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.

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.

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.

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.

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.

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.

Objective Assessment of the Utility of Chromoendoscopy with a Support Vector Machine.

PURPOSE: The utility of chromoendoscopy for early gastric cancer (GC) was determined by machine learning using data of color differences. METHODS: Eighteen histopathologically confirmed early GC lesions were examined. We prepared images from white light endoscopy (WL), indigo carmine (Indigo), and acetic acid-indigo carmine chromoendoscopy (AIM). A border between cancerous and non-cancerous areas on endoscopic images was established from post-treatment pathological findings, and 2000 pixels with equivalent luminance values were randomly extracted from each image of cancerous and non-cancerous areas. Each pixel was represented as a three-dimensional vector with RGB values and defined as a sample. We evaluated the Mahalanobis distance using RGB values, indicative of color differences between cancerous and non-cancerous areas. We then conducted diagnosis test using a support vector machine (SVM) for each image. SVM was trained using the 100 training samples per class and determined which area each of 1900 test samples per class came from. RESULTS: The means of the Mahalanobis distances for WL, Indigo, and AIM were 1.52, 1.32, and 2.53, respectively and there were no significant differences in the three modalities. Diagnosability per endoscopy technique was assessed using the F1 measure. The means of F1 measures for WL, Indigo, and AIM were 0.636, 0.618, and 0.687, respectively. AIM images were better than WL and Indigo images for the diagnosis of GC. CONCLUSION: Objective assessment by SVM found AIM to be suitable for diagnosis of early GC based on color differences.

A new prognostic model for hepatocellular carcinoma recurrence after curative hepatectomy.

We previously reported the effectiveness of the product of tumor number and size (NxS factor) for the prognosis of hepatocellular carcinoma (HCC) in patients following hepatectomy. The present study aimed to propose a new score based on the NxS factor to predict HCC recurrence following hepatectomy. A total of 406 patients who underwent hepatectomy for HCC at Osaka University Graduate School of Medicine were retrospectively analyzed to develop the new score. Among clinicopathological factors, including the NxS factor, the marker subset that achieved the best performance for prediction of early recurrence was assessed, and a prognostic model for HCC recurrence after curative hepatectomy (REACH) was developed. As the validation set, 425 patients who underwent hepatectomy for HCC at Yamaguchi University Graduate School of Medicine and Shimonoseki Medical Center were analyzed, and the prognostic ability of the REACH score was compared with that of well-known staging systems. Following analysis, the REACH score was constructed using six covariates (NxS factor, microscopic hepatic vein invasion, differentiation, serum albumin, platelet count and indocyanine green retention rate at 15 min). In the validation set, the REACH score predicted early recurrence in 73 of 81 samples, with a sensitivity of 89% and a specificity of 58%. The area under the curve (AUC) of the receiver operating characteristic curve of the REACH score was 0.78 and 0.74, respectively, for 1- and 2-year recurrence after hepatectomy; each AUC was higher than that of any of the other staging systems. Survival analysis indicated the REACH score had the best predictive value in disease-free and overall survival. The present findings demonstrated that the REACH score may be used to classify patients with HCC into high- and low-risk of recurrence, and to predict subsequent survival following hepatic resection.

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.

Lymph node metastasis can be determined by just tumor depth and lymphovascular invasion in early gastric cancer patients after endoscopic submucosal dissection.

PURPOSE: Endoscopic submucosal dissection (ESD) is a minimally invasive treatment for early gastric cancer (EGC) with negligible risk of lymph node metastasis (LNM). When a patient is determined to have noncurative resection after ESD, additional surgical resection with lymph node dissection is recommended. Previous studies report that LNM is found in about 10% of these patients. It may be possible to avoid unnecessary surgical resection by selecting patients properly. We aimed to clarify the risk factors associated with LNM in EGC patients who underwent ESD and to develop a highly accurate diagnostic algorithm for LNM. PATIENTS AND METHODS: Among 1005 patients with EGC who underwent ESD, 423 patients who could be followed up for more than 3 years after treatment or who underwent additional surgical resection were examined. We used the leave-one-out method to explore the combination of predictive factors of LNM and differentiated LNM by a unique classifier. RESULTS: Curative resection was achieved in 322 patients, whereas noncurative resection was achieved in 101 patients. In the noncurative resection group, LNM occurred in eight patients with additional surgical resection and one patient during follow-up. The combination of depth of invasion, lymphatic, and venous invasion showed the highest diagnostic performance and could differentiate LNM with 100% sensitivity, 86% specificity, and 86% diagnostic accuracy. CONCLUSION: More than 500 µm submucosal invasion and lymphatic and venous invasion will be useful in assessing LNM after ESD for patients with EGC. When these three factors are not observed, follow-up alone might be appropriate and it may be possible to reduce unnecessary surgical resection.

Prediction of Early Recurrence of Liver Cancer by a Novel Discrete Bayes Decision Rule for Personalized Medicine.

We discuss a novel diagnostic method for predicting the early recurrence of liver cancer with high accuracy for personalized medicine. The difficulty with cancer treatment is that even if the types of cancer are the same, the cancers vary depending on the patient. Thus, remarkable attention has been paid to personalized medicine. Unfortunately, although the Tokyo Score, the Modified JIS, and the TNM classification have been proposed as liver scoring systems, none of these scoring systems have met the needs of clinical practice. In this paper, we convert continuous and discrete data to categorical data and keep the natively categorical data as is. Then, we propose a discrete Bayes decision rule that can deal with the categorical data. This may lead to its use with various types of laboratory data. Experimental results show that the proposed method produced a sensitivity of 0.86 and a specificity of 0.49 for the test samples. This suggests that our method may be superior to the well-known Tokyo Score, the Modified JIS, and the TNM classification in terms of sensitivity. Additional comparative study shows that if the numbers of test samples in two classes are the same, this method works well in terms of the F1 measure compared to the existing scoring methods.

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.

Use of hyperspectral imaging technology to develop a diagnostic support system for gastric cancer.

Hyperspectral imaging (HSI) is a new technology that obtains spectroscopic information and renders it in image form. This study examined the difference in the spectral reflectance (SR) of gastric tumors and normal mucosa recorded with a hyperspectral camera equipped with HSI technology and attempted to determine the specific wavelength that is useful for the diagnosis of gastric cancer. A total of 104 gastric tumors removed by endoscopic submucosal dissection from 96 patients at Yamaguchi University Hospital were recorded using a hyperspectral camera. We determined the optimal wavelength and the cut-off value for differentiating tumors from normal mucosa to establish a diagnostic algorithm. We also attempted to highlight tumors by image processing using the hyperspectral camera's analysis software. A wavelength of 770 nm and a cut-off value of 1/4 the corrected SR were selected as the respective optimal wavelength and cut-off values. The rates of sensitivity, specificity, and accuracy of the algorithm's diagnostic capability were 71%, 98%, and 85%, respectively. It was possible to enhance tumors by image processing at the 770-nm wavelength. HSI can be used to measure the SR in gastric tumors and to differentiate between tumorous and normal mucosa.

An accurate prognostic staging system for hepatocellular carcinoma patients after curative hepatectomy.

The aim of this study was to develop an accurate predictive system for prognosis of hepatocellular carcinoma (HCC) patients after hepatectomy. We pooled data of clinicopathological features of 234 HCC patients who underwent curative hepatectomy. On the basis of the pooled data, we established a simple predictive staging system (PS score) scored by the mathematical product of tumor number and size, and degree of liver function. We compared the prognostic abilities of the PS score (score 0-3) with those of six well-known clinical staging systems. Then, we found that there were significant differences (P<0.05) in both disease-free survival (DFS) and overall survival (OS) between patients with different PS scores (PS score 0 vs. 1; PS score 1 vs. 2), and there was a significant difference in DFS, but not OS, between patients with PS score 2 and those with PS score 3. Moreover, the PS score had smaller values of the Akaike information criterion for both DFS and OS than any of the six well-known clinical staging systems. These results suggest that the PS score serves as a simple, accurate predictor for the prognosis of HCC patients after hepatectomy.