An algorithm-based meta-analysis of genome- and proteome-wide data identifies a combination of potential plasma biomarkers for colorectal cancer

Pan-Cancer Analysis of P3H1 and Experimental Validation in Renal Clear Cell Carcinoma

Prolyl 3-hydroxylase 1 (P3H1) has been implicated in cancer development, but no pan-cancer analysis has been conducted on P3H1. In this study, for the first time, aspects associated with P3H1, such as the mRNA expression, any mutation, promoter methylation, and prognostic significance, the relationship between P3H1 and clinicopathological parameters, drug sensitivity, and immune cell infiltration were investigated by searching several databases including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), cBioPortal, and The Tumor Immune Evaluation Resource (TIMER2.0) using bioinformatics tools. The findings indicate significant differential expression of P3H1 in most tumors when compared to normal tissues, with a strong association with clinical prognosis. A pan-cancer Cox regression analysis revealed that high P3H1 expression is significantly associated with low overall survival in patients with brain lower grade glioma, kidney clear cell carcinoma, adrenocortical cancer, liver hepatocellular carcinoma, mesothelioma, sarcoma, uveal melanoma, bladder urothelial carcinoma, kidney papillary cell carcinoma, kidney chromophobe, thymoma, and thyroid carcinoma. A negative correlation was observed between P3H1 DNA methylation and its expression. P3H1 is significantly associated with infiltrating cells, immune-related genes, tumor mutation burden, microsatellite instability, and mismatch repair. Finally, A significant correlation was found between P3H1 expression and sensitivity to nine drugs. Thus, enhanced P3H1 expression is associated with poor prognosis in a variety of tumors, which may be due to its role in tumor immune regulation and tumor microenvironment. This pan-cancer analysis provides insight into the function of P3H1 in tumorigenesis of different cancers and provides a theoretical basis for further in-depth studies to follow.

Data-driven decision-making for precision diagnosis of digestive diseases

Modern omics technologies can generate massive amounts of biomedical data, providing unprecedented opportunities for individualized precision medicine. However, traditional statistical methods cannot effectively process and utilize such big data. To meet this new challenge, machine learning algorithms have been developed and applied rapidly in recent years, which are capable of reducing dimensionality, extracting features, organizing data and forming automatable data-driven clinical decision systems. Data-driven clinical decision-making have promising applications in precision medicine and has been studied in digestive diseases, including early diagnosis and screening, molecular typing, staging and stratification of digestive malignancies, as well as precise diagnosis of Crohn's disease, auxiliary diagnosis of imaging and endoscopy, differential diagnosis of cystic lesions, etiology discrimination of acute abdominal pain, stratification of upper gastrointestinal bleeding (UGIB), and real-time diagnosis of esophageal motility function, showing good application prospects. Herein, we reviewed the recent progress of data-driven clinical decision making in precision diagnosis of digestive diseases and discussed the limitations of data-driven decision making after a brief introduction of methods for data-driven decision making.

Joint Asian Pacific Association of Gastroenterology (APAGE)-Asian Pacific Society of Digestive Endoscopy (APSDE) clinical practice guidelines on the use of non-invasive biomarkers for diagnosis of colorectal neoplasia

Screening for colorectal cancer (CRC) is effective in reducing CRC related mortality. Current screening methods include endoscopy based and biomarker based approaches. This guideline is a joint official statement of the Asian Pacific Association of Gastroenterology (APAGE) and the Asian Pacific Society of Digestive Endoscopy (APSDE), developed in response to the increasing use of, and accumulating supportive evidence for the role of, non-invasive biomarkers for the diagnosis of CRC and its precursor lesions. A systematic review of 678 publications and a two stage Delphi consensus process involving 16 clinicians in various disciplines was undertaken to develop 32 evidence based and expert opinion based recommendations for the use of faecal immunochemical tests, faecal based tumour biomarkers or microbial biomarkers, and blood based tumour biomarkers for the detection of CRC and adenoma. Comprehensive up-to-date guidance is provided on indications, patient selection and strengths and limitations of each screening tool. Future research to inform clinical applications are discussed alongside objective measurement of research priorities. This joint APAGE-APSDE practice guideline is intended to provide an up-to-date guide to assist clinicians worldwide in utilising non-invasive biomarkers for CRC screening; it has particular salience for clinicians in the Asia-Pacific region.

Establishment and Analysis of an Individualized EMT-Related Gene Signature for the Prognosis of Breast Cancer in Female Patients

Background. The current high mortality rate of female breast cancer (BC) patients emphasizes the necessity of identifying powerful and reliable prognostic signatures in BC patients. Epithelial-mesenchymal transition (EMT) was reported to be associated with the development of BC. The purpose of this study was to identify prognostic biomarkers that predict overall survival (OS) in female BC patients by integrating data from TCGA database. Method. We first downloaded the dataset in TCGA and identified gene signatures by overlapping candidate genes. Differential analysis was performed to find differential EMT-related genes. Univariate regression analysis was then performed to identify candidate prognostic variables. We then developed a prognostic model by multivariate analysis to predict OS. Calibration curves, receiver operating characteristics (ROC) curves, $C$ -index, and decision curve analysis (DCA) were used to test the veracity of the prognostic model. Result. In this study, we identified and validated a prognostic model integrating age and six genes (CD44, P3H1, SDC1, COL4A1, TGFβ1, and SERPINE1). $C$ -index values for BC patients were 0.672 (95% CI 0.611–0.732) and 0.692 (95% CI 0.586–0.798) in the training cohort and test set, respectively. The calibration curve and the DCA curve show the good predictive performance of the model. Conclusion. This study offered a robust predictive model for OS prediction in female BC patients and may provide a more accurate treatment strategy and personalized therapy in the future.

PLOD1 acts as a tumor promoter in glioma via activation of the HSF1 signaling pathway

Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 1 (PLOD1) is a collagen-related lysyl hydroxylase and its prognostic value in glioma patients was verified. However, its biological function in glioma has yet to be fully investigated. The PLOD1 mRNA status and clinical significance in gliomas were assessed via the GEPIA database. Overexpression or targeted depletion of PLOD1 was carried out in the human glioma cell line U87 and verified by western blotting. CCK8 and colony formation assays were implemented to examine the impact of PLOD1 on the proliferative and colony-forming phenotypes of U87 cells. Luciferase reporter assays and HSF1-specific pharmacologic inhibitors (KRIBB11) were employed to determine the regulatory relationship between PLOD1 and heat shock factor 1 (HSF1). High expression of PLOD1 was observed in tissue samples of glioblastoma multiforme (GBM) and brain lower-grade glioma (LGG). GEPIA overall survival further demonstrated that both GBM and LGG patients with high PLOD1 displayed worse clinical outcomes compared with those with low PLOD1. Overexpression and targeted depletion of PLOD1 enhanced and suppressed U87 cell proliferation and colony formation, respectively. Luciferase reporter assays showed that PLOD1 significantly enhanced the transcriptional activity of HSF1 in HEK293T cells. PLOD1 deficiency in U87 cells inhibited HSF1-induced survivin accumulation, whereas KRIBB11 also blocked the PLOD1-overexpressing induced survivin expression. An inhibitor of HSF1 signaling events abolished the increased clonogenic potential caused by PLOD1 overexpression in U87 cells. High expression of PLOD1 can increase the proliferation and colony formation of U87 cells by activating the HSF1 signaling pathway. This study suggested PLOD1/HSF1 as an effective therapeutic target for gliomas.

Normalization Method Utilizing Endogenous Proteins for Quantitative Proteomics

We developed a normalization method utilizing the expression levels of a panel of endogenous proteins as normalization standards (EPNS herein). We tested the validity of the method using two sets of tandem mass tag (TMT)-labeled data and found that this normalization method effectively reduced global intensity bias at the protein level. The coefficient of variation (CV) of the overall median was reduced by 55% and 82% on average, compared to the reduction by 72% and 86% after normalization using the upper quartile. Furthermore, we used differential protein expression analysis and statistical learning to identify biomarkers for colorectal cancer from a CPTAC data set. The expression changes of a panel of proteins, including NUP205, GTPBP4, CNN2, GNL3, and S100A11, all of which highly correlate with colorectal cancer. Applying these five proteins as model features, random forest modeling obtained prediction results with the maximum AUC of 0.9998 using EPNS-normalized data, comparing favorably to the AUC of 0.9739 using the raw data. Thus, the normalization method based on EPNS reduced the global intensity bias and is applicable for quantitative proteomic analysis.

KAP1 Is a Chromatin Reader that Couples Steps of RNA Polymerase II Transcription to Sustain Oncogenic Programs

Precise control of the RNA polymerase II (RNA Pol II) cycle, including pausing and pause release, maintains transcriptional homeostasis and organismal functions. Despite previous work to understand individual transcription steps, we reveal a mechanism that integrates RNA Pol II cycle transitions. Surprisingly, KAP1/TRIM28 uses a previously uncharacterized chromatin reader cassette to bind hypo-acetylated histone 4 tails at promoters, guaranteeing continuous progression of RNA Pol II entry to and exit from the pause state. Upon chromatin docking, KAP1 first associates with RNA Pol II and then recruits a pathway-specific transcription factor (SMAD2) in response to cognate ligands, enabling gene-selective CDK9-dependent pause release. This coupling mechanism is exploited by tumor cells to aberrantly sustain transcriptional programs commonly dysregulated in cancer patients. The discovery of a factor integrating transcription steps expands the functional repertoire by which chromatin readers operate and provides mechanistic understanding of transcription regulation, offering alternative therapeutic opportunities to target transcriptional dysregulation.

Targeting P4HA1 with a Small Molecule Inhibitor in a Colorectal Cancer PDX Model

Deposition, remodeling, and signaling of the extracellular matrix facilitate tumor growth and metastasis. Here, we demonstrated that an enzyme, collagen prolyl 4-hydroxylase, alpha polypeptide I (P4HA1), which is involved in collagen synthesis and deposition, had elevated expression in colorectal cancers (CRCs) as compared to normal colonic tissues. The expression of P4HA1 in CRCs was independent of patient's age, race/ethnicity, gender, pathologic stage and grade, tumor location, and microsatellite instability (MSI) and p53 status. By modulating P4HA1 with shRNA, there was a reduction in malignant phenotypes of CRCs, including cell proliferation, colony formation, invasion, migration, and tumor growth, in mice regardless of their p53 and MSI status. Immunoblot analysis of excised xenograft tumors developed from cells with silenced PH4HA1 showed low levels of proliferating cell nuclear antigen. Further, in CRC mouse models, silencing of P4HA1 in HT29 cells resulted in less metastasis to liver and bone. P4HA1 expression was regulated by miR-124, and inhibition of cell growth was noted for CRC cells treated with miR-124. Furthermore, low levels of the transcriptional repressor EZH2 reduced P4HA1 expression in CRC cells. Inhibition of P4HA1 with the small molecule inhibitor diethyl-pythiDC decreased AGO2 and MMP1, which are P4HA1 target molecules, and reduced the malignant phenotypes of CRC cells. Treatment of CRC patient-derived xenografts that exhibit high expression of P4HA1 with diethyl-pythiDC resulted in tumor regression. Thus, the present study shows that P4HA1 contributes to CRC progression and metastasis and that targeting of P4HA1 with diethyl-pythiDC could be an effective therapeutic strategy for aggressive CRCs.

Prolyl 4-hydroxylase alpha 1 protein expression risk-stratifies early stage colorectal cancer

Colorectal cancer (CRC) is one of the most prevalent and lethal malignancies. Especially for early stage CRC, prognostic molecular markers are needed to guide therapy. In this study, we first extracted total proteomes from matched pairs of fresh cancer and benign mucosal tissues from 22 CRC patients. Global proteomic profiling with Fourier transform liquid chromatography-mass spectrometry sequencing and label free quantitation uncovered that P4HA1 (prolyl 4-hydroxylase alpha 1) was overexpressed in CRC relative to benign colonic mucosa. We then investigated expression by immunohistochemical staining with P4HA1-specific antibodies using CRC tissue microarrays. Independent validation cohorts of 599 cases of early stage CRC and 91 cases of late stage CRC were examined. Multivariate and univariate survival analyses revealed that high expression of P4HA1 protein was an independent poor prognostic marker for patients with early stage CRC, especially of the microsatellite stable subtype. Our study provides strong support for P4HA1 as a predictive protein marker for precision diagnostics, therapeutic decision-making, and drug development for early stage colorectal cancer and demonstrates the utility of proteomic profiling to identify novel protein biomarkers.