aid in the accurate diagnosis of early HCC.