Identification and Validation in a Novel Quantification System of Ferroptosis Patterns for the Prediction of Prognosis and Immunotherapy Response in Left- and Right-Sided Colon Cancer.

Background: This study aimed to establish a novel quantification system of ferroptosis patterns and comprehensively analyze the relationship between ferroptosis score (FS) and the immune cell infiltration (ICI) characterization, tumor mutation burden (TMB), prognosis, and therapeutic sensitivity in left-sided and right-sided colon cancers (LCCs and RCCs, respectively). Methods: We comprehensively evaluated the ferroptosis patterns in 444 LCCs and RCCs based on 59 ferroptosis-related genes (FRGs). The FS was constructed to quantify ferroptosis patterns by using principal component analysis algorithms. Next, the prognostic value and therapeutic sensitivities were evaluated using multiple methods. Finally, we performed weighted gene co-expression network analysis (WGCNA) to identify the key FRGs. The IMvigor210 cohort, TCGA-COAD proteomics cohort, and Immunophenoscores were used to verify the predictive abilities of FS and the key FRGs. Results: Two ferroptosis clusters were determined. Ferroptosis cluster B demonstrated a high degree of congenital ICI and stromal-related signal enrichment with a poor prognosis. The prognosis, response of targeted inhibitors, and immunotherapy were significantly different between high and low FS groups (HSG and LSG, respectively). HSG was characterized by high TMB and microsatellite instability-high subtype with poor prognosis. Meanwhile, LSG was more likely to benefit from immunotherapy. ALOX5 was identified as a key FRG based on FS. Patients with high protein levels of ALOX5 had poorer prognoses. Conclusion: This work revealed that the evaluation of ferroptosis subtypes will contribute to gaining insight into the heterogeneity in LCCs and RCCs. The quantification for ferroptosis patterns played a non-negligible role in predicting ICI characterization, prognosis, and individualized immunotherapy strategies.

A Novel Quantification System Combining iTRAQ Technology and Multi-Omics Assessment to Predict Prognosis and Immunotherapy Efficacy in Colon Cancer.

Background: Colon cancer is one of the most common cancer types, although it has certain unique genetic features. This study aimed to develop a unique score for assessing prognosis and immunotherapy efficacy using integrated multi-omics analysis. Methods: Isobaric tagging for relative and absolute quantification (iTRAQ) based proteomic analysis was used to screen differentially expressed proteins (DEP) between tumor and normal samples. DEP mRNA obtained from TCGA were clustered into different categories to show landscape-related prognosis and function. Following that, DEG was extracted from DEP mRNA, and the DEP-related score (DEPRS) was constructed to investigate the difference in immunotherapy prognosis and sensitivity. Finally, WCGNA, random forest, and artificial neural networks were used to screen for key genes. The prognostic value and protein level of these genes were validated. Results: A total of 243 DEPs were identified through iTRAQ analysis, and the corresponding DEP mRNA was clustered into three. Following a series of tests, 1,577 DEGs were identified from overlapped DEP mRNA clusters and were classified into three gene clusters. The two types of clusters described above shared comparable characteristics in terms of prognosis and function. Then, it was established that a high DEPRS indicated a poor prognosis and DEPRS had significant associations with TMB, MSI status, and immunotherapeutic response. Finally, the key genes HART3 and FBLN2 were identified and were found to be implicated in immunotherapy and prognosis. Conclusion: The development of a DEPRS based on multi-omics analysis will aid in improving our understanding of colon cancer and guiding a more effective immunotherapy strategy. DEPRS and key genes are used as biomarkers in the clinical evaluation of patients.

Prognostic and therapeutic significance of a novel ferroptosis related signature in colorectal cancer patients.

Increasing studies have highlighted the importance of ferroptosis in colorectal cancer (CRC). However, how to use ferroptosis-related genes (FRGs) to predict the prognosis and guide the treatment of CRC remains unknown. To build a prognostic prediction model using the GEO and TCGA databases and explored a therapeutic strategy for CRC patients based on FRGs. A total of 60 FRGs were identified and three of them including ACACA, GSS, and NFS1 were associated with the prognosis of CRC. Using Lasso regression analysis, an FRGs signature was constructed and validated as an independent prognostic predictor. Then we developed a nomogram based on the FRGs signature and clinical prognostic factors to predict the prognosis of CRC patients, which was better than the traditional TNM staging system. Single-sample gene set enrichment analysis (ssGSEA) was further performed for the functional analysis and suggested that JAK-STAT signaling, Ras signaling pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway were significantly enriched in CRC patients with higher FRGs risk score. Interestingly, CRC cells with higher FRGs risk score were more sensitive to RSL3. Knocking down GSS and NFS1 increased the FRGs risk score and the sensitivity of CRC cells to RSL3. For the clinic use, we screened 75 FDA-approved cancer drugs and found that Fludarabine phosphate could decrease the expression of GSS and NFS1 most. Fludarabine phosphate, in combination with RSL3, showed a strong synergistic effect on CRC cells. Together, this study identified a potent prognostic model and provided an alternative individualized treatment for CRC patients.

Prognostic Immunity and Therapeutic Sensitivity Analyses Based on Differential Genomic Instability-Associated LncRNAs in Left- and Right-Sided Colon Adenocarcinoma.

Background: The purpose of our study was to develop a prognostic risk model based on differential genomic instability-associated (DGIA) long non-coding RNAs (lncRNAs) of left-sided and right-sided colon cancers (LCCs and RCCs); therefore, the prognostic key lncRNAs could be identified. Methods: We adopted two independent gene datasets, corresponding somatic mutation and clinical information from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Identification of differential DGIA lncRNAs from LCCs and RCCs was conducted with the appliance of "Limma" analysis. Then, we screened out key lncRNAs based on univariate and multivariate Cox proportional hazard regression analysis. Meanwhile, DGIA lncRNAs related prognostic model (DRPM) was established. We employed the DRPM in the model group and internal verification group from TCGA for the purpose of risk grouping and accuracy verification of DRPM. We also verified the accuracy of key lncRNAs with GEO data. Finally, the differences of immune infiltration, functional pathways, and therapeutic sensitivities were analyzed within different risk groups. Results: A total of 123 DGIA lncRNAs were screened out by differential expression analysis. We obtained six DGIA lncRNAs by the construction of DRPM, including AC004009.1, AP003555.2, BOLA3-AS1, NKILA, LINC00543, and UCA1. After the risk grouping by these DGIA lncRNAs, we found the prognosis of the high-risk group (HRG) was significantly worse than that in the low-risk group (LRG) (all p < 0.05). In all TCGA samples and model group, the expression of CD8+ T cells in HRG was lower than that in LRG (all p < 0.05). The functional analysis indicated that there was significant upregulation with regard to pathways related to both genetic instability and immunity in LRG, including cytosolic DNA sensing pathway, response to double-strand RNA, RIG-Ⅰ like receptor signaling pathway, and Toll-like receptor signaling pathway. Finally, we analyzed the difference and significance of key DGIA lncRNAs and risk groups in multiple therapeutic sensitivities. Conclusion: Through the analysis of the DGIA lncRNAs between LCCs and RCCs, we identified six key DGIA lncRNAs. They can not only predict the prognostic risk of patients but also serve as biomarkers for evaluating the differences of genetic instability, immune infiltration, and therapeutic sensitivity.

The oncogenic role of LncRNA FAM83C-AS1 in colorectal cancer development by epigenetically inhibits SEMA3F via stabilizing EZH2.

Inactivation of Semaphorin 3F (SEMA3F) is involved in colorectal cancer development. However, the mechanism by which SEMA3F is regulated remains elusive. Deregulation of lncRNAs have been implicated in multiple human malignancies, including colorectal cancer (CRC). To date, it is still unclear whether and how lncRNA regulates SEMA3F expression and mediates CRC progression. Here we identify the oncogenic role of lncRNA FAM83C antisense RNA 1 (FAM83C-AS1) in CRC. FAM83C-AS1 is upregulated in tumor tissues and cells of CRC, which is negatively correlated with SEMA3F expression. Reciprocally, knockdown of FAM83C-AS1 exhibits inhibitory effects on the malignant transformation of CRC. Moreover, our data uncover that FAM83C-AS1 enhances methylation of SEMA3F promoter H3K27me3 via upregulating methyltransferase enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2). Specifically, FAM83C-AS1 stabilizes EZH2 protein through recruiting the zinc finger RANBP2-type containing 1 (ZRANB1). Both in vitro and in vivo rescue assays exhibit that SEMA3F is dispensable for the tumor-promoting effects of FAM83C-AS1 on CRC progression. Our data thus demonstrate that the epigenetic role of FAM83C-AS1 in suppression of SEMA3F expression through stabilization of EZH2 to drive CRC progression, which may be conducive to discovering novel therapeutic targets for the treatment of CRC.

Differential Metabolic Alterations and Biomarkers Between Gastric Cancer and Colorectal Cancer: A Systematic Review and Meta-Analysis.

PURPOSE: Numerous metabolomics studies have been conducted to detect the metabolic mechanisms and biomarkers related to gastric cancer and colorectal cancer. Because of the common metabolic features between gastric cancer and colorectal cancer, a differential diagnosis is difficult. Here, we performed a systematic review and meta-analysis to identify differential metabolic biomarkers between these two types of cancers. MATERIALS AND METHODS: PubMed, Embase, and ScienceDirect were searched to identify all metabolomics studies of gastric cancer and colorectal cancer published up to September 2018. Differential metabolites or altered pathways were extracted. The intersections and differences for these metabolites and pathways between gastric cancer and colorectal cancer were compared. Candidate biomarker sets for diagnosis were proposed from biofluid or feces by comparing them with tumor tissues. RESULTS: Totally, 24 and 65 studies were included in gastric cancer and colorectal cancer, and 223 and 472 differential metabolites were extracted, respectively. Eight pathways were reproducibly enriched in blood, tissue and urine in gastric cancer, while, 11 pathways were reproducibly enriched in blood, urine, feces and tissue in colorectal cancer. Candidate metabolic biomarker sets in blood, urine, or feces for these two cancers were proposed. We found 27 pathways (categorized into eight classifications) common to both cancers, five pathways involving 35 metabolites enriched only in gastric cancer, and eight pathways involving 54 metabolites enriched only in colorectal cancer. CONCLUSION: The altered metabolic pathways showed signatures of abnormal metabolism in gastric cancer and colorectal cancer; the potential metabolic biomarkers proposed in this study have important implications for the prospective validation of gastric cancer and colorectal cancer.

SPNS2 promotes the malignancy of colorectal cancer cells via regulating Akt and ERK pathway.

Colorectal cancer (CRC) is a prevalent malignant tumour that causes considerable cancer-related deaths globally. The sphingolipid transporter 2 (SPNS2), a sphingosine-1-phosphate (S1P) transporter, modulates multiple biological events including malignancy of cancer cells. In this study, the effects of SPNS2 on CRC progression were studied. We found that SPNS2 expression was significantly upregulated in CRC tissues compared to that in adjacent non-tumour tissues. To assess the role of SPNS2 in CRC cells, we performed loss- and gain-of-function experiments in SW480 and HCT116 cells, respectively. The results demonstrated that SPNS2 promoted proliferation, migration and invasion, and inhibited apoptosis in CRC cells. Additionally, SPNS2 enhanced the release of intracellular S1P, and increased S1P receptor 1 (S1PR1) and S1PR3 expression. Moreover, SPNS2 activated the Akt and ERK pathways, and the biological behaviours of SPNS2 were attenuated by Akt or ERK inhibitor in HCT116 cells. In conclusion, our results demonstrated that SPNS2 promoted proliferation, migration and invasion, and inhibited apoptosis by regulating S1P/S1PR1/3 axis and activating Akt and ERK pathway in CRC cells.

Facile Secondary Deposition for Improving Quantum Dot Loading in Fabricating Quantum Dot Solar Cells.

Sufficient loading of presynthesized quantum dots (QDs) on mesoporous TiO2 electrodes is the prerequisite for the fabrication of high-performance QD-sensitized solar cells (QDSCs). Here, we provide a general approach for increasing QD loading on mesoporous TiO2 films by surface engineering. It was found that the zeta potential of presensitized TiO2 can be effectively adjusted by surfactant treatment, on the basis of which additional QDs are successfully introduced onto photoanodes during secondary deposition. The strategy developed, that is, the secondary deposition incorporating surfactant treatment, makes it possible to load various QDs onto photoanodes regardless of the nature of QDs. In standard AM 1.5G sunlight, a certified efficiency of 10.26% for the QDSC with Cu2S/brass counter electrodes was achieved by the secondary deposition of Zn-Cu-In-Se QDs.

Genome-wide methylation analysis identifies novel prognostic methylation markers in colon adenocarcinoma.

Previous studies have indicated that abnormal methylation is a critical and early event in the pathogenesis of most types of human cancer, which contributes to tumorigenesis. However, there has been little focus on the potential of DNA methylation patterns as predictive markers for the prognosis of colon adenocarcinoma (COAD). In the present study, a genome-wide comparative analysis of DNA methylation profiles was performed between 315 COAD samples and 38 matched tumor-adjacent normal tissue samples. A total of 675 differentially methylated regions (DMRs) associated with 630 genes were identified, including 654 hypermethylated regions (UMRs) and 21 hypomethylated regions, which were capable of distinguishing COAD samples from non-malignant tissue samples. Although most of the DMRs appeared to be located within the gene body or promoter regions, UMRs were mostly located within CpG islands. Functional analysis suggested that genes associated with DMRs were enriched in many of the core cancer-signaling pathways known to be important in COAD biology. A survival analysis was also performed, which identified 7 DMRs as potential candidate markers with the ability to classify patients into high and low-risk groups with significantly different overall survival. The present study provides a better understanding of the molecular mechanisms underlying COAD, and demonstrates the utility of aberrant DNA methylation in the prognosis of COAD.

Cosensitized Quantum Dot Solar Cells with Conversion Efficiency over 12.

The improvement of sunlight utilization is a fundamental approach for the construction of high-efficiency quantum-dot-based solar cells (QDSCs). To boost light harvesting, cosensitized photoanodes are fabricated in this work by a sequential deposition of presynthesized Zn-Cu-In-Se (ZCISe) and CdSe quantum dots (QDs) on mesoporous TiO2 films via the control of the interactions between QDs and TiO2 films using 3-mercaptopropionic acid bifunctional linkers. By the synergistic effect of ZCISe-alloyed QDs with a wide light absorption range and CdSe QDs with a high extinction coefficient, the incident photon-to-electron conversion efficiency is significantly improved over single QD-based QDSCs. It is found that the performance of cosensitized photoanodes can be optimized by adjusting the size of CdSe QDs introduced. In combination with titanium mesh supported mesoporous carbon as a counterelectrode and a modified polysulfide solution as an electrolyte, a champion power conversion efficiency up to 12.75% (Voc = 0.752 V, Jsc = 27.39 mA cm-2 , FF = 0.619) is achieved, which is, as far as it is known, the highest efficiency for liquid-junction QD-based solar cells reported.

A long non-coding RNA expression signature to predict survival of patients with colon adenocarcinoma.

Colon cancer is the most common type of gastrointestinal cancer and is still the leading cause of cancer-related mortality worldwide. Long non-coding RNAs (lncRNAs) have been proved to be superior biomarkers in cancer diagnosis and prognosis than miRNAs and protein-coding genes. In the current study, our objective was to detect novel lncRNA biomarkers by analyzing lncRNA expression profiles and clinical data in a large cohort of patients with colon patients from The Cancer Genome Atlas (TCGA). By using Cox regression analysis, we identified two lncRNAs (SNHG6 and CTD-2354A18.1) which could be independent prognostic factors for predicting clinical outcome in colon adenocarcinoma. Then a linear combination of these two lncRNA biomarkers (SNHG6 and CTD-2354A18.1), termed two-lncRNA signature, was developed in the training set as a predictor for OS in patients with colon adenocarcinoma, and validated in the testing set and the entire patient set. This two-lncRNA signature demonstrated significant prognostic performance in both the testing set and the entire patient set which classified the patients into two groups with significantly different OS. The multivariate and stratified analysis suggested that the prognostic value of the two-lncRNA signature was independent of other traditional clinical variables. Functional analysis suggested that these two lncRNA biomarkers might be mainly involved in transcription/translation-related or DNA repair-related biological processes. In summary, our results warrant further studies on these lncRNAs that will improve our understanding of the mechanisms associated with pathogenesis and progression of colon adenocarcinoma.

Identification of potential long non-coding RNA biomarkers associated with the progression of colon cancer.

Increasing evidence has suggested that dysregulated lncRNA expression played important roles in the development and progression of human cancers. Although prognostic roles of lncRNAs have been recognized for colon cancer (CC) patients, the search for novel lncRNA biomarkers potentially involved in CC progression is an urgent and still largely unmet medical need. In this study, we evaluated the lncRNA expression changes during the progression of CC by analyzing two cohorts of previously published expression profiles of CC patients and identified hundreds of differentially expressed lncRNAs. Then we identified eight lncRNAs that closely associated with the progression of CC patients from a large number of significantly altered lncRNAs using random forest supervised classification algorithm. Finally, an SVM-based lncRNA risk classifier was developed to discriminate high-risk CC patients from persons with early-stage and validated in both the training dataset and testing dataset by survival analysis and five-fold cross-validation strategy. Our pathway enrichment analysis based on protein-coding genes that are co-expressed with lncRNAs, suggested that variation in expression of eight lncRNAs biomarkers might affect critical pathways involved in CC progression. With further validation, these eight lncRNAs might have significant implications for the clinical management of CC patients with early stage and improve our understanding of cancer progression.

The influence of genetic polymorphisms in MDR1 gene on breast cancer risk factors in Chinese.

Breast cancer (BC) is the most common cancer among women in the world. The human multidrug resistance 1 gene (MDR1) is potentially an important gene influencing the susceptibility to breast cancer. This study aimed to assess the association of MDR1 genetic polymorphisms with the susceptibility to BC. Overall, 353 BC patients and 360 cancer-free controls were enrolled. The clinical characteristics were summarized by questionnaires. The c.1564A > T genetic polymorphism was genotyped using created restriction site-polymerase chain reaction method. We found that no significant differences in the genotypic and allelic frequencies between BC patients and cancer-free controls. Furthermore, the distribution of BC patients' risk factors was not significantly different among AA, AT, and TT genotypes. Our findings indicate that the c.1564A > T genetic polymorphism is not significantly associated with the susceptibility to BC in Chinese Han populations.

Methylation profiles of the BRCA1 promoter in hereditary and sporadic breast cancer among Han Chinese.

The development of breast cancer is a multistep process associated with complex changes in host gene expression patterns including inactivation of tumor suppressor genes and activation of oncogenes. Critically, hereditary predisposition plays a significant role in cancer susceptibility. However, mutation of the BRCA1 gene is found only in the minority of hereditary breast cancer, which indicates that there might be alternative, novel mechanisms contributing to inactivation of the BRCA1 gene. Studies have shown that aberrant methylation of genomic DNA plays an important role in carcinogenesis. The aim of this study was to investigate whether DNA methylation may be an alternative mechanism for the inactivation of BRCA1 as an epigenetic modification of the genome and whether hereditary breast cancer has a different BRCA1 methylation phenotype pattern than sporadic breast cancer. The pattern of CpG island methylation within the promoter region of BRCA1 was assessed by bisulfite sequencing DNA from peripheral blood cells of 72 patients with hereditary predisposition but without BRCA1 mutations and 30 sporadic breast cancer controls. The overall methylation level in patients with hereditary predisposition was significantly lower than that in the sporadic control group. However, patients with hereditary predisposition showed a significantly higher methylation susceptibility for the sites -518 when compared to controls. These results suggest that there might be different BRCA1 promoter methylation levels and patterns in sporadic and hereditary breast cancer in peripheral blood DNA. These findings may facilitate the early diagnosis of hereditary breast cancer.

Clinicopathologic characteristics and prognosis of young patients with breast cancer.

BACKGROUND: The aim was to describe the clinicopathological features and prognosis of young patients with breast cancer. PATIENTS AND METHODS: We reviewed the records of 1478 consecutive patients aged ≤50 years with first diagnosis of invasive breast cancer referred to surgery from January 1999 to March 2005. A total of 174 patients were aged <35 years (group I) and 1304 were aged 35-50 years (group II). RESULTS: Compared with patients of group II, patients of group I had a higher percentage of tumors classified as estrogen receptors (ER) negative, progesterone receptors (PR) negative, with a Ki-67 labeling index ≥20% of the cells. The 5-year survival of group I was 78.3% as compared with 84.2% for group II (P = 0.006). CONCLUSION: Compared with patients aged between 35 and 50 years, patients aged <35 years have a greater chance of having an endocrine-unresponsive tumor and a significantly poor prognosis.