Troponin I2 as a Specific Biomarker for Prediction of Peritoneal Metastasis in Gastric Cancer

Positive peritoneal lavage fluid cytology based on isolation by size of epithelial tumor cells indicates a high risk of peritoneal metastasis

Background

Peritoneal metastasis (PM) is the most prevalent type of metastasis in patients with gastric cancer (GC) and has an extremely poor prognosis. The detection of free cancer cells (FCCs) in the peritoneal cavity has been demonstrated to be one of the worst prognostic factors for GC. However, there is a lack of sensitive detection methods for FCCs in the peritoneal cavity. This study aimed to use a new peritoneal lavage fluid cytology examination to detect FCCs in patients with GC, and to explore its clinical significance on diagnosing of occult peritoneal metastasis (OPM) and prognosis.

Methods

Peritoneal lavage fluid from 50 patients with GC was obtained and processed via the isolation by size of epithelial tumor cells (ISET) method. Immunofluorescence and fluorescence in situ hybridization (FISH) were used to identify FCCs expressing chromosome 8 (CEP8), chromosome 17 (CEP17), and epithelial cell adhesion molecule (EpCAM).

Results

Using a combination of the ISET platform and immunofluorescence-FISH, the detection of FCCs was higher than that by light microscopy (24.0% vs. 2.0%). Samples were categorized into positive and negative groups, based on the expressions of CEP8, CEP17, and EpCAM. Statistically significant relationships were demonstrated between age (P = 0.029), sex (P = 0.002), lymphatic invasion (P = 0.001), pTNM stage (P = 0.001), and positivity for FCCs. After adjusting for covariates, patients with positive FCCs had lower progression-free survival than patients with negative FCCs.

Conclusion

The ISET platform highly enriched nucleated cells from peritoneal lavage fluid, and indicators comprising EpCAM, CEP8, and CEP17 confirmed the diagnosis of FCCs. As a potential detection method, it offers an opportunity for early intervention of OPM and an extension of patient survival.

Transcriptomics-based liquid biopsy panel for early non-invasive identification of peritoneal recurrence and micrometastasis in locally advanced gastric cancer

BACKGROUND

This study aimed to develop a novel six-gene expression biomarker panel to enhance the early detection and risk stratification of peritoneal recurrence and micrometastasis in locally advanced gastric cancer (LAGC).

METHODS

We used genome-wide transcriptome profiling and rigorous bioinformatics to identify a six-gene expression biomarker panel. This panel was validated across multiple clinical cohorts using both tissue and liquid biopsy samples to predict peritoneal recurrence and micrometastasis in patients with LAGC.

RESULTS

Through genome-wide expression profiling, we identified six mRNAs and developed a risk prediction model using 196 samples from a surgical specimen training cohort. This model, incorporating a 6-mRNA panel with clinical features, demonstrated high predictive accuracy for peritoneal recurrence in gastric cancer patients, with an AUC of 0.966 (95% CI: 0.944-0.988). Transitioning from invasive surgical or endoscopic biopsy to noninvasive liquid biopsy, the model retained its predictive efficacy (AUC = 0.963; 95% CI: 0.926-1.000). Additionally, the 6-mRNA panel effectively differentiated patients with or without peritoneal metastasis in 95 peripheral blood specimens (AUC = 0.970; 95% CI: 0.936-1.000) and identified peritoneal micrometastases with a high efficiency (AUC = 0.941; 95% CI: 0.874-1.000).

CONCLUSIONS

Our study provides a novel gene expression biomarker panel that significantly enhances early detection of peritoneal recurrence and micrometastasis in patients with LAGC. The RSA model's predictive capability offers a promising tool for tailored treatment strategies, underscoring the importance of integrating molecular biomarkers with clinical parameters in precision oncology.

Predicting peritoneal recurrence in gastric cancer with serosal invasion using a pathomics nomogram

Peritoneal recurrence is the most frequent and lethal recurrence pattern in gastric cancer (GC) with serosal invasion after radical surgery. However, current evaluation methods are not adequate for predicting peritoneal recurrence in GC with serosal invasion. Emerging evidence shows that pathomics analyses could be advantageous for risk stratification and outcome prediction. Herein, we propose a pathomics signature composed of multiple pathomics features extracted from digital hematoxylin and eosin-stained images. We found that the pathomics signature was significantly associated with peritoneal recurrence. A competing-risk pathomics nomogram including carbohydrate antigen 19-9 level, depth of invasion, lymph node metastasis, and pathomics signature was developed for predicting peritoneal recurrence. The pathomics nomogram had favorable discrimination and calibration. Thus, the pathomics signature is a predictive indicator of peritoneal recurrence, and the pathomics nomogram may provide a helpful reference for predicting an individual's risk in peritoneal recurrence of GC with serosal invasion.

Identification of immunocell infiltrates and effective diagnostic biomarkers in laryngeal carcinoma

Laryngeal cancer (LC) is a malignant tumor that occurs in the head and neck. Laryngeal cancer is one of the most common cancers of the neck and head, and its prognosis has always been poor. The incidence of LC increased gradually and showed an early rising trend. Laryngeal cancer is rarely studied in relation to immunity, Malignant tumors will change the state of the human body in various ways to adapt to their own survival and avoid the immune system. This study aims to explore the immune molecular mechanism of laryngeal cancer through bioinformatics analysis. The gene expression data was downloaded for 3 microarray datasets: GSE27020, GSE59102, and GSE51985. CIBERSORT algorithm was performed to evaluate immune cell infiltration in tissues between LC and healthy control (HC). Differentially expressed genes (DEGs) were screened. Functional correlation of DEGs were analyzed by Gene Ontology, Gene Set Enrichment Analysis and Kyoto encyclopedia of genes and genomes. Candidate biomarkers were identified by cytoHubba of Cytoscape. Spearman correlations between the above biomarkers and infiltrating immune cells were explored using R software analysis. The immune cell types of LC and HC were significantly different. Twenty-one DEGs were obtained by cross-screening. The function of DEGs is closely related to the number of immune cells. Five central genes (TNNT3, TNNI2, Desmin, matrix metallopeptidase 9 and cytotoxic T lymphocyte antigen 4) were screened. The HUB gene was demonstrated to have the ability to diagnose LC and HC with good specificity and sensitivity. The correlation between immune cells and biomarkers showed that hub gene was positively correlated with macrophages and dendritic cells, and negatively correlated with CD4 + T cell. TNNT3, TNNI2, Desmin, matrix metallopeptidase 9 and cytotoxic T lymphocyte antigen 4 can be used as diagnostic biomarker for LC. Macrophages, dendritic cells and CD4 + T cell may participate in the occurrence and development of LC.

Development and validation of nomogram of peritoneal metastasis in gastric cancer based on simplified clinicopathological features and serum tumor markers

BACKGROUND

Peritoneal metastasis (PM) is not uncommon in patients with gastric cancer(GC), which affects clinical treatment decisions, but the relevant examination measures are not efficiently detected. Our goal was to develop a clinical radiomics nomogram to better predict peritoneal metastases.

METHODS

A total of 3480 patients from 2 centers were divided into 1 training, 1 internal validation, and 1 external validation cohort(1949 in the internal training set, 704 in the validation set, and 827 in the external validation cohort) with clinicopathologically confirmed GC. We recruited 11 clinical factors, including age, sex, smoking status, tumor size, differentiation, Borrmann type, location, clinical T stage, and serum tumor markers (STMs) comprising carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4), and carcinoembryonic antigen (CEA), to develop the radiomics nomogram. For clinical predictive feature selection and the establishment of clinical models, statistical methods of analysis of variance (ANOVA), relief and recursive feature elimination (RFE) and logistic regression analysis were used. To develop combined predictive models, tumor diameter, type, and location, clinical T stage and STMs were finally selected. The discriminatory ability of the nomogram to predict PM was evaluated by the area under the receiver operating characteristic curve(AUC), and decision curve analysis (DCA) was conducted to evaluate the clinical usefulness of the nomogram.

RESULTS

The AUC of the clinical models was 0.762 in the training cohorts, 0.772 in the internal validation cohort, and 0.758 in the external validation cohort. However, when combined with STMs, the AUC was improved to 0.806, 0.839 and 0.801, respectively. DCA showed that the combined nomogram was of good clinical evaluation value to predict PM in GC.

CONCLUSIONS

The present study proposed a clinical nomogram with a combination of clinical risk factors and radiomics features that can potentially be applied in the individualized preoperative prediction of PM in GC patients.

Gamma-aminobutyric Acid Type A Receptor Subunit Delta as a Potential Therapeutic Target in Gastric Cancer

BACKGROUND

Novel therapeutic targets are needed to improve the poor prognosis of patients with advanced gastric cancer. The aim of this study was to identify a novel therapeutic target for the treatment of GC and to investigate the potential therapeutic value of an antibody raised against the target.

METHODS

We identified gamma-aminobutyric acid type A receptor subunit delta as a candidate therapeutic target by differential transcriptome analysis of metastatic GC tissue and adjacent nontumor tissues. GABRD mRNA levels were analyzed in 230 pairs of gastric tissue by quantitative reverse-transcription polymerase chain reaction. GABRD function was assessed in proliferation, invasion, and apoptosis assays in human GC cell lines expressing control or GABRD-targeting small interfering RNA (siRNA). Mouse anti-human polyclonal GABRD antibodies were generated and assessed for inhibition of GC cell growth in vitro and in a mouse xenograft model of peritoneal GC dissemination.

RESULTS

High GABRD mRNA expression level in primary human GC tissue was associated with poor prognosis. Expression of siGABRD in GC cell lines significantly decreased cell proliferation and invasion and increased apoptosis compared with control siRNA expression. Anti-GABRD polyclonal antibodies inhibited GC cell proliferation in vitro and decreased peritoneal tumor nodule size in the mouse xenograft model.

CONCLUSION

We identified GABRD as novel regulator of GC cell growth and function. GABRD is upregulated in GC tissue and is associated with poor prognosis, suggesting that it may be a potential therapeutic target for GC.

Clinical Value of PET.CT Based on Big Data in Colorectal and Peritoneal Metastatic Cancer

This study focuses on the evaluation of the clinical utility of PET-CT imaging in peritoneal metastases and colorectal cancer. One hundred patients with colorectal peritoneal metastases, who underwent whole-body PET-CT imaging from January 2015 to December 2019, were selected as the experimental group, and 20 healthy individuals were selected as the control group. The SUVmax of the two groups of patients was 5.73 ± 3.84 and 2.70 ± 2.32, respectively, and the difference was statistically significant. The SUVmax AUC was 0.720, and the AUC of serum AFP, CEA, CA125, and CA199 were 0.596, 0.677, 0.642, and 0.696, respectively. Conclusion. 100 patients with colorectal and peritoneal metastatic cancer underwent PET/CT examination. The follow-up or other imaging examinations confirmed the diagnosis. Analysis of the ROC curve in this study found that with a peritoneal SUVmax> 3.2 as the diagnostic index for colorectal peritoneal metastatic cancer, the sum of sensitivity and specificity reached the maximum.

Clostridium novyi’s Alpha-Toxin Changes Proteome and Phosphoproteome of HEp-2 Cells

C. novyi type A produces the alpha-toxin (TcnA) that belongs to the large clostridial glucosylating toxins (LCGTs) and is able to modify small GTPases by N-acetylglucosamination on conserved threonine residues. In contrast, other LCGTs including Clostridioides difficile toxin A and toxin B (TcdA; TcdB) modify small GTPases by mono-o-glucosylation. Both modifications inactivate the GTPases and cause strong effects on GTPase-dependent signal transduction pathways and the consequent reorganization of the actin cytoskeleton leading to cell rounding and finally cell death. However, the effect of TcnA on target cells is largely unexplored. Therefore, we performed a comprehensive screening approach of TcnA treated HEp-2 cells and analyzed their proteome and their phosphoproteome using LC-MS-based methods. With this data-dependent acquisition (DDA) approach, 5086 proteins and 9427 phosphosites could be identified and quantified. Of these, 35 proteins were found to be significantly altered after toxin treatment, and 1832 phosphosites were responsive to TcnA treatment. By analyzing the TcnA-induced proteomic effects of HEp-2 cells, 23 common signaling pathways were identified to be altered, including Actin Cytoskeleton Signaling, Epithelial Adherens Junction Signaling, and Signaling by Rho Family GTPases. All these pathways are also regulated after application of TcdA or TcdB of C. difficile. After TcnA treatment the regulation on phosphorylation level was much stronger compared to the proteome level, in terms of both strength of regulation and the number of regulated phosphosites. Interestingly, various signaling pathways such as Signaling by Rho Family GTPases or Integrin Signaling were activated on proteome level while being inhibited on phosphorylation level or vice versa as observed for the Role of BRCA1 in DNA Damage Response. ZIP kinase, as well as Calmodulin-dependent protein kinases IV & II, were observed as activated while Aurora-A kinase and CDK kinases tended to be inhibited in cells treated with TcnA based on their substrate regulation pattern.

Novel CT based clinical nomogram comparable to radiomics model for identification of occult peritoneal metastasis in advanced gastric cancer

BACKGROUND

Occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC) patients remains a major diagnostic challenge. The aim of this study was to develop novel predictive models for identification of OPM in AGCs.

METHOD

A total of 810 patients with primary AGCs from two hospitals were retrospectively selected and divided into training (n = 393), internal validation (n = 215) and external validation cohorts (n = 202). CT based machine learning models were built and tested to predict the OPM status in AGCs., which are 1) Radiomic signatures: using venous CT imaging features, 2) Clinical models: integrating tumor location, differentiation and extent of serosal exposure, and 3) Radiomics models: combining of radiomic signature, tumor location and tumor differentiation.

RESULT

Total incidence of OPM was 8.27% (67/810). Clinical models yielded comparable classification accuracy with the corresponding radiomics models with similar AUCs (0.902-0.969 vs. 0.896-0.975) while the radiomic signatures showed relatively low AUCs of 0.863-0.976. In the case where the specificity is higher than 90%, the overall sensitivity of clinical model and radiomics model for OPM positive cases was 76.1% (51/67) and 82.1% (55/67). A nomogram based on the logistic clinical model was drawn to facilitate the usage and verification of the clinical model.

CONCLUSION

Both the novel CT based clinical nomogram and radiomics model provide promising method to yield high accuracy in identification of OPM in AGC patients.

Integration of Genomic Biology Into Therapeutic Strategies of Gastric Cancer Peritoneal Metastasis

The peritoneum is a common site of metastasis in advanced gastric cancer (GC). Diagnostic laparoscopy is now routinely performed as part of disease staging, leading to an earlier diagnosis of synchronous peritoneal metastasis (PM). The biology of GCPM is unique and aggressive, leading to a dismal prognosis. These tumors tend to be resistant to traditional systemic therapy, and yet, this remains the current standard-of-care recommended by most international clinical guidelines. As this is an area of unmet clinical need, several translational studies and clinical trials have focused on addressing this specific disease state. Advances in genomic sequencing and molecular profiling have revealed several promising therapeutic targets and elucidated novel biology, particularly on the role of the surrounding tumor microenvironment in GCPM. Peritoneal-specific clinical trials are being designed with a combination of locoregional therapeutic strategies with systemic therapy. In this review, we summarize the new knowledge of cancer biology, advances in surgical techniques, and emergence of novel therapies as an integrated strategy emerges to address GCPM as a distinct clinical entity.

Relationship of ERCC5 genetic polymorphisms with metastasis and recurrence of gastric cancer

OBJECTIVE

This study aims to explore the role of ERCC5 genetic polymorphisms in gastric cancer and their relationship with metastasis and recurrence of gastric cancer.

METHODS

A total of 200 patients with gastric cancer and 133 healthy subjects were enrolled. MassARRAY iPLEX® technology was used to genotype ERCC5 rs2016073, rs751402, rs2094258, rs2296147, and rs2296148 between the control group and the gastric cancer group. The relationship of ERCC5 genetic polymorphisms with metastasis and recurrence of gastric cancer was explored. The differences in sociodemographic characteristics between patients with gastric cancer and control subjects were compared using the chi-square test. The genetic loci between the control group and the gastric cancer group were analyzed by the chi-square test.

RESULTS

There was no significant difference in the metastasis of gastric cancer between males and females (p=0.628), but there was a significant difference in the metastasis of gastric cancer (p=0.005). Patients aged ≤60 years and >60 years showed no significant difference in the metastasis of gastric cancer (p=0.420), but there was a significant difference in the recurrence of gastric cancer (p<0.001). The loci rs2016073, rs751402, and rs2094258 in the gastric cancer group showed no significant differences compared with the control group (p=0.194), and the loci rs2296147 and rs2296148 showed significant differences.

CONCLUSIONS

The results suggested that ERCC5 polymorphisms (e.g., rs201607, rs751402, rs2094258, rs2296147, and rs2296148) may be associated with metastasis and recurrence of gastric cancer.

SYT8 promotes pancreatic cancer progression via the TNNI2/ERRα/SIRT1 signaling pathway

Pancreatic cancer is a highly lethal malignancy due to failures of early detection and high metastasis in patients. While certain genetic mutations in tumors are associated with severity, the molecular mechanisms responsible for cancer progression are still poorly understood. Synaptotagmin-8 (SYT8) is a membrane protein that regulates hormone secretion and neurotransmission, and its expression is positively regulated by the promoter of the insulin gene in pancreatic islet cells. In this study, we identified a previously unknown role of SYT8 in altering tumor characteristics in pancreatic cancer. SYT8 levels were upregulated in patient tumors and contributed towards increased cell proliferation, migration, and invasion in vitro and in vivo. Increased SYT8 expression also promoted tumor metastasis in an in vivo tumor metastasis model. Furthermore, we showed that SYT8-mediated increase in tumorigenicity was regulated by SIRT1, a protein deacetylase previously known to alter cell metabolism in pancreatic lesions. SIRT1 expression was altered by orphan nuclear receptor ERRα and troponin-1 (TNNI2), resulting in cell proliferation and migration in an SYT8-dependent manner. Together, we identified SYT8 to be a central regulator of tumor progression involving signaling via the SIRT1, ERRα, and TNNI2 axis. This knowledge may provide the basis for the development of therapeutic strategies to restrict tumor metastasis in pancreatic cancer.

Comparison of [68 Ga]Ga-FAPI-04 and [18F]-FDG for the detection of primary and metastatic lesions in patients with gastric cancer: a bicentric retrospective study

INTRODUCTION

The low sensitivity of [¹⁸F]-fluorodeoxyglucose ([¹⁸F]-FDG) for the diagnosis of gastric cancer limits its application. In this study, we aimed to investigate the potential advantage of [⁶⁸ Ga]Ga-FAPI-04 over [¹⁸F]-FDG in the evaluation of gastric cancer.

METHODS

This was a bicentric retrospective analysis of a prospective parent study (clinical trial: HS-KY-2020-826 (Huashan Hospital) and DF-2020-102 (Shanghai East Hospital)). Thirty-eight patients with gastric cancer (31 with adenocarcinoma and 7 with signet ring cell carcinoma) were included in this study. All of the participants underwent [⁶⁸ Ga]Ga-FAPI-04 and [¹⁸F]-FDG imaging by positron emission tomography (PET)/computed tomography (CT) or PET/magnetic resonance (MR). The scans were interpreted by two experienced nuclear medicine physicians, and the maximum standardized uptake value (SUV_max) was calculated. Histopathological findings obtained from biopsy or resected surgical specimens were used as a reference for the final diagnosis.

RESULTS

For the detection of primary gastric cancer, the sensitivities of [⁶⁸ Ga]Ga-FAPI-04 PET and [¹⁸F]-FDG PET were 100% (38/38) and 82% (31/38), respectively (P = 0.016). Four cases of adenocarcinoma and three cases of signet ring cell carcinoma were missed by [¹⁸F]-FDG PET. The mean SUV_max of [⁶⁸ Ga]Ga-FAPI-04 in tumours greater than 4 cm (11.0 ± 4.5) was higher than that in tumours less than 4 cm (4.5 ± 3.2) (P = 0.0015). The mean SUV_max of [⁶⁸ Ga]Ga-FAPI-04 was higher in T2-4 tumours (9.7 ± 4.4) than in T1 tumours (3.1 ± 1.5) (P = 0.0002). For the detection of metastatic lesions, the sensitivities of [⁶⁸ Ga]Ga-FAPI-04 PET and [¹⁸F]-FDG PET in 10 patients with regional lymph node metastasis and distant metastasis were 6/10 and 5/10, respectively.

CONCLUSION

In this selected cohort, [⁶⁸ Ga]Ga-FAPI-04 PET had a superior detection rate than [¹⁸F]-FDG PET for primary gastric cancer. [⁶⁸ Ga]Ga-FAPI-04 PET could provide better performance with regard to gastric cancer diagnosis and staging. Prospective clinical trials are warranted.

Identification of DNA methylation biomarkers for risk of liver metastasis in early-stage colorectal cancer

Background

Liver metastases can occur even in CRC patients who underwent curative surgery. While evidence suggested that adjuvant chemotherapy can help to reduce the occurrence of liver metastases for certain patients, it is not a recommended routine as the side effects outweigh the potential benefits, especially in Stage II CRC patients. This study aims to construct a model for predicting liver metastasis risk using differential methylation signals in primary CRC tumors, which can facilitate the decision for adjuvant chemotherapy.

Methods

Fifty-nine stage I/II and IV CRC patients were enrolled. Primary tumor, adjacent normal tissue, and metastatic tumor tissues were subject to targeted bisulfite sequencing for DNA methylation. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to identify potential DMRs for predicting liver metastasis of CRC.

Results

We identified a total of 241,573 DMRs by comparing the DNA methylation profile of primary tumors of stage II patients who developed metastasis to those who were metastasis-free during the follow up period. 213 DMRs were associated with poor prognosis, among which 182 DMRS were found to be hypermethylated in the primary tumor of patients with metastases. Furthermore, by using the LASSO regression model, we identified 23 DMRs that contributed to a high probability of liver metastasis of CRC. The leave-one-out cross validation (LOOCV) was used to evaluate model predictive performance at an AUC of 0.701. In particular, 7 out of those 23 DMRs were found to be in the promoter region of genes that were previously reported prognostic biomarkers in diverse tumor types, including TNNI2, PAX8, GUF1, KLF4, EVI2B, CEP112, and long non-coding RNA AC011298. In addition, the model was also able to distinguish metastases of different sites (liver or lung) at an AUC of 0.933.

Conclusion

We have identified DNA methylation biomarkers associated with the risk of cancer liver metastasis in early-stage CRC patients. A risk prediction model based on those epigenetic markers was proposed for outcome assessment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01108-3.

Transcriptomic Profiling Identifies a Risk Stratification Signature for Predicting Peritoneal Recurrence and Micrometastasis in Gastric Cancer

PURPOSE

Gastric cancer peritoneal carcinomatosis is fatal. Delay in detection of peritoneal metastases contributes to high mortality, highlighting the need to develop biomarkers that can help identify patients at high risk for peritoneal recurrence or metastasis.

EXPERIMENTAL DESIGN

We performed a systematic discovery and validation for the identification of peritoneal recurrence prediction and peritoneal metastasis detection biomarkers by analyzing expression profiling datasets from 249 patients with gastric cancer, followed by analysis of 426 patients from three cohorts for clinical validation.

RESULTS

Genome-wide expression profiling identified a 12-gene panel for robust prediction of peritoneal recurrence in patients with gastric cancer (AUC = 0.95), which was successfully validated in a second dataset (AUC = 0.86). Examination of 216 specimens from a training cohort allowed us to establish a six gene-based risk-prediction model [AUC = 0.72; 95% confidence interval (CI): 0.66-0.78], which was subsequently validated in an independent cohort of 111 patients with gastric cancer (AUC = 0.76; 95% CI: 0.67-0.83). In both cohorts, combining tumor morphology and depth of invasion further improved the predictive accuracy of the prediction model (AUC = 0.84). Thereafter, we evaluated the performance of the identical six-gene panel for its ability to detect peritoneal metastasis by analyzing 210 gastric cancer specimens (prior 111 patients plus additional 99 cases), which discriminated patients with and without peritoneal metastasis (AUC = 0.72). Finally, our biomarker panel was also remarkably effective for identifying peritoneal micrometastasis (AUC = 0.72), and its diagnostic accuracy was significantly enhanced when depth of invasion was included in the model (AUC = 0.85).

CONCLUSIONS

Our novel transcriptomic signature for risk stratification and identification of high-risk patients with peritoneal carcinomatosis might serve as an important clinical decision making in patients with gastric cancer.

Differential DNA Methylation in Prostate Tumors from Puerto Rican Men

In 2020, approximately 191,930 new prostate cancer (PCa) cases are estimated in the United States (US). Hispanic/Latinos (H/L) are the second largest racial/ethnic group in the US. This study aims to assess methylation patterns between aggressive and indolent PCa including DNA repair genes along with ancestry proportions. Prostate tumors classified as aggressive (n = 11) and indolent (n = 13) on the basis of the Gleason score were collected. Tumor and adjacent normal tissue were annotated on H&E (Haemotoxylin and Eosin) slides and extracted by macro-dissection. Methylation patterns were assessed using the Illumina 850K DNA methylation platform. Raw data were processed using the Bioconductor package. Global ancestry proportions were estimated using ADMIXTURE (k = 3). One hundred eight genes including AOX1 were differentially methylated in tumor samples. Regarding the PCa aggressiveness, six hypermethylated genes (RREB1, FAM71F2, JMJD1C, COL5A3, RAE1, and GABRQ) and 11 hypomethylated genes (COL9A2, FAM179A, SLC17A2, PDE10A, PLEKHS1, TNNI2, OR51A4, RNF169, SPNS2, ADAMTSL5, and CYP4F12) were identified. Two significant differentially methylated DNA repair genes, JMJD1C and RNF169, were found. Ancestry proportion results for African, European, and Indigenous American were 24.1%, 64.2%, and 11.7%, respectively. The identification of DNA methylation patterns related to PCa in H/L men along with specific patterns related to aggressiveness and DNA repair constitutes a pivotal effort for the understanding of PCa in this population.

Predicting postoperative peritoneal metastasis in gastric cancer with serosal invasion using a collagen nomogram

Accurate prediction of peritoneal metastasis for gastric cancer (GC) with serosal invasion is crucial in clinic. The presence of collagen in the tumour microenvironment affects the metastasis of cancer cells. Herein, we propose a collagen signature, which is composed of multiple collagen features in the tumour microenvironment of the serosa derived from multiphoton imaging, to describe the extent of collagen alterations. We find that a high collagen signature is significantly associated with a high risk of peritoneal metastasis (P < 0.001). A competing-risk nomogram including the collagen signature, tumour size, tumour differentiation status and lymph node metastasis is constructed. The nomogram demonstrates satisfactory discrimination and calibration. Thus, the collagen signature in the tumour microenvironment of the gastric serosa is associated with peritoneal metastasis in GC with serosal invasion, and the nomogram can be conveniently used to individually predict the risk of peritoneal metastasis in GC with serosal invasion after radical surgery.

Radiomics Nomogram for Prediction of Peritoneal Metastasis in Patients With Gastric Cancer

Objective: The aim of this study is to evaluate whether radiomics imaging signatures based on computed tomography (CT) could predict peritoneal metastasis (PM) in gastric cancer (GC) and to develop a nomogram for preoperative prediction of PM status.

Methods: We collected CT images of pathological T4 gastric cancer in 955 consecutive patients of two cancer centers to analyze the radiomics features retrospectively and then developed and validated the prediction model built from 292 quantitative image features in the training cohort and two validation cohorts. Lasso regression model was applied for selecting feature and constructing radiomics signature. Predicting model was developed by multivariable logistic regression analysis. Radiomics nomogram was developed by the incorporation of radiomics signature and clinical T and N stage. Calibration, discrimination, and clinical usefulness were used to evaluate the performance of the nomogram.

Results: In training and validation cohorts, PM status was associated with the radiomics signature significantly. It was found that the radiomics signature was an independent predictor for peritoneal metastasis in multivariable logistic analysis. For training and internal and external validation cohorts, the area under the receiver operating characteristic curves (AUCs) of radiomics signature for predicting PM were 0.751 (95%CI, 0.703–0.799), 0.802 (95%CI, 0.691–0.912), and 0.745 (95%CI, 0.683–0.806), respectively. Furthermore, for training and internal and external validation cohorts, the AUCs of radiomics nomogram for predicting PM were 0.792 (95%CI, 0.748–0.836), 0.870 (95%CI, 0.795–0.946), and 0.815 (95%CI, 0.763–0.867), respectively.

Conclusions: CT-based radiomics signature could predict peritoneal metastasis, and the radiomics nomogram can make a meaningful contribution for predicting PM status in GC patient preoperatively.

Predicting Peritoneal Dissemination of Gastric Cancer in the Era of Precision Medicine: Molecular Characterization and Biomarkers

Gastric cancer (GC) is a leading cause of worldwide cancer-related death. Being a highly heterogeneous disease, the current treatment of GC has been suboptimal due to the lack of subtype-dependent therapies. Peritoneal dissemination (PD) is a common pattern of GC metastasis associated with poor prognosis. Therefore, it is urgently necessary to identify patients at high risk of PD. PD is found to be associated with Lauren diffuse type GC. Molecular profiling of GC, especially diffuse type GC, has been utilized to identify molecular alterations and has given rise to various molecular classifications, shedding light on the underlying mechanism of PD and enabling identification of patients at higher PD risk. In addition, a series of diagnositc and prognostic biomarkers of PD from serum, peritoneal lavages and primary GCs have been reported. This comprehensive review summarizes findings on the multi-omic characteristics of diffuse type GC, the clinical significance of updating molecular classifications of GC in association with PD risk and research advances in PD-associated biomarkers.

High Level of Legumain Was Correlated With Worse Prognosis and Peritoneal Metastasis in Gastric Cancer Patients

Background: Accumulating evidence has demonstrated that legumain (LGMN) is abnormally expressed in several malignancies and functions as an oncogene. However, the association between LGMN and gastric cancer (GC) has not yet been fully elucidated. In this study, we performed a comprehensive analysis of the role of LGMN in clinicopathologic characteristics and survival of GC patients.

Methods: The study had two patient cohorts, The Cancer Genome Atlas (TCGA) cohort and the Zhongshan Hospital cohort, both of which were used to analyze the role of LGMN in GC samples. The relationship between LGMN and clinicopathologic characteristics was determined by the Chi-square test and logistic regression analysis. The Kaplan–Meier method and Cox proportional hazards regression analysis were conducted to investigate the prognostic role of LGMN in GC patients. Moreover, a nomogram was constructed based on the factors that were independently associated with peritoneal metastasis. Finally, the gene set enrichment analysis (GSEA) was conducted to explore the underlying pathways through which LGMN was involved in GC progression.

Results: The mRNA and protein levels of LGMN were significantly upregulated in GC tissues, especially for diffuse-type GC. High level of LGMN was independently associated with poor prognosis in both TCGA and Zhongshan cohorts. Further analysis showed that increased protein level of LGMN was related to peritoneal metastasis in GC patients. In a nomogram model, the LGMN expression could help predict the possibility of peritoneal metastasis in GC patients. LGMN was a strong determinant for prediction of peritoneal metastasis. GC patients with high LGMN expression tended to have worse survival together with more frequent diffuse-type tumors and increased risk of peritoneal metastasis. The GSEA results showed that focal adhesion, ecm receptor interaction, cell adhesion molecules cams, TGF-β signaling pathway, JAK-STAT signaling pathway, gap junction, etc. were differentially enriched in the phenotype with high LGMN expression.

Conclusion: LGMN was an independent prognostic factor for OS in GC patients. Increased expression of LGMN was significantly associated with peritoneal metastasis. The nomogram based on LGMN might guide the clinical decisions for patients with GC.

Slow skeletal muscle troponin T, titin and myosin light chain 3 are candidate prognostic biomarkers for Ewing's sarcoma

Ewing's sarcoma (ES) is a common malignant bone tumor in children and adolescents. Although great efforts have been made to understand the pathogenesis and development of ES, the underlying molecular mechanism remains unclear. The present study aimed to identify new key genes as potential biomarkers for the diagnosis, targeted therapy or prognosis of ES. mRNA expression profile chip data sets GSE17674, GSE17679 and GSE45544 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened using the R software limma package, and functional and pathway enrichment analyses were performed using the enrichplot package and GSEA software. The NetworkAnalyst online tool, as well as Cytoscape and its plug-ins cytoHubba and NetworkAnalyzer, were used to construct a protein-protein interaction network (PPI) and conduct module analysis to screen key (hub) genes. LABSO COX regression and overall survival (OS) analysis of the Hub genes were performed. A total of 211 DEGs were obtained by integrating and analyzing the three data sets. The functions and pathways of the DEGs were mainly associated with the regulation of small-molecule metabolic processes, cofactor-binding, amino acid, proteasome and ribosome biosynthesis in eukaryotes, as well as the Rac1, cell cycle and P53 signaling pathways. A total of one important module and 20 hub genes were screened from the PPI network using the Maximum Correlation Criteria algorithm of cytoHubba. LASSO COX regression results revealed that titin (TTN), fast skeletal muscle troponin T, skeletal muscle actin α-actin, nebulin, troponin C type 2 (fast), myosin light-chain 3 (MYL3), slow skeletal muscle troponin T (TNNT1), myosin-binding protein C1 slow-type, tropomyosin 3 and myosin heavy-chain 7 were associated with prognosis in patients with ES. The Kaplan-Meier curves demonstrated that high mRNA expression levels of TNNT1 (P<0.001), TTN (P=0.049), titin-cap (P=0.04), tropomodulin 1 (P=0.011), troponin I2 fast skeletal type (P=0.021) and MYL3 (P=0.017) were associated with poor OS in patients with ES. In conclusion, the DEGs identified in the present study may be key genes in the pathogenesis of ES, three of which, namely TNNT1, TTN and MYL3, may be potential prognostic biomarkers for ES.

Incorporating molecular biomarkers into clinical practice for gastric cancer

Introduction: Gastric cancer is one of the most common causes of cancer-related mortality worldwide. To improve clinical outcomes, it is critical to develop appropriate approaches to diagnosis and treatment. Biomarkers have numerous potential clinical applications, including screening, assessing risk, determining prognosis, monitoring recurrence, and predicting response to treatment. Furthermore, biomarkers may contribute to the development of effective therapies. Areas covered: Here we review recent progress in exploiting GC-specific biomarkers such as protein-coding genes, microRNAs, long noncoding RNAs, and methylated gene promoters. Expert opinion: The development of biomarkers for diagnosing and monitoring gastric cancer and for individualizing therapeutic targets shows great promise for improving gastric cancer management.