Genetically-regulated transcriptomics & copy number variation of proctitis points to altered mitochondrial and DNA repair mechanisms in individuals of European ancestry

Inflammatory response in dairy cows caused by heat stress and biological mechanisms for maintaining homeostasis

Climate change increases global temperatures, which is lethal to both livestock and humans. Heat stress is known as one of the various livestock stresses, and dairy cows react sensitively to high-temperature stress. We aimed to better understand the effects of heat stress on the health of dairy cows and observing biological changes. Individual cows were divided into normal (21-22 °C, 50-60% humidity) and high temperature (31-32 °C, 80-95% humidity), respectively, for 7-days. We performed metabolomic and transcriptome analyses of the blood and gut microbiomes of feces. In the high-temperature group, nine metabolites including linoleic acid and fructose were downregulated, and 154 upregulated and 72 downregulated DEGs (Differentially Expressed Genes) were identified, and eighteen microbes including Intestinimonas and Pseudoflavonifractor in genus level were significantly different from normal group. Linoleic acid and fructose have confirmed that associated with various stresses, and functional analysis of DEG and microorganisms showing significant differences confirmed that high-temperature stress is related to the inflammatory response, immune system, cellular energy mechanism, and microbial butyrate production. These biological changes were likely to withstand high-temperature stress. Immune and inflammatory responses are known to be induced by heat stress, which has been identified to maintain homeostasis through modulation at metabolome, transcriptome and microbiome levels. In these findings, heat stress condition can trigger alteration of immune system and cellular energy metabolism, which is shown as reduced metabolites, pathway enrichment and differential microbes. As results of this study did not include direct phenotypic data, we believe that additional validation is required in the future. In conclusion, high-temperature stress contributed to the reduction of metabolites, changes in gene expression patterns and composition of gut microbiota, which are thought to support dairy cows in withstanding high-temperature stress via modulating immune-related genes, and cellular energy metabolism to maintain homeostasis.

Comprehensive prognostic and immune analysis of a glycosylation related risk model in pancreatic cancer

BACKGROUND

Pancreatic cancer (PC) is a malignant tumor with extremely poor prognosis, exhibiting resistance to chemotherapy and immunotherapy. Nowadays, it is ranked as the third leading cause of cancer-related mortality. Glycation is a common epigenetic modification that occurs during the tumor transformation. Many studies have demonstrated a strong correlation between glycation modification and tumor progression. However, the expression status of glycosylation-related genes (GRGs) in PC and their potential roles in PC microenvironment have not been extensively investigated.

METHOD

We systematically integrated RNA sequencing data and clinicopathological parameters of PC patients from TCGA and GTEx databases. A GRGs risk model based on glycosylation related genes was constructed and validated in 60 patients from Pancreatic biobank via RT-PCR. R packages were used to analyze the relationships between GRGs risk scores and overall survival (OS), tumor microenvironment, immune checkpoint, chemotherapy drug sensitivity and tumor mutational load in PC patients. Panoramic analysis was performed on PC tissues. The function of B3GNT8 in PC was detected via in vitro experiments.

RESULTS

In this study, we found close correlations between GRGs risk model and PC patients' overall survival and tumor microenvironment. Multifaceted predictions demonstrated the low-risk cohort exhibits superior OS compared to high-risk counterparts. Meanwhile, the low-risk group was characterized by high immune infiltration and may be more sensitive to immunotherapy or chemotherapy. Panoramic analysis was further confirmed a significant relationship between the GRGs risk score and both the distribution of PC tumor cells as well as CD8 + T cell infiltration. In addition, we also identified a unique glycosylation gene B3GNT8, which could suppress PC progression in vitro and in vivo.

CONCLUSION

We established a GRGs risk model, which could predict prognosis and immune infiltration in PC patients. This risk model may provide a new tool for PC precision treatment.

Multivariate piecewise linear regression model to predict radiosensitivity using the association with the genome-wide copy number variation

Introduction

The search for biomarkers to predict radiosensitivity is important not only to individualize radiotherapy of cancer patients but also to forecast radiation exposure risks. The aim of this study was to devise a machine-learning method to stratify radiosensitivity and to investigate its association with genome-wide copy number variations (CNVs) as markers of sensitivity to ionizing radiation.

Methods

We used the Affymetrix CytoScan HD microarrays to survey common CNVs in 129 fibroblast cell strains. Radiosensitivity was measured by the surviving fraction at 2 Gy (SF2). We applied a dynamic programming (DP) algorithm to create a piecewise (segmented) multivariate linear regression model predicting SF2 and to identify SF2 segment-related distinctive CNVs.

Results

SF2 ranged between 0.1384 and 0.4860 (mean=0.3273 The DP algorithm provided optimal segmentation by defining batches of radio-sensitive (RS), normally-sensitive (NS), and radio-resistant (RR) responders. The weighted mean relative errors (MRE) decreased with increasing the segments' number. The borders of the utmost segments have stabilized after partitioning SF2 into 5 subranges.

Discussion

The 5-segment model associated C-3SFBP marker with the most-RS and C-7IUVU marker with the most-RR cell strains. Both markers were mapped to gene regions (MCC and SLC1A6, respectively). In addition, C-3SFBP marker is also located in enhancer and multiple binding motifs. Moreover, for most CNVs significantly correlated with SF2, the radiosensitivity increased with the copy-number decrease.In conclusion, the DP-based piecewise multivariate linear regression method helps narrow the set of CNV markers from the whole radiosensitivity range to the smaller intervals of interest. Notably, SF2 partitioning not only improves the SF2 estimation but also provides distinctive markers. Ultimately, segment-related markers can be used, potentially with tissues' specific factors or other clinical data, to identify radiotherapy patients who are most RS and require reduced doses to avoid complications and the most RR eligible for dose escalation to improve outcomes.

Emerging glyco-risk prediction model to forecast response to immune checkpoint inhibitors in colorectal cancer

BACKGROUND

Aberrant glycosylation is one of the most common post-translational modifications leading to heterogeneity in colorectal cancer (CRC). This study aims to construct a risk prediction model based on glycosyltransferase to forecast the response to immune checkpoint inhibitors in CRC patients.

METHODS

Based on the TCGA dataset and glycosyltransferase genes, the NMF algorithm and WGCNA were used to identify molecular subtypes and co-expressed genes, respectively. Lasso and multivariate COX regression were used to identify prognostic glycosyltransferase genes and construct a glyco-risk prediction model in CRC patients. Univariate and multivariate Cox regression, Kaplan-Meier, and ROC curves were applied to further verify the prognostic performance of the model in CRC patients in the training and validation sets. We compared the responsiveness of immunotherapy and chemotherapy between the two groups. In vitro experiments and clinical specimens verified the specific function of the key glycosyltransferase genes in CRC.

RESULTS

The CRC cohort was divided into two subtypes with prominent differences in survival based on the well-robust seven-gene glyco-risk prediction model (composed of ALG1L2, HAS1, PYGL, COLGALT2, B3GNT4, POFUT2, and GALNT7). The nomograms based on the risk model could predict the prognosis of CRC patients independently of other clinicopathologic characteristics. Our prediction model showed a better overall prediction performance than other models. Compared with the low-risk group, the high-risk CRC patients showed a lower immune infiltration state, but a higher TMB and a lower response to anti-PD-1, anti-PD-L1, and anti-CTLA-4 therapy. Clinical specimen validation showed an obvious difference in the expression of seven glycosyltransferase genes between the low- and high-risk groups. Significant reduction in POFUT2 expression in high-risk groups was associated with reduced N-glycans production.

CONCLUSION

Our study constructed a robust glyco-risk prediction model that could provide direction for immunotherapy and chemotherapy in CRC patients, which could help clinicians make personalized treatment decisions.

GPI-anchored glutathione S-transferase as marker allows affinity sorting of transfection-positive cells

Cell transfection efficiency is still a limiting factor in gene function research. A method that allows isolation and enrichment of the transfection-positive cells is an effective solution. Here, we report a transfection-positive cell sorting system that utilizes GPI-anchored GST (Glutathione S-transferase) as a plasmid marker. The Glutathione S-transferase fusion protein will be expressed and displayed on the cell surface through GPI anchor, and hence permits the positive cells to be isolated using Glutathione (GSH) Magnetic Beads. We prove that the system works efficiently in both the adherent Lenti-X 293T cells and the suspension K-562 cells. The affinity cell sorting procedure efficiently enriched positive cells from 20% to 98% in K-562 cells. The applications in gene knockdown and overexpression experiments in K-562 cells dramatically enhanced the extent of gene alteration, with the gene knockdown efficiency increasing from 7% to 60% and the gene overexpression level rising from 47 to 253 times. This Glutathione S-transferase affinity transfection-positive cell sorting method is simple and fast to operate, large-instrument free, low cost, and hence possesses great potential in gene function study in vitro.

rs10514231 Leads to Breast Cancer Predisposition by Altering ATP6AP1L Gene Expression

Numerous genetic variants located in autophagy-related genes have been identified for association with various cancer risks, but the biological mechanisms underlying these associations remain largely unknown. Here we investigated their regulatory activity with a parallel reporter gene assay system in breast cancer cells and identified multiple regulatory SNP sites, including rs10514231. It was located in the second intron of ATG10 and showed gene regulatory activity in most breast cancer cells we used. Mechanistically, the T allele of rs10514231 led to ATP6AP1L downregulation by decreasing the binding affinity of TCF7L2. Overexpression of the ATP6AP1L gene in cancer cells diminished cell proliferation, migration, and invasion. Notably, ATP6AP1L downregulation correlated with breast cancer risk and with poor prognosis in patients. These results provide a plausible mechanism behind the association of rs10514231 with breast cancer risk and will be important for more effective therapeutic target identification for precision medicine.

A Ten-year-long Update on Radiation Proctitis Among Prostate Cancer Patients Treated With Curative External Beam Radiotherapy

This comprehensive synopsis summarizes the most relevant information obtained from a systematic analysis of studies of the last decade on radiation proctitis, one of the most feared radioinduced side effects among prostate cancer patients treated with curative external beam radiotherapy. The present review provides a useful support to radiation oncologists for limiting the onset or improving the treatment of radiation proctitis. This work shows that the past decade was a harbinger of significant new evidence in technological advances and technical tricks to avoid radiation proctitis, in addition to dosimetric perspectives and goals, understanding of pathogenesis, diagnostic work-up and treatment. We believe that a well-rounded knowledge of such an issue is fundamental for its appropriate management.