Integrated transcriptomic analysis of distance-related field cancerization in rectal cancer patients

Apparent diffusion coefficient and its standard deviation from diffusion-weighted imaging in preoperative predicting liver invasion by T3-staged resectable gallbladder carcinoma

AIM

To evaluate apparent diffusion coefficient (ADC) and its standard deviation (SDADC) in preoperative predicting liver invasion by T3-staged gallbladder carcinoma (GBC).

MATERIALS AND METHODS

Forty-one consecutive patients with T3-staged resectable GBC were included and divided into two sets with (n=27) and without (n=14) liver invasion. All patients underwent DWI at b-values of 0, 20, 50, 80, 100, 200, 400, 600, 800, and 1,000 s/mm2 with a 3 T magnetic resonance imaging scanner before surgery. ADC and SDADC of tumour-adjacent and tumour-distant liver tissues were measured on DWI, and were compared by Mann-Whitney U-tests. If there was a significant difference in any derived parameter, the area under the receiver operating characteristic curve (AUC) was used to assess performance of this parameter to predict liver invasion.

RESULTS

DWI could differentiate between patients with and without liver invasion when b = 0, 1,000 s/mm2 (AUCs of ADC and SDADC were 0.697 and 0.714, respectively). In patients with liver invasion, mean ADC and SDADC of tumour-adjacent liver tissue were lower than of tumour-distant liver tissue when b = 0, 800 s/mm2, and = 0, 1,000 s/mm2 (all p-values <0.05). To differentiate tumour-adjacent from tumour-distant liver tissues in patients with liver invasion, AUCs of ADC were 0.687 (b = 0, 800 s/mm2) and 0.680 (b = 0, 1,000 s/mm2), and AUCs of SDADC were 0.673 (b = 0, 800 s/mm2) and 0.731 (b = 0, 1,000 s/mm2).

CONCLUSIONS

DWI could have potential value in preoperative predicting liver invasion by T3-staged GBC.

AEG-1 as a Novel Therapeutic Target in Colon Cancer: A Study from Silencing AEG-1 in BALB/c Mice to Large Data Analysis

BACKGROUND

Astrocyte elevated gene-1 (AEG-1) is overexpressed in various malignancies. Exostosin-1 (EXT-1), a tumor suppressor, is an intermediate for malignant tumors. Understanding the mechanism behind the interaction between AEG-1 and EXT-1 may provide insights into colon cancer metastasis.

METHODS

AOM/DSS was used to induce tumor in BALB/c mice. Using an in vivo-jetPEI transfection reagent, transient transfection of AEG-1 and EXT-1 siRNAs were achieved. Histological scoring, immunohistochemical staining, and gene expression studies were performed from excised tissues. Data from the Cancer Genomic Atlas and GEO databases were obtained to identify the expression status of AEG-1 and itsassociation with the survival.

RESULTS

In BALB/c mice, the AOM+DSS treated mice developed necrotic, inflammatory and dysplastic changes in the colon with definite clinical symptoms such as loss of goblet cells, colon shortening, and collagen deposition. Administration of AEG-1 siRNA resulted in a substantial decrease in the disease activity index. Mice treated with EXT-1 siRNA showed diffusely reduced goblet cells. In vivo investigations revealed that PTCH-1 activity was influenced by upstream gene AEG-1, which in turn may affect EXT-1 activity. Data from The Cancer Genomic Atlas and GEO databases confirmed the upregulation of AEG-1 and downregulation of EXT-1 in cancer patients.

CONCLUSIONS

This study revealed that AEG-1 silencing might alter EXT-1 expression indirectly through PTCH-1, influencing cell-ECM interactions, and decreasing dysplastic changes, proliferation and invasion.

Epigenome-wide methylation analysis of colorectal carcinoma, adenoma and normal tissue reveals novel biomarkers addressing unmet clinical needs

BACKGROUND

Biomarker discovery in colorectal cancer has mostly focused on methylation patterns in normal and colorectal tumor tissue, but adenomas remain understudied. Therefore, we performed the first epigenome-wide study to profile methylation of all three tissue types combined and to identify discriminatory biomarkers.

RESULTS

Public methylation array data (Illumina EPIC and 450K) were collected from a total of 1 892 colorectal samples. Pairwise differential methylation analyses between tissue types were performed for both array types to "double evidence" differentially methylated probes (DE DMPs). Subsequently, the identified DMPs were filtered on methylation level and used to build a binary logistic regression prediction model. Focusing on the clinically most interesting group (adenoma vs carcinoma), we identified 13 DE DMPs that could effectively discriminate between them (AUC = 0.996). We validated this model in an in-house experimental methylation dataset of 13 adenomas and 9 carcinomas. It reached a sensitivity and specificity of 96% and 95%, respectively, with an overall accuracy of 96%. Our findings raise the possibility that the 13 DE DMPs identified in this study can be used as molecular biomarkers in the clinic.

CONCLUSIONS

Our analyses show that methylation biomarkers have the potential to discriminate between normal, precursor and carcinoma tissues of the colorectum. More importantly, we highlight the power of the methylome as a source of markers for discriminating between colorectal adenomas and carcinomas, which currently remains an unmet clinical need.

Exploring the pathogenesis of colorectal carcinoma complicated with hepatocellular carcinoma via microarray data analysis

Background: Despite the increasing number of research endeavors dedicated to investigating the relationship between colorectal carcinoma (CRC) and hepatocellular carcinoma (HCC), the underlying pathogenic mechanism remains largely elusive. The aim of this study is to shed light on the molecular mechanism involved in the development of this comorbidity. Methods: The gene expression profiles of CRC (GSE90627) and HCC (GSE45267) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) of psoriasis and atherosclerosis, three kinds of analyses were performed, namely, functional annotation, protein-protein interaction (PPI) network and module construction, and hub gene identification, survival analysis and co-expression analysis. Results: A total of 150 common downregulated differentially expressed genes and 148 upregulated differentially expressed genes were selected for subsequent analyses. The significance of chemokines and cytokines in the pathogenesis of these two ailments is underscored by functional analysis. Seven gene modules that were closely connected were identified. Moreover, the lipopolysaccharide-mediated signaling pathway is intricately linked to the development of both diseases. Finally, 10 important hub genes were identified using cytoHubba, including CDK1, KIF11, CDC20, CCNA2, TOP2A, CCNB1, NUSAP1, BUB1B, ASPM, and MAD2L1. Conclusion: Our study reveals the common pathogenesis of colorectal carcinoma and hepatocellular carcinoma. These common pathways and hub genes may provide new ideas for further mechanism research.

Integrated analysis identifies oxidative stress-related lncRNAs associated with progression and prognosis in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most common cancers in the world. Oxidative stress reactions have been reportedly associated with oncogenesis and tumor progression. By analyzing mRNA expression data and clinical information from The Cancer Genome Atlas (TCGA), we aimed to construct an oxidative stress-related long noncoding RNA (lncRNA) risk model and identify oxidative stress-related biomarkers to improve the prognosis and treatment of CRC.

RESULTS

Differentially expressed oxidative stress-related genes (DEOSGs) and oxidative stress-related lncRNAs were identified by using bioinformatics tools. An oxidative stress-related lncRNA risk model was constructed based on 9 lncRNAs (AC034213.1, AC008124.1, LINC01836, USP30-AS1, AP003555.1, AC083906.3, AC008494.3, AC009549.1, and AP006621.3) by least absolute shrinkage and selection operator (LASSO) analysis. The patients were then divided into high- and low-risk groups based on the median risk score. The high-risk group had a significantly worse overall survival (OS) (p < 0.001). Receiver operating characteristic (ROC) and calibration curves displayed the favorable predictive performance of the risk model. The nomogram successfully quantified the contribution of each metric to survival, and the concordance index and calibration plots demonstrated its excellent predictive capacity. Notably, different risk subgroups showed significant differences in terms of their metabolic activity, mutation landscape, immune microenvironment and drug sensitivity. Specifically, differences in the immune microenvironment implied that CRC patients in certain subgroups might be more responsive to immune checkpoint inhibitors.

CONCLUSIONS

Oxidative stress-related lncRNAs can predict the prognosis of CRC patients, which provides new insight for future immunotherapies based on potential oxidative stress targets.

Identification and validation of a novel stress granules-related prognostic model in colorectal cancer

Aims: A growing body of evidence demonstrates that Stress granules (SGs), a non-membrane cytoplasmic compartments, are important to colorectal development and chemoresistance. However, the clinical and pathological significance of SGs in colorectal cancer (CRC) patients is unclear. The aim of this study is to propose a new prognostic model related to SGs for CRC on the basis of transcriptional expression. Main methods: Differentially expressed SGs-related genes (DESGGs) were identified in CRC patients from TCGA dataset by limma R package. The univariate and Multivariate Cox regression model was used to construct a SGs-related prognostic prediction gene signature (SGPPGS). The CIBERSORT algorithm was used to assess cellular immune components between the two different risk groups. The mRNA expression levels of the predictive signature from 3 partial response (PR) and 6 stable disease (SD) or progress disease (PD) after neoadjuvant therapy CRC patients' specimen were examined. Key findings: By screening and identification, SGPPGS comprised of four genes (CPT2, NRG1, GAP43, and CDKN2A) from DESGGs is established. Furthermore, we find that the risk score of SGPPGS is an independent prognostic factor to overall survival. Notably, the abundance of immune response inhibitory components in tumor tissues is upregulated in the group with a high-risk score of SGPPGS. Importantly, the risk score of SGPPGS is associated with the chemotherapy response in metastatic colorectal cancer. Significance: This study reveals the association between SGs related genes and CRC prognosis and provides a novel SGs related gene signature for CRC prognosis prediction.

Exploration of an Prognostic Signature Related to Endoplasmic Reticulum Stress in Colorectal Adenocarcinoma and Their Response Targeting Immunotherapy

Background: Endoplasmic reticulum (ER) stress plays a pro-apoptotic role in colorectal adenocarcinoma (COAD). This study aimed to develop a novel ER-stress-related prognostic risk model for COAD and provide support for COAD cohorts with different risk score responses to immune checkpoint inhibitor therapies. Methods: TCGA-COAD and GSE39582 were included in this prospective study. Univariate and multivariate Cox analyses were performed to identify prognostic ER stress-related genes (ERSGs). Accordingly, the immune infiltration landscape and immunotherapy response in different risk groups were assessed. Finally, the expression of prognostic genes in 10 normal and 10 COAD tissue samples was verified using reverse transcription-quantitative polymerase chain reaction. Results: Eight prognostic genes were selected to establish an ERSG-based signature in the training set of the TCGA-COAD cohort. The accuracy of this was confirmed using a testing set of TCGA-COAD and GSE39582 cohorts. Gene set variation analysis indicated that differential functionality in high-low-risk groups was related to immune-related pathways. Corresponding to this, CD36, TIMP1, and PTGIS were significantly associated with 19 immune cells with distinct proportions between the different risk groups, such as central memory CD4T cells and central memory CD8T cells. Moreover, the risk score was considered effective for predicting the clinical response to immunotherapy, and the immunotherapy response was significantly and negatively correlated with the risk score of individuals with COAD. Furthermore, the immune checkpoint inhibitor treatment was less effective in the high-risk group, where the expression levels of PD-L1 and tumor immune dysfunction and exclusion scores in the high-risk group were significantly increased. Finally, the experimental results demonstrated that the expression trends of prognostic genes in clinical samples were consistent with the results from public databases. Conclusion: Our study established a novel risk signature to predict the COAD prognosis of patients and provide theoretical support for the clinical treatment of COAD.

CD163 as a Potential Biomarker in Colorectal Cancer for Tumor Microenvironment and Cancer Prognosis: A Swedish Study from Tissue Microarrays to Big Data Analyses

(1) Background: CD163, a specific macrophage receptor, affects the progression of malignant tumors. Unfortunately, the regulation and expression of CD163 are poorly understood. In this study, we determined the expressions of CD163 in TMA samples from CRC patients and combined them with patient data from several Swedish hospitals. (2) Methods: The expressions of CD163 in tissue samples from CRC patients were examined. After combining 472 CRC patients’ gene expression and 438 CRC patients’ clinical data with the TCGA database, 964 cases from the GEO database, and experimental expression data from 1247 Swedish CRC patients, we selected four genes (PCNA, LOX, BCL2, and CD163) and analyzed the tumor-infiltrating immune cells (TICs) and CRC prognosis. (3) Results: Based on histopathological TMA analysis, CD163 was strongly expressed in the stroma of both normal and cancer tissues, and the expressions in normal and cancer cells varied from negative to strong. The results from public databases show decreased expression of CD163 in cancer tissue compared to normal mucosa (|log FC| > 1 and FDR < 0.01), and it is a negative prognostic factor for CRC patients (p-value < 0.05). Through tumor microenvironment (TME) analysis, we found a potential influence of CD163 on immune cell infiltration. Furthermore, the enrichment analysis indicated the possible interaction with other proteins and biological pathways. (4) Conclusions: CD163 is expressed differently in CRC tissue and is a negative prognostic factor. Its expression is associated with the TME and tumor purity of CRC. Considering all results, CD163 has the potential to be a predictive biomarker in the investigation of CRC.

Apparent diffusion coefficient derived from diffusion-weighted imaging to differentiate between tumor, tumor-adjacent and tumor-distant tissues in resectable rectal adenocarcinoma

PURPOSE

To evaluate feasibility of apparent diffusion coefficient (ADC) at different b-values to differentiate between tumor, tumor-adjacent and tumor-distant tissues in rectal adenocarcinoma (RA).

MATERIALS AND METHODS

Seventy consecutive patients with RA undergoing preoperative diffusion-weighted imaging were retrospectively enrolled. ADCs of tumor, proximal tumor-adjacent tissue (PTA) and tumor-distant tissue (PTD), and distal tumor-adjacent tissue (DTA) and tumor-distant tissue (DTD) were calculated with b-values of 0 and 800 sec/mm2, 0 and 1000 sec/mm2, 0 and 1500 sec/mm2, and multiple b-values of 0, 50, 100, 800, 1000 and 1500 sec/mm2. Statistical analysis was performed to determine feasibility of ADC to differentiate between pairwise tissues.

RESULTS

Mean ADC of tumor was lower than those of PTA, PTD, DTA and DTD; and mean ADCs of PTA and DTA were lower than those of PTD and DTD at all b-values, respectively (all P-values < 0.001). ADC cut-offs of 1.089 × 10-3 mm2/sec (b = 0, 1000 sec/mm2) or 1.215 × 10-3 mm2/sec (b = 0, 800 sec/mm2), and 1.142 × 10-3 mm2/sec (b = 0, 1000 sec/mm2) or 0.995 × 10-3 mm2/sec (b = 0, 1500 sec/mm2) achieved excellent performance in differentiating tumor from PTA or PTD, and tumor from DTA or DTD (area under receiver operating characteristic curves [AUCs]: 0.813 or 0.952, and 0.970 or 0.996), respectively. ADC cut-offs of 1.625 × 10-3 mm2/sec (b = 0, 800 sec/mm2), and 1.165 × 10-3 mm2/sec (b = 0, 1500 sec/mm2) could differentiate PTA from PTD, and DTA from DTD (AUCs: 0.709 and 0.673), respectively.

CONCLUSION

ADC can help differentiate between tumor, tumor-adjacent and tumor-distant tissues in RA.

SELENBP1 inhibits progression of colorectal cancer by suppressing epithelial–mesenchymal transition

Selenium-binding protein 1 (SELENBP1) is frequently dysregulated in various malignancies including colorectal cancer (CRC); however, its roles in progression of CRCs and the underlying mechanism remain to be elucidated. In this study, we compared the expression of SELENBP1 between CRCs and colorectal normal tissues (NTs), as well as between primary and metastatic CRCs; we determined the association between SELENBP1 expression and CRC patient prognoses; we conducted both in vitro and in vivo experiments to explore the functional roles of SELENBP1 in CRC progression; and we characterized the potential underlying mechanisms associated with SELENBP1 activities. We found that the expression of SELENBP1 was significantly and consistently decreased in CRCs than that in adjacent NTs, while significantly and frequently decreased in metastatic than primary CRCs. High expression of SELENBP1 was an independent predictor of favorable prognoses in CRC patients. Overexpression of SELENBP1 suppressed, while silencing of SELENBP1 promoted cell proliferation, migration and invasion, and in vivo tumorigenesis of CRC. Mechanically, SELENBP1 may suppress CRC progression by inhibiting the epithelial–mesenchymal transition.

Field cancerization in breast cancer

Breast cancer affects one in seven women worldwide during their lifetime. Widespread mammographic screening programs and education campaigns allow for early detection of the disease, often during its asymptomatic phase. Current practice in treatment and recurrence monitoring is based primarily on pathological evaluations but can also encompass genomic evaluations, both of which focus on the primary tumor. Although breast cancer is one of the most studied cancers, patients still recur at a rate of up to 15% within the first 10 years post‐surgery. Local recurrence was originally attributed to tumor cells contaminating histologically normal (HN) tissues beyond the surgical margin, but advances in technology have allowed for the identification of distinct aberrations that exist in the peri‐tumoral tissues themselves. One leading theory to explain this phenomenon is the field cancerization theory. Under this hypothesis, tumors arise from a field of molecularly altered cells that create a permissive environment for malignant evolution, which can occur with or without morphological changes. The traditional histopathology paradigm dictates that molecular alterations are reflected in the tissue phenotype. However, the spectrum of inter‐patient variability of normal breast tissue may obfuscate recognition of a cancerized field during routine diagnostics. In this review, we explore the concept of field cancerization focusing on HN peri‐tumoral tissues: we present the pathological and molecular features of field cancerization within these tissues and discuss how the use of peri‐tumoral tissues can affect research. Our observations suggest that pathological and molecular evaluations could be used synergistically to assess risk and guide the therapeutic management of patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Drug Repositioning Based on the Reversal of Gene Expression Signatures Identifies TOP2A as a Therapeutic Target for Rectal Cancer

Rectal cancer is a common disease with high mortality rates and limited therapeutic options. Here we combined the gene expression signatures of rectal cancer patients with the reverse drug-induced gene-expression profiles to identify drug repositioning candidates for cancer therapy. Among the predicted repurposable drugs, topoisomerase II inhibitors (doxorubicin, teniposide, idarubicin, mitoxantrone, and epirubicin) presented a high potential to reverse rectal cancer gene expression signatures. We showed that these drugs effectively reduced the growth of colorectal cancer cell lines closely representing rectal cancer signatures. We also found a clear correlation between topoisomerase 2A (TOP2A) gene copy number or expression levels with the sensitivity to topoisomerase II inhibitors. Furthermore, CRISPR-Cas9 and shRNA screenings confirmed that loss-of-function of the TOP2A has the highest efficacy in reducing cellular proliferation. Finally, we observed significant TOP2A copy number gains and increased expression in independent cohorts of rectal cancer patients. These findings can be translated into clinical practice to evaluate TOP2A status for targeted and personalized therapies based on topoisomerase II inhibitors in rectal cancer patients.

Metabolic Flexibility in Canine Mammary Tumors: Implications of the Carnitine System

Deregulation of fatty acid catabolism provides an alternative energy source to glycolysis for cancer cell survival and proliferation. The regulator enzymes of the carnitine system (CS), responsible for the transport of fatty acids across mitochondrial membranes for β-oxidation are deregulated in tumorigenesis. Recently, we found that Carnitine Palmitoyl Transferase 1 (CPT1), a crucial regulator of CS components, is expressed and dysregulated in canine mammary tumor (CMT) tissues and cells. In this study, we examined the protein expression of the three remaining enzymes of CS (Carnitine Acylcarnitine Translocase (CACT), Carnitine Palmitoyl Transferase 2 (CPT2), Carnitine O-acetyltransferase (CrAT), in canine mammary cells and tissues by Western blot and immunohistochemistry. Protein expression of the components of CS was found in normal mammary glands and a concomitant deregulation of expression in CMT tissues that inversely correlated with the degree of tumor differentiation. Moreover, the expression and a different deregulation of CS-related proteins was also observed in CF33, CMT-U27, CMT-U309, and P114 cell lines used as in vitro model. These results demonstrate for the first time the expression of CS components in CMT tissues and cancer cells; however, further studies are needed to elucidate their roles in dogs as well.

Identification of a metabolic signature to predict overall survival for colorectal cancer

PURPOSE

Metabolic genes are associated with the occurrence and development of tumors. Metabolic-related risk models have showed partly prognostic predictive ability in cancers. However, the correlation between metabolic-related genes (MRGs) and the outcome of colorectal cancer is still poorly understood.

PATIENTS AND METHODS

TCGA database is used as the training cohort; while GSE39582 is the verification cohort. The least absolute shrinkage and selection operator Cox regression analysis were utilized to identify the MRGs and establish a genetic risk scoring model. A nomogram by integrating MRGs risk scores with TNM stage was constructed. The potential biological mechanisms were explored using gene set enrichment analysis. Associations of the signature with immune cell infiltrations and the tumor mutation burden (TMB) were also uncovered by Spearman rank test.

RESULTS

A six-gene metabolic signature was identified. Based on the risk scoring model with the signature, patients were divided into two groups (high-risk versus low-risk). The overall survival (OS) duration of patients with high-risk were quite shorter than those of low-risk patients (TCGA: p < .001, GSE39582: p < .001). Metabolic-related pathways were major enriched in low-risk group, while the high-risk group exhibited multiple immune-related pathways. Moreover, our signature was more linear dependent with antigen-presenting cell than effector immune cells, and a positive correction were seen between our signature and TMB.

CONCLUSION

Our research has discovered a six-gene metabolic signature to predict the OS of colorectal cancer. These genes may play significant roles in colorectal cancer regulating tumor microenvironment and serving as potential biomarkers for anti-cancer therapy.

TRIM39 deficiency inhibits tumor progression and autophagic flux in colorectal cancer via suppressing the activity of Rab7

The biological function of TRIM39, a member of TRIM family, remains largely unexplored in cancer, especially in colorectal cancer (CRC). In this study, we show that TRIM39 is upregulated in tumor tissues compared to adjacent normal tissues and associated with poor prognosis in CRC. Functional studies demonstrate that TRIM39 deficiency restrains CRC progression in vitro and in vivo. Our results further find that TRIM39 is a positive regulator of autophagosome–lysosome fusion. Mechanistically, TRIM39 interacts with Rab7 and promotes its activity via inhibiting its ubiquitination at lysine 191 residue. Depletion of TRIM39 inhibits CRC progression and autophagic flux in a Rab7 activity-dependent manner. Moreover, TRIM39 deficiency suppresses CRC progression through inhibiting autophagic degradation of p53. Thus, our findings uncover the roles as well as the relevant mechanisms of TRIM39 in CRC and establish a functional relationship between autophagy and CRC progression, which may provide promising approaches for the treatment of CRC.

Construction and validation of a metabolic risk model predicting prognosis of colon cancer

Metabolic genes have played a significant role in tumor development and prognosis. In this study, we constructed a metabolic risk model to predict the prognosis of colon cancer based on The Cancer Genome Atlas (TCGA) and validated the model by Gene Expression Omnibus (GEO). We extracted 753 metabolic genes and identified 139 differentially expressed genes (DEGs) from TCGA database. Then we conducted univariate cox regression analysis and Least Absolute Shrinkage and Selection Operator Cox regression analysis to identify prognosis-related genes and construct the metabolic risk model. An eleven-gene prognostic model was constructed after 1000 resamples. The gene signature has been proved to have an excellent ability to predict prognosis by Kaplan-Meier analysis, time-dependent receiver operating characteristic, risk score, univariate and multivariate cox regression analysis based on TCGA. Then we validated the model by Kaplan-Meier analysis and risk score based on GEO database. Finally, we performed a weighted gene co-expression network analysis and protein-protein interaction network on DEGs, and Kyoto Encyclopedia of Genes and Genomes pathways and Gene Ontology enrichment analyses were conducted. The results of functional analyses showed that most significantly enriched pathways focused on metabolism, especially glucose and lipid metabolism pathways.

AGA White Paper: Roadmap for the Future of Colorectal Cancer Screening in the United States

The American Gastroenterological Association's Center for Gastrointestinal Innovation and Technology convened a consensus conference in December 2018, entitled, "Colorectal Cancer Screening and Surveillance: Role of Emerging Technology and Innovation to Improve Outcomes." The goal of the conference, which attracted more than 60 experts in screening and related disciplines, including the authors, was to envision a future in which colorectal cancer (CRC) screening and surveillance are optimized, and to identify barriers to achieving that future. This White Paper originates from that meeting and delineates the priorities and steps needed to improve CRC outcomes, with the goal of minimizing CRC morbidity and mortality. A one-size-fits-all approach to CRC screening has not and is unlikely to result in increased screening uptake or desired outcomes owing to barriers stemming from behavioral, cultural, and socioeconomic causes, especially when combined with inefficiencies in deployment of screening technologies. Overcoming these barriers will require the following: efficient utilization of multiple screening modalities to achieve increased uptake; continued development of noninvasive screening tests, with iterative reassessments of how best to integrate new technologies; and improved personal risk assessment to better risk-stratify patients for appropriate screening testing paradigms.

Ribosome Biogenesis Alterations in Colorectal Cancer

Many studies have focused on understanding the regulation and functions of aberrant protein synthesis in colorectal cancer (CRC), leaving the ribosome, its main effector, relatively underappreciated in CRC. The production of functional ribosomes is initiated in the nucleolus, requires coordinated ribosomal RNA (rRNA) processing and ribosomal protein (RP) assembly, and is frequently hyperactivated to support the needs in protein synthesis essential to withstand unremitting cancer cell growth. This elevated ribosome production in cancer cells includes a strong alteration of ribosome biogenesis homeostasis that represents one of the hallmarks of cancer cells. None of the ribosome production steps escape this cancer-specific dysregulation. This review summarizes the early and late steps of ribosome biogenesis dysregulations described in CRC cell lines, intestinal organoids, CRC stem cells and mouse models, and their possible clinical implications. We highlight how this cancer-related ribosome biogenesis, both at quantitative and qualitative levels, can lead to the synthesis of ribosomes favoring the translation of mRNAs encoding hyperproliferative and survival factors. We also discuss whether cancer-related ribosome biogenesis is a mere consequence of cancer progression or is a causal factor in CRC, and how altered ribosome biogenesis pathways can represent effective targets to kill CRC cells. The association between exacerbated CRC cell growth and alteration of specific steps of ribosome biogenesis is highlighted as a key driver of tumorigenesis, providing promising perspectives for the implementation of predictive biomarkers and the development of new therapeutic drugs.

The emerging role of targeting cancer metabolism for cancer therapy

Glucose, as the main consuming nutrient of the body, faces different destinies in cancer cells. Glycolysis, oxidative phosphorylation, and pentose phosphate pathways produce different glucose-derived metabolites and thus affect cells' bioenergetics differently. Tumor cells' dependency to aerobic glycolysis and other cancer-specific metabolism changes are known as the cancer hallmarks, distinct cancer cells from normal cells. Therefore, these tumor-specific characteristics receive the limelight as targets for cancer therapy. Glutamine, serine, and fatty acid oxidation together with 5-lipoxygenase are main pathways that have attracted lots of attention for cancer therapy. In this review, we not only discuss different tumor metabolism aspects but also discuss the metabolism roles in the promotion of cancer cells at different stages and their difference with normal cells. Besides, we dissect the inhibitors potential in blocking the main metabolic pathways to introduce the effective and non-effective inhibitors in the field.

Non-Coding and Regulatory RNAs as Epigenetic Remodelers of Fatty Acid Homeostasis in Cancer

Cancer cells commonly display metabolic fluctuations. Together with the Warburg effect and the increased glutaminolysis, alterations in lipid metabolism homeostasis have been recognized as a hallmark of cancer. Highly proliferative cancer cells upregulate de novo synthesis of fatty acids (FAs) which are required to support tumor progression by exerting multiple roles including structural cell membrane composition, regulators of the intracellular redox homeostasis, ATP synthesis, intracellular cell signaling molecules, and extracellular mediators of the tumor microenvironment. Epigenetic modifications have been shown to play a crucial role in human development, but also in the initiation and progression of complex diseases. The study of epigenetic processes could help to design new integral strategies for the prevention and treatment of metabolic disorders including cancer. Herein, we first describe the main altered intracellular fatty acid processes to support cancer initiation and progression. Next, we focus on the most important regulatory and non-coding RNAs (small noncoding RNA-sncRNAs-long non-coding RNAs-lncRNAs-and other regulatory RNAs) which may target the altered fatty acids pathway in cancer.

Impaired Metabolic Pathways Related to Colorectal Cancer Progression and Therapeutic Implications

BACKGROUND

Risk of colorectal cancer (CRC) is defined by genetic predisposition and environmental factors that often co-occur and interact, resulting in diversiform biological reactions. The present study attempted to investigate transcriptome alteration and adaptation associated with CRC progression.

METHODS

The study consisted of patients who presented at Memorial Sloan-Kettering Cancer Center, Guangzhou, China with a colonic neoplasm in 1992-2004. Microarray GSE41258 of the study was acquired from Gene Expression Omnibus and 253 included microarrays were categorized by groups of normal colon, early primary tumor, lymph node metastases primary tumor, advanced primary tumor and distant metastases. Short Time-series Expression Miner (STEM) was applied to discover tumor grade-dependent gene expression patterns. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were carried out to explore functional enrichment of differential expression genes (DEGs).

RESULTS

Overall, 2870 significant DEGs were screened out on all groups. Six significant grade-dependent gene expression patterns were statistically significant. DEGs in all significant patterns were mainly assembled in GO terms of metastases and deterioration of tumor, epithelial proteins and cytokines, and protein binding and bridging. DEGs in profile 0 down-regulated with higher tumor grade, prominently enriched in KEGG pathways of metabolism.

CONCLUSION

Besides many well-known colorectal cancer-related pathways, DEGs of profiles especially those down-regulated with CRC progression, clustered in various metabolic pathways including starch and sucrose metabolism, fatty acid metabolism, nitrogen metabolism, as well as xenobiotics biotransformation that link to tumorigenesis, demonstrating the impairment of physiological metabolic pathways in the context of tumor progression. These results gave a high potential for therapeutic strategies.

Integrative Gene Expression Profiling Analysis to Investigate Potential Prognostic Biomarkers for Colorectal Cancer

BACKGROUND Despite noteworthy advancements in the multidisciplinary treatment of colorectal cancer (CRC) and deeper understanding in the molecular mechanisms of CRC, many of CRC patients with histologically identical tumors present different treatment response and prognosis. Thus, more evidence on novel predictive and prognostic biomarkers for CRC remains urgently needed. This study aims to identify potential prognostic biomarkers for CRC with integrative gene expression profiling analysis. MATERIAL AND METHODS Differential expression analysis of paired CRC and adjacent normal tissue samples in 6 microarray datasets was independently performed, and the 6 datasets were integrated by the robust rank aggregation method to detect consistent differentially expressed genes (DEGs). Aberrant expression patterns of these genes were further validated in RNA sequencing data. Then, gene set enrichment analysis (GSEA) was performed to investigate significantly dysregulated biological functions in CRC. Finally, univariate, LASSO and multivariate Cox regression models were built to identify key prognostic genes in CRC patients. RESULTS A total of 990 DEGs (495 downregulated and 495 upregulated genes) were acquired after integratedly analyzing the 6 microarray datasets, and 4131 DEGs (2050 downregulated and 2081 upregulated genes) were obtained from the RNA sequencing dataset. Subsequently, these DEGs were intersected and 885 consistent DEGs were finally identified, including 458 downregulated and 427 upregulated genes. Two risky prognostic genes (TIMP1 and LZTS3) and 5 protective prognostic genes (AXIN2, CXCL1, ITLN1, CPT2 and CLDN23) were identified, which were significantly associated with the prognosis of CRC. CONCLUSIONS The 7 genes that we identified would provide more evidence for further applying novel diagnostic and prognostic biomarkers in clinical practice to facilitate personalized treatment of CRC.

Metabolomic prostate cancer fields in HRMAS MRS-profiled histologically benign tissue vary with cancer status and distance from cancer

In this article, we review the state of the field of high resolution magic angle spinning MRS (HRMAS MRS)-based cancer metabolomics since its beginning in 2004; discuss the concept of cancer metabolomic fields, where metabolomic profiles measured from histologically benign tissues reflect patient cancer status; and report our HRMAS MRS metabolomic results, which characterize metabolomic fields in prostatectomy-removed cancerous prostates. Three-dimensional mapping of cancer lesions throughout each prostate enabled multiple benign tissue samples per organ to be classified based on distance from and extent of the closest cancer lesion as well as the Gleason score (GS) of the entire prostate. Cross-validated partial least squares-discriminant analysis separations were achieved between cancer and benign tissue, and between cancer tissue from prostates with high (≥4 + 3) and low (≤3 + 4) GS. Metabolomic field effects enabled histologically benign tissue adjacent to cancer to distinguish the GS and extent of the cancer lesion itself. Benign samples close to either low GS cancer or extensive cancer lesions could be distinguished from those far from cancer. Furthermore, a successfully cross-validated multivariate model for three benign tissue groups with varying distances from cancer lesions within one prostate indicates the scale of prostate cancer metabolomic fields. While these findings could, at present, be potentially useful in the prostate cancer clinic for analysis of biopsy or surgical specimens to complement current diagnostics, the confirmation of metabolomic fields should encourage further examination of cancer fields and can also enhance understanding of the metabolomic characteristics of cancer in myriad organ systems. Our results together with the success of HRMAS MRS-based cancer metabolomics presented in our literature review demonstrate the potential of cancer metabolomics to provide supplementary information for cancer diagnosis, staging, and patient prognostication.

A qualitative transcriptional signature for the early diagnosis of colorectal cancer

Currently, using biopsy specimens for the early diagnosis of colorectal cancer (CRC) is not entirely reliable due to insufficient sampling amount and inaccurate sampling location. Thus, it is necessary to develop a signature that can accurately identify patients with CRC under these clinical scenarios. Based on the relative expression orderings of genes within individual samples, we developed a qualitative transcriptional signature to discriminate CRC tissues, including CRC adjacent normal tissues from non-CRC individuals. The signature was validated using multiple microarray and RNA sequencing data from different sources. In the training data, a signature consisting of 7 gene pairs was identified. It was well validated in both biopsy and surgical resection specimens from multiple datasets measured by different platforms. For biopsy specimens, 97.6% of 42 CRC tissues and 94.5% of 163 non-CRC (normal or inflammatory bowel disease) tissues were correctly classified. For surgically resected specimens, 99.5% of 854 CRC tissues and 96.3% of 81 CRC adjacent normal tissues were correctly identified as CRC. Notably, we additionally measured 33 CRC biopsy specimens by the Affymetrix platform and 13 CRC surgical resection specimens, with different proportions of tumor epithelial cells, ranging from 40% to 100%, by the RNA sequencing platform, and all these samples were correctly identified as CRC. The signature can be used for the early diagnosis of CRC, which is also suitable for minimum biopsy specimens and inaccurately sampled specimens, and thus has potential value for clinical application.

Diabetes-mediated promotion of colon mucosa carcinogenesis is associated with mitochondrial dysfunction

Type 2 diabetes mellitus (T2DM) has been associated with an increased risk of cancer, including colon cancer (CC). However, we recently reported no influence of T2DM on CC prognosis, suggesting that any effect might be at the early stages of tumor development. We hypothesized that T2DM may create an environment in the healthy tissue, which acts as a carcinogenesis driver in agreement with the field of cancerization concept. Here, we focused on early carcinogenesis by analyzing paired tumor and normal colonic mucosa samples from the same patients. The proteome of CC and paired mucosa was quantitatively analyzed in 28 individuals (12 diabetics and 16 nondiabetics) by mass spectrometry with isobaric labeling. Out of 3076 identified proteins, 425 were differentially expressed at the tumor in diabetics compared with nondiabetics. In the adjacent mucosa, 143 proteins were differentially expressed in diabetics and nondiabetics. An enrichment analysis of this signature pointed to mitochondria, ribosome, and translation. Only six proteins were upregulated by diabetes both in tumor and mucosa, of which five were mitochondrial proteins. Differential expression in diabetic versus nondiabetic mucosa was confirmed for MRPL53, MRPL18, and TIMM8B. Higher levels of MRPL18, TIMM8B, and EIF1A were also found in normal colon epithelial cells exposed to high‐glucose conditions. We conclude that T2DM is associated with specific molecular changes in the normal mucosa of CC patients, consistent with field of cancerization in a diabetic environment. The mitochondrial protein signature identifies a potential therapeutic target that could underlie the higher risk of CC in diabetics.

[Medium-chain acyl-CoA dehydrogenase enhances invasion and metastasis ability of breast cancer cells]

OBJECTIVE

To investigate the effect of medium-chain acyl-CoA dehydrogenase (ACADM) on invasion and metastasis of breast cancer cells and explore the underlying mechanism.

METHODS

A large cancer genome database was used to analyze the expression of ACADM in breast cancer tissues and normal tissues. The proliferation, migration and invasion of cultured breast cancer MCF-7 and T47D cells with ACADM overexpression or ACADM silencing were evaluated using MTT proliferation assay, EdU assay, Transwell chamber assay, and Boyden invasion assay; Western blotting was used to detect the protein expressions of the related pathway in the cells. In nude mouse models of tail vein metastasis of MCF-7 cells with or without ACADM overexpression, the tumor growth and tumor histopathology were observed using HE staining.

RESULTS

Analysis of the Oncomine sample set showed a significantly higher expression level of ACADM in breast cancer tissues than in normal breast tissues (P &lt; 0.05). Overexpression of ACADM obviously enhanced the migration and invasion abilities and promoted the epithelial-mesenchymal transition (EMT) of cultured MCF-7 and T47D cells; conversely, silencing of ACADM significantly suppressed the migration and invasion of the breast cancer cells. In the nude mouse models, ACADM overexpression in MCF-7 cells significantly enhanced their in vivo migration and invasion abilities.

CONCLUSIONS

ACADM can promote the EMT process of breast cancer cells and improve the migration and invasion ability. ACADM is an oncogene in breast cancer.

Radiogenomic Analysis of F-18-Fluorodeoxyglucose Positron Emission Tomography and Gene Expression Data Elucidates the Epidemiological Complexity of Colorectal Cancer Landscape

PURPOSE

Transcriptomic profiling has enabled the neater genomic characterization of several cancers, among them colorectal cancer (CRC), through the derivation of genes with enhanced causal role and informative gene sets. However, the identification of small-sized gene signatures, which can serve as potential biomarkers in CRC, remains challenging, mainly due to the great genetic heterogeneity of the disease.

METHODS

We developed and exploited an analytical framework for the integrative analysis of CRC datasets, encompassing transcriptomic data and positron emission tomography (PET) measurements. Profiling data comprised two microarray datasets, pertaining biopsy specimen from 30 untreated patients with primary CRC, coupled by their F-18-Fluorodeoxyglucose (FDG) PET values, using tracer kinetic analysis measurements. The computational framework incorporates algorithms for semantic processing, multivariate analysis, data mining and dimensionality reduction.

RESULTS

Transcriptomic and PET data feature sets, were evaluated for their discrimination performance between primary colorectal adenocarcinomas and adjacent normal mucosa. A composite signature was derived, pertaining 12 features: 7 genes and 5 PET variables. This compact signature manifests superior performance in classification accuracy, through the integration of gene expression and PET data.

CONCLUSIONS

This work represents an effort for the integrative, multilayered, signature-oriented analysis of CRC, in the context of radio-genomics, inferring a composite signature with promising results for patient stratification.

When fats commit crimes: fatty acid metabolism, cancer stemness and therapeutic resistance

The role of fatty acid metabolism, including both anabolic and catabolic reactions in cancer has gained increasing attention in recent years. Many studies have shown that aberrant expression of the genes involved in fatty acid synthesis or fatty acid oxidation correlate with malignant phenotypes including metastasis, therapeutic resistance and relapse. Such phenotypes are also strongly associated with the presence of a small percentage of unique cells among the total tumor cell population. This distinct group of cells may have the ability to self-renew and propagate or may be able to develop resistance to cancer therapies independent of genetic alterations. Therefore, these cells are referred to as cancer stem cells/tumor-initiating cells/drug-tolerant persisters, which are often refractory to cancer treatment and difficult to target. Moreover, interconversion between cancer cells and cancer stem cells/tumor-initiating cells/drug-tolerant persisters may occur and makes treatment even more challenging. This review highlights recent findings on the relationship between fatty acid metabolism, cancer stemness and therapeutic resistance and prompts discussion about the potential mechanisms by which fatty acid metabolism regulates the fate of cancer cells and therapeutic resistance.

The carnitine system and cancer metabolic plasticity

Metabolic flexibility describes the ability of cells to respond or adapt its metabolism to support and enable rapid proliferation, continuous growth, and survival in hostile conditions. This dynamic character of the cellular metabolic network appears enhanced in cancer cells, in order to increase the adaptive phenotype and to maintain both viability and uncontrolled proliferation. Cancer cells can reprogram their metabolism to satisfy the energy as well as the biosynthetic intermediate request and to preserve their integrity from the harsh and hypoxic environment. Although several studies now recognize these reprogrammed activities as hallmarks of cancer, it remains unclear which are the pathways involved in regulating metabolic plasticity. Recent findings have suggested that carnitine system (CS) could be considered as a gridlock to finely trigger the metabolic flexibility of cancer cells. Indeed, the components of this system are involved in the bi-directional transport of acyl moieties from cytosol to mitochondria and vice versa, thus playing a fundamental role in tuning the switch between the glucose and fatty acid metabolism. Therefore, the CS regulation, at both enzymatic and epigenetic levels, plays a pivotal role in tumors, suggesting new druggable pathways for prevention and treatment of human cancer.