PCSK1 Overexpression in Rectal Cancer Correlates with Poor Response to Preoperative Chemoradiotherapy and Prognosis

Establishment of a prognostic model for melanoma based on necroptosis-related genes

In this study, the clinical implications and potential functions of necroptosis-related genes (NRGs) in melanoma were systematically characterized. A novel NRG signature was then constructed to analyze the immune status and prognosis of patients with melanoma. The NRG signatures for melanoma prognosis were searched using the Cancer Genome Atlas (TCGA) dataset and followed by stepwise Cox regression analysis. Patients with melanoma were divided into two groups, and survival analysis, receiver operating characteristic (ROC), and univariate and multivariate analyses were subsequently performed. The correlation of risk score (RS) with tumor immunity and RT-polymerase chain reaction (PCR) was analyzed to further verify the gene signatures. Data on tumor mutational burden (TMB) and chromosomal copy number variation (CNV) were analyzed. Three NRGs were identified as prognostic risk signatures and were significantly related to overall survival (OS) in melanoma. The signatures had better diagnostic accuracy. Furthermore, analysis of mutations in the NRGs and the incidence of chromosomal CNV helped to reveal the relationship between mutations and melanoma occurrence. A nomogram was established based on RSs. The risk characteristics were significantly associated with immunity and high risk is closely correlated with melanoma development. In vitro experiments revealed that necrostatin-1 (Nec-1) promoted cell viability and repressed the expression levels of interleukin (IL)12A and proprotein convertase subtilisin/kexin type (PCSK)1. Additionally, the expression levels of IL12A, CXCL10, and PCSK1 decreased in tumor tissues of melanoma patients. NRGs exert vital roles in immunity and might be applied as a prognostic factor of melanoma.

Peripubertal Nutritional Prevention of Cancer-Associated Gene Expression and Phenotypes

Breast cancer (BC) is a nearly ubiquitous malignancy that effects the lives of millions worldwide. Recently, nutritional prevention of BC has received increased attention due to its efficacy and ease of application. Chief among chemopreventive compounds are plant-based substances known as dietary phytochemicals. Sulforaphane (SFN), an epigenetically active phytochemical found in cruciferous vegetables, has shown promise in BC prevention. In addition, observational studies suggest that the life stage of phytochemical consumption may influence its anticancer properties. These life stages, called critical periods (CPs), are associated with rapid development and increased susceptibility to cellular damage. Puberty, a CP in which female breast tissue undergoes proliferation and differentiation, is of particular interest for later-life BC development. However, little is known about the importance of nutritional chemoprevention to CPs. We sought to address this by utilizing two estrogen receptor-negative [ER(-)] transgenic mouse models fed SFN-containing broccoli sprout extract during the critical period of puberty. We found that this treatment resulted in a significant decrease in tumor incidence and weight, as well as an increase in tumor latency. Further, we found significant alterations in the long-term expression of cancer-associated genes, including p21, p53, and BRCA2. Additionally, our transcriptomic analyses identified expressional changes in many cancer-associated genes, and bisulfite sequencing revealed that the antiproliferation-associated gene Erich4 was both hypomethylated and overexpressed in our experimental group. Our study indicates that dietary interventions during the CP of puberty may be important for later-life ER(-) BC prevention and highlights potential important genetic and epigenetic targets for treatment and study of the more deadly variants of BC.

A Risk Score Signature Consisting of Six Immune Genes Predicts Overall Survival in Patients with Lower-Grade Gliomas

Background. Lower-grade gliomas (LGGs) are less aggressive with a long overall survival (OS) time span. Because of individualized genomic features, a prognostic system incorporating molecular signatures can more accurately predict OS. Methods. Differential expression analysis between LGGs and normal tissues was performed using the Gene Expression Omnibus (GEO) datasets (GSE4290 and GSE12657). Immune-related differentially expressed genes (ImmPort-DEGs) were analyzed for functional enrichment. The least absolute shrinkage and selection operator (LASSO) analysis was performed to develop an immune risk score signature (IRSS). We extracted information from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) to establish and validate the model. The relationship of model gene sets with immune infiltration was analyzed based on gene set variation analysis (GSVA) scores. Patients were divided into low- and high-risk groups based on the median score. The time-dependent receiver-operating characteristic (ROC) curve and the Kaplan-Meier curve were used to evaluate the model. Then, a precise prognostic nomogram was established, and its efficacy was verified. Results. A total of 18 related immune genes were identified, building a 6-gene IRSS (BMP2, F2R, FGF13, PCSK1, PRKCB, and PTGER3). DEGs were enriched in T cell and NK cell regulatory pathways. Immune infiltration analysis confirmed that the gene signature correlated with a decrease in innate immune cells. In terms of model evaluation, ROC curves at 1, 3, and 5 years showed moderate predictive ability of IRSS ( $\text{AUC}=0.930$ , 0.797, and 0.728). The Cox regression analysis revealed that IRSS was an independent prognostic factor, and the nomogram model had good predictive ability ( $\text{C}-\text{index}=0.828$ ). Meanwhile, the predictive power of IRSS was also confirmed in the training cohort. The Kaplan-Meier results showed that the prognosis of the high-risk group was significantly worse in all cohorts. Conclusion. IRSS may serve as a novel survival prediction tool in the classification of LGG patients.

High Expression of Folate Receptor Alpha (FOLR1) is Associated With Aggressive Tumor Behavior, Poor Response to Chemoradiotherapy, and Worse Survival in Rectal Cancer

Objectives: Recently, molecular medicine targeting Folate Receptor Alpha (FOLR1), which mediates intracellular folate uptake and tumor cell proliferation, has been identified in several malignancies. However, the association between FOLR1 expression and rectal cancer remains unclear. Methods: Immunostaining of FOLR1 was performed on biopsy specimens from 172 rectal cancer patients undergoing preoperative chemoradiotherapy (CRT). FOLR1 expression was measured and divided into low (0+-2+) or high (3+-4+) level. Correlations between FOLR1 status and clinicopathologic features, tumor regression grade, disease-specific survival (DSS), local recurrence-free survival, and metastasis-free survival (MeFS) were analyzed, retrospectively. Results: High FOLR1 expression was significantly associated with advanced post-treatment tumor and nodal status (T3-4; N1-2, P = .001), vascular invasion (P = .042), perineural invasion (P = .012), and poor regression change after CRT (P = .001). In uni- and multi-variable survival analysis, FOLR1 overexpression remained a significant predictor of lower DSS (hazard ratio [HR], 2.328; 95% confidence interval [CI], 1.014-5.344; P = .046) and MeFS (HR, 2.177; 95% CI, 1.000-1.1286; P = .050). Conclusion: These results indicate that high FOLR1 status is associated with aggressive tumor behavior, poor response to CRT, and worse survival. Therefore, FOLR1 expression at initial biopsy may be useful in predicting outcomes and also be a target for the exploration of FOLR1-based therapeutic agents.

High Expression of VSTM2L Induced Resistance to Chemoradiotherapy in Rectal Cancer through Downstream IL-4 Signaling

Background

Preoperative chemoradiotherapy (pCRT) is a common and essential therapeutic strategy for patients with locally advanced rectal cancer (LARC), but poor tumor response and therapeutic resistance to chemoradiotherapy have appeared usually among persons and affected those patients' survival prognosis. The resistance to chemoradiotherapy in rectal cancer is difficult to predict. This study was aimed at evaluating the role of V-set and transmembrane domain containing 2 like protein (VSTM2L) in resistance to chemoradiotherapy in rectal cancer.

Methods

Analysis of the GEO profiling datasets of rectal cancer patients receiving pCRT disclosed that VSTM2L as a candidate gene was significantly upregulated in nonresponders of rectal cancer with pCRT. The mRNA and protein expression of VSTM2L was detected by quantitate real-time PCR, western blotting, and immunohistochemistry in six rectal cancer biopsy tissues before pCRT. Furthermore, the rectal cancer patient-derived organoids were cultured to evaluate the association of VSTM2L expression and tumor response to CRT. Overexpression of VSTM2L in cancer cells treated with CRT was analyzed for the function of cell proliferation and viability, clone formation, DNA damage repair, and apoptosis ability. The GSEA and RNA-sequence analysis were used to find the downstream mechanism of VSTM2L overexpression in cells treated with CRT.

Results

The mRNA levels of VSTM2L were significantly downregulated in normal rectal tissues compared to tumor tissues and were upregulated in nonresponders of rectal cancer patients receiving pCRT and positively correlated with poor survival prognosis from GEO datasets. High expression of VSTM2L was significantly associated with tumor regression after pCRT (P = 0.030). Moreover, high expression of VSTM2L reduced γ-H2AX expression in rectal cancer patient-derived organoids treated with CRT. The overexpression of VSTM2L in colorectal cancer cells induced resistance to CRT via promoting cell proliferation and inhibiting apoptosis. The molecular mechanism revealed that the overexpression of VSTM2L induced resistance to CRT through downstream IL-4 signaling affecting the progress of cell proliferation and apoptosis.

Conclusion

The high expression of VSTM2L induced resistance to CRT, and adverse survival outcomes served as a prognostic factor in patients with rectal cancer receiving pCRT, suggesting that VSTM2L high expression may be a potential resistant predictable biomarker for LARC patients receiving pCRT.

Identification of a Metabolism-Related Risk Signature Associated With Clinical Prognosis in Glioblastoma Using Integrated Bioinformatic Analysis

Altered metabolism of glucose, lipid and glutamine is a prominent hallmark of cancer cells. Currently, cell heterogeneity is believed to be the main cause of poor prognosis of glioblastoma (GBM) and is closely related to relapse caused by therapy resistance. However, the comprehensive model of genes related to glucose-, lipid- and glutamine-metabolism associated with the prognosis of GBM remains unclear, and the metabolic heterogeneity of GBM still needs to be further explored. Based on the expression profiles of 1,395 metabolism-related genes in three datasets of TCGA/CGGA/GSE, consistent cluster analysis revealed that GBM had three different metabolic status and prognostic clusters. Combining univariate Cox regression analysis and LASSO-penalized Cox regression machine learning methods, we identified a 17-metabolism-related genes risk signature associated with GBM prognosis. Kaplan-Meier analysis found that obtained signature could differentiate the prognosis of high- and low-risk patients in three datasets. Moreover, the multivariate Cox regression analysis and receiver operating characteristic curves indicated that the signature was an independent prognostic factor for GBM and had a strong predictive power. The above results were further validated in the CGGA and GSE13041 datasets, and consistent results were obtained. Gene set enrichment analysis (GSEA) suggested glycolysis gluconeogenesis and oxidative phosphorylation were significantly enriched in high- and low-risk GBM. Lastly Connectivity Map screened 54 potential compounds specific to different subgroups of GBM patients. Our study identified a novel metabolism-related gene signature, in addition the existence of three different metabolic status and two opposite biological processes in GBM were recognized, which revealed the metabolic heterogeneity of GBM. Robust metabolic subtypes and powerful risk prognostic models contributed a new perspective to the metabolic exploration of GBM.