Advances in prognostic markers for colorectal cancer

ENO1 deletion potentiates ferroptosis and decreases glycolysis in colorectal cancer cells via AKT/STAT3 signaling

Colorectal cancer (CRC) is one of the most prevailing and lethal forms of cancer globally. α-enolase (ENO1) has been well documented to be involved in the progression and drug resistance of CRC. The present study was designed to specify the role of ENO1 in major events during the process of CRC and to introduce its latent functional mechanism. ENO1 expression was determined by western blot analysis. Extracellular acidification rates were assessed using an XF96 extracellular flux analyzer. Glucose uptake, lactic acid production, total iron levels and ferroptosis-related markers were examined with corresponding kits. A dichlorodihydrofluorescein diacetate probe measured intracellular reactive oxygen species content. Western blotting detected the expression of glycolysis- and ferroptosis-related proteins. CCK-8 and EdU staining assays assessed cell proliferation. In the current study, ENO1 was highly expressed in CRC cells. Knockdown of ENO1 markedly reduced the glycolysis and accelerated the ferroptosis in CRC cells. Moreover, the inhibitory effects of WZB117, a specific inhibitor of glycolysis-related glucose transporter type 1, on CRC cell proliferation were further enhanced by ENO1 interference. In addition, silencing of ENO1 inactivated the AKT/STAT3 signaling. The AKT activator SC79 partially reversed the effects of ENO1 deficiency on the AKT/STAT3 signaling, glycolysis, proliferation as well as ferroptosis in CRC cells. In summary, inactivation of AKT/STAT3 signaling mediated by ENO1 inhibition might boost the ferroptosis and suppress the glycolysis in CRC cells.

Exploring molecular markers and drug candidates for colorectal cancer through comprehensive bioinformatics analysis

Colorectal cancer (CRC) often has a poor prognosis and identifying useful and novel agents for treating CRC is urgently required. This study aimed to examine molecular markers associated with CRC prognosis and to identify potential drug candidates. The differentially expressed genes (DEGs) of CRC in TCGA were identified. The genes associated with CRC, summarized from NCBI-gene, OMIM, and the DEGs, were used to construct a co-expression network by WGCNA. Moreover, the co-expression genes from modules of interest were used to carry out functional enrichment. A total of 2742 DEGs, including 1674 upregulated and 1068 downregulated genes, were identified. Thirteen co-expression modules were constructed with WGCNA. Brown and blue co-expression modules with significant differences in disease phenotype were found. Functional enrichment analysis showed that genes in the brown module were mainly related to cell cycle, cell proliferation, DNA replication, and RNA transport. The genes in the blue module were mainly associated with fatty acid degradation, sulfur metabolism, PPAR signaling pathway and bile secretion. In addition, both the genes in brown and blue were associated with tumor staging. Some prognostic markers and candidate small molecules drugs for CRC treatment were identified. In conclusion, we revealed molecular biomarker profiles in CRC by systematic bioinformatics analysis, constructed regulatory networks of mRNA, ncRNA and transcriptional regulators (TFs), and identified potential drugs targeting hub proteins and TFs.

Identification of ZMYND19 as a novel biomarker of colorectal cancer: RNA-sequencing and machine learning analysis

Colorectal cancer (CRC) is the third most common cause of cancer-related deaths. The five-year relative survival rate for CRC is estimated to be approximately 90% for patients diagnosed with early stages and 14% for those diagnosed at an advanced stages of disease, respectively. Hence, the development of accurate prognostic markers is required. Bioinformatics enables the identification of dysregulated pathways and novel biomarkers. RNA expression profiling was performed in CRC patients from the TCGA database using a Machine Learning approach to identify differential expression genes (DEGs). Survival curves were assessed using Kaplan-Meier analysis to identify prognostic biomarkers. Furthermore, the molecular pathways, protein-protein interaction, the co-expression of DEGs, and the correlation between DEGs and clinical data have been evaluated. The diagnostic markers were then determined based on machine learning analysis. The results indicated that key upregulated genes are associated with the RNA processing and heterocycle metabolic process, including C10orf2, NOP2, DKC1, BYSL, RRP12, PUS7, MTHFD1L, and PPAT. Furthermore, the survival analysis identified NOP58, OSBPL3, DNAJC2, and ZMYND19 as prognostic markers. The combineROC curve analysis indicated that the combination of C10orf2 -PPAT- ZMYND19 can be considered as diagnostic markers with sensitivity, specificity, and AUC values of 0.98, 1.00, and 0.99, respectively. Eventually, ZMYND19 gene was validated in CRC patients. In conclusion, novel biomarkers of CRC have been identified that may be a promising strategy for early diagnosis, potential treatment, and better prognosis.

Development of an immune-related gene prognostic risk model and identification of an immune infiltration signature in the tumor microenvironment of colon cancer

BACKGROUND

Colon cancer is a common and highly malignant tumor. Its incidence is increasing rapidly with poor prognosis. At present, immunotherapy is a rapidly developing treatment for colon cancer. The aim of this study was to construct a prognostic risk model based on immune genes for early diagnosis and accurate prognostic prediction of colon cancer.

METHODS

Transcriptome data and clinical data were downloaded from the cancer Genome Atlas database. Immunity genes were obtained from ImmPort database. The differentially expressed transcription factors (TFs) were obtained from Cistrome database. Differentially expressed (DE) immune genes were identified in 473 cases of colon cancer and 41 cases of normal adjacent tissues. An immune-related prognostic model of colon cancer was established and its clinical applicability was verified. Among 318 tumor-related transcription factors, differentially expressed transcription factors were finally obtained, and a regulatory network was constructed according to the up-down regulatory relationship.

RESULTS

A total of 477 DE immune genes (180 up-regulated and 297 down-regulated) were detected. We developed and validated twelve immune gene models for colon cancer, including SLC10A2, FABP4, FGF2, CCL28, IGKV1-6, IGLV6-57, ESM1, UCN, UTS2, VIP, IL1RL2, NGFR. The model was proved to be an independent prognostic variable with good prognostic ability. A total of 68 DE TFs (40 up-regulated and 23 down-regulated) were obtained. The regulation network between TF and immune genes was plotted by using TF as source node and immune genes as target node. In addition, Macrophage, Myeloid Dendritic cell and CD4⁺ T cell increased with the increase of risk score.

CONCLUSION

We developed and validated twelve immune gene models for colon cancer, including SLC10A2, FABP4, FGF2, CCL28, IGKV1-6, IGLV6-57, ESM1, UCN, UTS2, VIP, IL1RL2, NGFR. This model can be used as a tool variable to predict the prognosis of colon cancer.

IL1RN and PRRX1 as a Prognostic Biomarker Correlated with Immune Infiltrates in Colorectal Cancer: Evidence from Bioinformatic Analysis

The extensive morbidity of colorectal cancer (CRC) and the inferior prognosis of terminal CRC urgently call for reliable prognostic biomarkers. For this, we identified 704 differentially expressed genes (DEGs) by intersecting three datasets, GSE41328, GSE37364, and GSE15960 from Gene Expression Omnibus database, to maximize the accuracy of the results. Preliminary analysis of the DEGs was then performed using online gene analysis datasets, such as DAVID, UCSC Cancer Genome Browser, CBioPortal, STRING, and UCSC Cancer Genome Browser. Cytoscape was utilized to visualize the protein perception interaction network of DEGs, and the bubble map of GO and KEGG enrichment function was demonstrated using the R package. The Molecular Complex Detection (MCODE), Biological Network Gene Oncology (BiNGO) plug-in in Cytoscape, was applied to further screen the DEGs to obtain 15 seed genes, which were IL1RN, GALNT12, ADH6, SCN7A, CXCL1, FGF18, SOX9, ACACB, PRRX1, MZB1, SLC22A3, CNNM4, LY6E, IFITM2, and GDPD3. Among them, IL1RN, ADH6, SCN7A, ACACB, MZB1, and GDPD3 exhibited statistically significant survival differences, whereas limited studies were conducted in CRC. Based on the enrichment results of the "Gene Ontology"(GO) and "Kyoto Encyclopedia of Genes and genomes "(KEGG) as well as documented findings of key genes, we further emphasized the potential of IL1RN and PRRX1 as markers of immune infiltrates in CRC and confirmed our hypothesis by compiling data from the UALCAN, Tumor Immune Estimation Resource, and TISIDB databases for these two genes. The above-mentioned genes might offer a valuable insight into the diagnosis, immunotherapeutic targets, and prognosis of CRC.

FBXW7 and Its Downstream NOTCH Pathway Could be Potential Indicators of Organ-Free Metastasis in Colorectal Cancer

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths globally. Metastasis is associated with a poor prognosis, yet the underlying molecular mechanism(s) remained largely unknown. In this study, a total of 85 CRC patients were included and the primary tumor lesions were evaluated by next-generation sequencing using a targeted panel for genetic aberrations. Patients were sub-divided according to their metastasis pattern into the non-organ metastases (Non-OM) and organ metastases (OM) groups. By comparing the genetic differences between the two groups, we found that mutations in FBXW7 and alterations in its downstream NOTCH signaling pathway were more common in the Non-OM group. Moreover, correlation analysis suggested that FBXW7 mutations were independent of other somatic alterations. The negative associations of alterations in FBXW7 and its downstream NOTCH signaling pathway with CRC organ metastasis were validated in a cohort of 230 patients in the TCGA CRC dataset. Thus, we speculated that the genomic alterations of FBXW7/NOTCH axis might be an independent negative indicator of CRC organ metastases.

Expression of Spermine Oxidase Is Associated with Colorectal Carcinogenesis and Prognosis of Patients

Uncovering tumor markers of colorectal cancer is important for the early detection and prognosis of the patients. Spermine oxidase (SMOX) is upregulated in various cancers. The present study aims to explore the biologic function and expression patterns of SMOX in colorectal cancer (CRC), the third most common type of cancer worldwide. We used quantitative real-time PCR, Western blot, and in vitro functional studies in four CRC cell lines knocked down by SMOX siRNA and immunohistochemistry in 350 cases of CRC tissues. The results showed that SMOX was overexpressed in CRC cell lines and clinical samples. SMOX overexpression in tumor tissues was an independent prognostic factor, worsening overall survival (p = 0.001). The knock-down of SMOX inhibited CRC cell proliferation, invasion, and soft agar colony formation, uncovering its carcinogenic functions. This study indicated that SMOX overexpression could be an important oncogene in CRC and might serve as a valuable prognostic marker and potential therapeutic target for CRC.

An age stratified analysis of the biomarkers in patients with colorectal cancer

Colorectal cancer (CRC), a common malignant tumor of the digestive tract, has a high incidence and mortality rate. Several recent studies have found that aging is associated with the increasing risk of cancer. Nevertheless, the expression status and function of age-related genes in CRC is still not well understood. In the study, we comprehensively analyzed the gene expression data of CRC patients from The Cancer Genome Atlas (TCGA) database. Age-related differential expression genes (age-related DEGs) in tumor tissues compared with normal tissues of CRC were further identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of age-related DEGs were performed by clusterProfiler of R. Afterwards, we used the STRING database to map the protein-protein interaction network of DEGs. We constructed prognostic model through univariate and multivariate COX regression analyses, and further evaluated their predictive power. The prognostic gene signature-related functional pathways were explored by gene set enrichment analysis (GSEA). The weighted gene co-expression network analysis (WGCNA) was used to identify key module associated with two prognostic gene signatures. Finally, we used the Metascape to perform functional enrichment analysis of genes in the key module. A total of 279 age-related DEGs were identified from the TCGA database. GO and KEGG enrichment analysis showed that the age-related DEGs were enriched in the Modulation of chemical synaptic transmission and Neuroactive ligand-receptor interaction. Moreover, we established a novel age-related gene signature (DLX2 and PCOLCE2) for overall survival in CRC, which was further predicted in both the training and validation sets. The results of GSEA demonstrated that numerous disease-related pathways were enriched in the high-risk group. We identified 43 genes related to the DLX2 and PCOLCE2 by the WGCNA co-expression network. We also found that these 43 genes were enriched in the cancer-related pathways. To sum up, the study identified an age-related gene signature for predicting the prognosis of CRC patients, which is conducive to the identification of novel prognostic molecular markers.

Development and Application of Patient-Derived Cancer Organoidsin Clinical Management of Gastrointestinal Cancer: A State-of-the-Art Review

Human gastrointestinal cancer (e.g., gastric cancer and colorectal cancer) has been a leading cause of cancer-related deaths worldwide and has imposed a great threat to the public health. Although early-stage gastrointestinal cancer can be effectively treated by surgery, followed by postoperative chemotherapy, patients with advanced gastrointestinal cancer often exhibit poor prognosis and cancer relapse due to the absence of effective personalized treatment strategies. Patient-derived cancer organoid technology has been rapidly developed in recent years, and its emergence has opened up an unprecedented approach to model human cancers in vitro. Patient-derived cancer organoids involve the ex vivo culture of fragments of freshly resected human tumors that retain the histological features of original tumors. This review thoroughly discussed the evolutionary process of human gastrointestinal organoids cultured since 2009, and highlighted the potentials of patient-derived cancer organoids in clinical management of gastrointestinal cancer in terms of advances achieved in cancer modelling compared with conventional modelling methods, high-throughput drug screening, and development of personalized treatment selection. Additionally, the current limitations of patient-derived cancer organoids and the potential solutions to overcome these problems were summarized.

Down-regulation of IGHG1 enhances Protoporphyrin IX accumulation and inhibits hemin biosynthesis in colorectal cancer by suppressing the MEK-FECH axis

Immunoglobulin γ-1 heavy chain constant region (IGHG1) is a functional isoform of immunoglobulins and plays an important role in the cytolytic activity of immune effector cells. Dysregulated IGHG1 was implicated in the occurrence and development of various tumors. Protoporphyrin IX (PpIX) is an endogenous fluorophore and is used in photodynamic therapy, which induces the generation of reactive oxygen species to initiate the death of tumor cells. However, the roles of IGHG1 in the colorectal cancer cell proliferation and PpIX accumulation have not been reported yet. Data from qRT-PCR and western blot analysis showed that IGHG1 was up-regulated in the colorectal cancer cells. Colorectal cancer cells were then transfected with shRNA targeting IGHG1 to down-regulate IGHG1 and conducted with Cell Counting Kit 8 (CCK8) and colony formation assays. Results demonstrated that shRNA-mediated down-regulation of IGHG1 decreased cell viability of colorectal cancer and suppressed cell proliferation. Moreover, PpIX accumulation was promoted and the hemin content was decreased by the silence of IGHG1. Interference of IGHG1 reduced the phosphorylated extracellular signal-regulated kinase (ERK) and ferrochelatase (FECH) expression, resulting in retarded cell proliferation in an MEK-FECH axis-dependent pathway.

Revisiting social MPE: an integration of molecular pathological epidemiology and social science in the new era of precision medicine

INTRODUCTION

Molecular pathological epidemiology (MPE) is an integrative transdisciplinary area examining the relationships between various exposures and pathogenic signatures of diseases. In line with the accelerating advancements in MPE, social science and its health-related interdisciplinary areas have also developed rapidly. Accumulating evidence indicates the pathological role of social-demographic factors. We therefore initially proposed social MPE in 2015, which aims to elucidate etiological roles of social-demographic factors and address health inequalities globally. With the ubiquity of molecular diagnosis, there are ample opportunities for researchers to utilize and develop the social MPE framework.

AREAS COVERED

Molecular subtypes of breast cancer have been investigated rigorously for understanding its etiologies rooted from social factors. Emerging evidence indicates pathogenic heterogeneity of neurological disorders such as Alzheimer's disease. Presenting specific patterns of social-demographic factors across different molecular subtypes should be promising for advancing the screening, prevention, and treatment strategies of those heterogeneous diseases. This article rigorously reviewed literatures investigating differences of race/ethnicity and socioeconomic status across molecular subtypes of breast cancer and Alzheimer's disease to date.

EXPERT OPINION

With advancements of the multi-omics technologies, we foresee a blooming of social MPE studies, which can address health disparities, advance personalized molecular medicine, and enhance public health.

Identification of NEO1 as a prognostic biomarker and its effects on the progression of colorectal cancer

Background

Due to the high morbidity and poor clinical outcomes, early predictive and prognostic biomarker identification is desiderated in colorectal cancer (CRC). As a homologue of the Deleted in Colorectal Cancer (DCC) gene, the role of Neogenin-1 (NEO1) in CRC remained unveiled. This study was designed to probe into the effects and potential function of NEO1 in CRC.

Methods

Online databases, Gene Set Enrichment Analysis (GSEA), quantitative real-time PCR and western blotting were used to evaluate NEO1 expression in colorectal cancer tissues. Survival analysis was performed to predict the prognosis of CRC patients based on NEO1 expression level. Then, cell proliferation was detected by colony formation and Cell Counting Kit 8 (CCK-8) assays. CRC cell migration and invasion were examined by transwell assays. Finally, we utilized the Gene Set Variation Analysis (GSVA) and GSEA to dig the potential mechanisms of NEO1 in CRC.

Results

Oncomine database and The Cancer Genome Atlas (TCGA) database showed that NEO1 was down-regulated in CRC. Further results validated that NEO1 mRNA and protein expression were both significantly lower in CRC tumor tissues than in the adjacent tissues in our clinical samples. NEO1 expression was decreased with the progression of CRC. Survival and other clinical characteristic analyses exhibited that low NEO1 expression was related with poor prognosis. A gain-of-function study showed that overexpression of NEO1 restrained proliferation, migration and invasion of CRC cells while a loss-of-function showed the opposite effects. Finally, functional pathway enrichment analysis revealed that NEO1 low expression samples were enriched in inflammation-related signaling pathways, EMT and angiogenesis.

Conclusion

A tumor suppressor gene NEO1 was identified and verified to be correlated with the prognosis and progression of CRC, which could serve as a prognostic biomarker for CRC patients.

Enhanced expression of GABRD predicts poor prognosis in patients with colon adenocarcinoma

Neurotransmitters are reported to be involved in tumor initiation and progression. This study aimed to elucidate the prognostic value of γ-aminobutyric acid type A receptor δ subunit (GABRD) in colon adenocarcinoma (COAD) using the data from The Cancer Genome Atlas (TCGA) database. The GABRD mRNA expression levels in the COAD and normal tissues were compared using the Wilcoxon rank-sum test. The correlation between clinicopathologic characteristics and GABRD expression was analyzed by Wilcoxon rank-sum test or Kruskal-Wallis test and logistic regression. The prognostic value of GABRD mRNA expression in patients with COAD was determined using the Kaplan-Meier curve and Cox regression analysis. Finally, the molecular mechanisms of GABRD in COAD were predicted by gene set enrichment analysis (GSEA). The COAD tissues exhibited higher GABRD mRNA expression levels than the normal tissues. The logistic regression analysis revealed that GABRD mRNA expression was correlated with TNM stage, N stage, M stage, and microsatellite instability (MSI) status. The Kaplan-Meier survival curve and log-rank test revealed that patients with COAD exhibiting high GABRD mRNA expression were associated with poor overall survival (OS). The multivariate analysis indicated that increased GABRD mRNA expression was an independent prognostic factor and was correlated with a poor OS. The GSEA revealed that GABRD was involved in signaling pathways, including cell adhesion molecules, gap junction, melanogenesis, and mTOR signaling pathway, as well as the signaling pathways associated with basal cell carcinoma or bladder cancer development. In summary, enhanced GABRD mRNA expression may be a potential independent prognostic biomarker for COAD.

Proteogenomic biomarkers in colorectal cancers: clinical applications

INTRODUCTION

Colorectal cancer (CRC) is one of the leading cancers in terms of incidence and mortality, rate requiring a multidisciplinary approach. The discovery of specific CRC biomarkers has caused a paradigm shift in its clinical management.

AREAS COVERED

The aim is to illustrate the possible clinical applications of CRC biomarkers through an updated literature review (from 2015 to 2020) based on the PubMed database. A relationship between cancer localization and genetic profile has been identified. Nowadays, the tumor markers are largely used to select patients that could really benefit from a specific type of adjuvant therapy, in order to optimize treatment programs, especially in metastatic patients. This review highlights both CRC biomarkers' advantages and critical issues.

EXPERT OPINION

New biomarker discoveries allow to set noninvasive tests that could increase patient's compliance with therapy. They also permit a cost-effective early diagnosis, as well as patient-tailored treatments, improving the overall survival. The CRC biomarkers could also have a prognostic value, and usually, they are included in follow-up programs. However, despite the continuous progression of new technologies, their clinical validation is still debated. In this context, additional clinical studies are still necessary to identify, among potential markers, the most effective ones.

Clinical Significance and Prognostic Value of miR-28-5p in Colon Cancer

Background

The association of miR-28-5p with colon cancer remains to be elucidated. This study aimed to determine the clinical significance and prognostic value of miR-28-5p in colon cancer.

Methods

We retrospectively analyzed the data of miR-28-5p in colon adenocarcinoma data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and the data was divided into cancer group and normal group, respectively. Forty colon cancer tissues and adjacent normal tissues were collected and tested by qRT-PCR methods. The difference of the miR-28-5p expression between colon cancer and normal tissues was compared. The clinical significance of miR-28-5p in colon cancer and the association with the survival were determined. The predictive value of miR-28-5p in clinical features was determined using receiver operating characteristic curve. The target genes of miR-28-5p were identified, and the functional of target genes was performed using bioinformatics analysis.

Results

: The expression of miR-28-5p was increased in colon cancer tissues compared with normal controls (p = 0.037). The expression of miR-28-5p was significantly increased in tissues with distant metastases compared with that without distant metastases (p = 0.026). Patients with high expression of miR-28-5p have a shorter survival time than those with low expression (p = 0.004). Cox analysis showed that miR-28-5p was an independent predictor for the survival of patients (p = 0.014). Combination of miR-28-5p with TNM stage and clinical stage can improve the prognostic value for the patients (p < 0.05). miR-28-5p has a moderate predictive value in predicting the TNM stage and clinical stage (T stage: AUC = 0.515; N stage: AUC = 0.523, M stage: AUC = 0.572; clinical stage: AUC = 0.539). 711 potential target genes of miR-28-5p were screened; their function and pathways were identified.

Conclusions

: This study demonstrated that miR-28-5p was increased in colon cancer and can be an independent indicator for the overall survival in patients with colon cancer.

Update on urine as a biomarker in cancer: a necessary review of an old story

Introduction: Cancer causes thousands of deaths worldwide each year. Therefore, monitoring of health status and the early diagnosis of cancer using noninvasive assays, such as the analysis of molecular biomarkers in urine, is essential. However, effective biomarkers for early diagnosis of cancer have not been established in many types of cancer.Areas covered: In this review, we discuss recent findings with regard to the use of urine composition as a biomarker in eleven types of cancer. We also highlight the use of urine biomarkers for improving early diagnosis.Expert opinion: Urinary biomarkers have been applied for clinical application of early diagnosis. The main limitation is a lack of integrated approaches for identification of new biomarkers in most cancer. The utilization of urinary biomarker detection will be promoted by improved detection methods and new data from different types of cancers. With the development of precision medicine, urinary biomarkers will play an increasingly important clinical role. Future early diagnosis would benefit from changes in the utilization of urinary biomarkers.

CHIP-mediated ubiquitination of Galectin-1 predicts colorectal cancer prognosis

CHIP and Galectin-1 are associated with the development of metastasis in cancer. However, the precise roles of CHIP or Gal1 in colorectal cancer are uncertain. Here, our study explored the relationship and clinical significance of CHIP or Gal1 in CRC. CHIP or Gal1 expression was significantly decreased or up-regulated in CRC compared with adjacent noncancerous tissues by immunohistochemistry on a CRC tissue microarray, respectively. Low CHIP or high Gal1 expression significantly correlated with clinicopathological characteristics in patients, as well as with shorter overall survival. Multivariate Cox regression analysis revealed that CHIP or Gal1 expression was an independent prognostic factor for CRC patients. Moreover, CHIP associated with Gal1 has a synergistic effect on the prediction of CRC prognosis. In vitro and vivo, high CHIP or low Gal1 expression inhibit CRC growth or metastasis. Our results found that CHIP could degradate Gal1 by ubiquitination. In summary, CHIP could inhibit CRC growth or metastasis through promoting Gal1 ubiquitination and degradation by proteasome. CHIP and Gal1 expressions are novel candidate prognostic markers in CRC. A combined effect of CHIP and Gal1 as efficient prognostic indicators was found for the first time.

Energy Restriction and Colorectal Cancer: A Call for Additional Research

: Colorectal cancer has the second highest cancer-related mortality rate, with an estimated 881,000 deaths worldwide in 2018. The urgent need to reduce the incidence and mortality rate requires innovative strategies to improve prevention, early diagnosis, prognostic biomarkers, and treatment effectiveness. Caloric restriction (CR) is known as the most robust nutritional intervention that extends lifespan and delays the progression of age-related diseases, with remarkable results for cancer protection. Other forms of energy restriction, such as periodic fasting, intermittent fasting, or fasting-mimicking diets, with or without reduction of total calorie intake, recapitulate the effects of chronic CR and confer a wide range of beneficial effects towards health and survival, including anti-cancer properties. In this review, the known molecular, cellular, and organismal effects of energy restriction in oncology will be discussed. Energy-restriction-based strategies implemented in colorectal models and clinical trials will be also revised. While energy restriction constitutes a promising intervention for the prevention and treatment of several malignant neoplasms, further investigations are essential to dissect the interplay between fundamental aspects of energy intake, such as feeding patterns, fasting length, or diet composition, with all of them influencing health and disease or cancer effects. Currently, effectiveness, safety, and practicability of different forms of fasting to fight cancer, particularly colorectal cancer, should still be contemplated with caution.