Statin use, candidate mevalonate pathway biomarkers, and colon cancer survival in a population-based cohort study

Association of metformin and statin uses with the prognosis of colon cancer: a meta-analysis

BACKGROUND

Metformin and statins are commonly used globally for the treatment of type 2 diabetes mellitus and dyslipidemia, respectively. Recently, multiple novel pathways have been discovered, which may contribute to the treatment of various types of cancer. Several meta-analysis studies have reported that the use of metformin or statins is associated with a lower risk of colon cancer compared to nonusers. In this study, our aim was to perform a meta-analysis and investigate the prognostic roles of these two medications in colon cancer.

METHODS

To identify relevant articles, literature searches were performed in the PubMed and Web of Science databases using a combination of keywords related to metformin, statins and colon cancer prognosis until August 2023. The study utilized STATA 12.0 software (Stata Corporation, College Station, Texas, USA) to compute all the hazard ratios (HRs) and 95% confidence intervals (CIs) regarding the association between metformin or statin uses and prognostic-related outcomes.

RESULTS

Our analysis revealed that the use of metformin was associated with a significantly lower overall mortality of colon cancer (HR = 0.63; 95% CI = 0.51-0.77; I2  = 94.9%; P  < 0.001), as well as lower cancer-specific mortality of colon cancer (HR = 0.68; 95% CI = 0.50-0.94; I2  = 91.9%; P  < 0.001). Similarly, the use of statins was also associated with a lower overall mortality of colon cancer (HR = 0.68; 95% CI = 0.60-0.78; I2  = 93.8%; P  < 0.001), as well as a lower cancer-specific mortality of colon cancer (HR = 0.74; 95% CI = 0.67-0.81; I2  = 82.2%; P  < 0.001).

CONCLUSION

Our meta-analysis study suggests that statins and metformin may have potential as adjuvant agents with significant benefits in the prognosis of colon cancer.

Cholesterol-ferroptosis nexus: Unveiling novel cancer therapeutic avenues

Ferroptosis, a novel form of regulated cell death characterized by iron-mediated lipid peroxidation, holds immense potential in cancer therapeutics due to its role in tumor progression and resistance. This review predominantly explores the intricate relationship between ferroptosis and cholesterol metabolism pathways, mainly focusing on the cholesterol biosynthesis pathway. This review highlights the therapeutic implications of targeting cholesterol metabolism pathways for cancer treatment by delving into the mechanisms underlying ferroptosis regulation. Strategies such as inhibiting HMG-CoA reductase and suppressing squalene synthesis offer promising avenues for inducing ferroptosis in cancer cells. Moreover, insights into targeting the 7-dehydrocholesterol pathway provide novel perspectives on modulating ferroptosis susceptibility and managing ferroptosis-associated diseases. Understanding the interplay between ferroptosis and cholesterol metabolism pathways underscores the potential of lipid metabolism modulation as an innovative therapeutic approach in cancer treatment.

Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study

Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation. Our transformer-based approach substantially improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training and evaluating on a large multicenter cohort of over 13,000 patients from 16 colorectal cancer cohorts, we achieve a sensitivity of 0.99 with a negative predictive value of over 0.99 for prediction of microsatellite instability (MSI) on surgical resection specimens. We demonstrate that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem.

Drugs Targeting p53 Mutations with FDA Approval and in Clinical Trials

Mutations in the tumor suppressor p53 (p53) promote cancer progression. This is mainly due to loss of function (LOS) as a tumor suppressor, dominant-negative (DN) activities of missense mutant p53 (mutp53) over wild-type p53 (wtp53), and wtp53-independent oncogenic activities of missense mutp53 by interacting with other tumor suppressors or oncogenes (gain of function: GOF). Since p53 mutations occur in ~50% of human cancers and rarely occur in normal tissues, p53 mutations are cancer-specific and ideal therapeutic targets. Approaches to target p53 mutations include (1) restoration or stabilization of wtp53 conformation from missense mutp53, (2) rescue of p53 nonsense mutations, (3) depletion or degradation of mutp53 proteins, and (4) induction of p53 synthetic lethality or targeting of vulnerabilities imposed by p53 mutations (enhanced YAP/TAZ activities) or deletions (hyperactivated retrotransposons). This review article focuses on clinically available FDA-approved drugs and drugs in clinical trials that target p53 mutations and summarizes their mechanisms of action and activities to suppress cancer progression.

Strategies and techniques for quality control and semantic enrichment with multimodal data: a case study in colorectal cancer with eHDPrep

BACKGROUND

Integration of data from multiple domains can greatly enhance the quality and applicability of knowledge generated in analysis workflows. However, working with health data is challenging, requiring careful preparation in order to support meaningful interpretation and robust results. Ontologies encapsulate relationships between variables that can enrich the semantic content of health datasets to enhance interpretability and inform downstream analyses.

FINDINGS

We developed an R package for electronic health data preparation, "eHDPrep," demonstrated upon a multimodal colorectal cancer dataset (661 patients, 155 variables; Colo-661); a further demonstrator is taken from The Cancer Genome Atlas (459 patients, 94 variables; TCGA-COAD). eHDPrep offers user-friendly methods for quality control, including internal consistency checking and redundancy removal with information-theoretic variable merging. Semantic enrichment functionality is provided, enabling generation of new informative "meta-variables" according to ontological common ancestry between variables, demonstrated with SNOMED CT and the Gene Ontology in the current study. eHDPrep also facilitates numerical encoding, variable extraction from free text, completeness analysis, and user review of modifications to the dataset.

CONCLUSIONS

eHDPrep provides effective tools to assess and enhance data quality, laying the foundation for robust performance and interpretability in downstream analyses. Application to multimodal colorectal cancer datasets resulted in improved data quality, structuring, and robust encoding, as well as enhanced semantic information. We make eHDPrep available as an R package from CRAN (https://cran.r-project.org/package = eHDPrep) and GitHub (https://github.com/overton-group/eHDPrep).

Distinct Molecular Profiles of Sporadic Early-Onset Colorectal Cancer: A Population-Based Cohort and Systematic Review

Background and Aims

The observed increase in the incidence of early-onset colorectal cancer (EOCRC) is being driven by sporadic cases, but the molecular characteristics of these tumors are not fully understood. Our objective was to investigate the prevalence of microsatellite instability (MSI) and selected mutations in sporadic EOCRC, and their association with survival.

Methods

Firstly, we compared the prevalence of molecular characteristics and survival within a population-based cohort study of 652 stage II and III colon cancer patients in Northern Ireland, comparing sporadic early-onset (<50 years, n = 35) with older (60-69 years, n = 179) patients. Secondly, a systematic review for studies reporting the prevalence of MSI, mismatch repair deficiency (dMMR), or BRAF, KRAS, NRAS, PIK3CA, and TP53 mutations in sporadic EOCRC was conducted. A meta-analysis was performed to calculate pooled estimates of the prevalence of molecular features in sporadic EOCRC.

Results

Firstly, within the cohort study, EOCRC patients did not have a significantly increased risk of colorectal cancer-specific death (adjusted hazard ratio 1.20; 95% confidence interval [CI] 0.61-2.39) compared with 60- to 69-year-olds. Second, 32 studies were included in the systematic review. The pooled analysis estimated a prevalence of 10% (95% CI 7%-14%) for MSI high/dMMR in sporadic EOCRC. BRAF and KRAS mutations had a prevalence of 1% (95% CI 0%-3%) and 32% (95% CI 23%-40%), respectively.

Conclusion

The molecular characteristics of sporadic EOCRC differ from those of cancers in older adults, particularly regarding reduced prevalence of BRAF mutations. Ten percent of sporadic EOCRC display MSI high/dMMR. Further studies are needed to address survival in sporadic EOCRC cases and whether molecular profiles influence EOCRC outcomes in this patient group.

Establishment and validation of a cholesterol metabolism-related prognostic signature for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents the most important type of liver cancer, the 5-year survival rate for advanced HCC is 2%. The heterogeneity of HCC makes previous models fail to achieve satisfactory results. The role of Cholesterol-based metabolic reprogramming in cancer has attracted more and more attention. In this study, we screened cholesterol metabolism-related genes (CMRGs) based on a systematical analysis from TCGA and GEO database. Then, we constructed a prognostic signature based on the screened 5 CMRGs: FDPS, FABP5, ANXA2, ACADL and HMGCS2. The clinical value of the five CMRGs was validated by TCGA database and HPA database. HCC patients were assigned to the high-risk and low-risk groups on the basis of median risk score calculated by the five CMRGs. We evaluated the signature in TCGA database and validated in ICGC database. The results revealed that the prognostic signature had good prognostic performance, even among different clinicopathological subgroups. The function analysis linked CMRGs with KEGG pathway, such as cell adhesion molecules, drug metabolism-cytochrome P450 and other related pathways. In addition, patients in the high-risk group exhibited characteristics of high TP53 mutation, high immune checkpoints expression and high immune cell infiltration. Furthermore, based on the prognostic signature, we identified 25 most significant small molecule drugs as potential drugs for HCC patients. Finally, a nomogram combined risk score and TNM stage was constructed. These results indicated our prognostic signature has an excellent prediction performance. This study is expected to provide a potential diagnostic and therapeutic strategies for HCC.

Orthogonal MET analysis in a population-representative stage II-III colon cancer cohort: prognostic and potential therapeutic implications

Clinical trials for MET inhibitors have demonstrated limited success for their use in colon cancer (CC). However, clinical efficacy may be obscured by a lack of standardisation in MET assessment for patient stratification. In this study, we aimed to determine the molecular context in which MET is deregulated in CC using a series of genomic and proteomic tests to define MET expression and identify patient subgroups that should be considered in future studies with MET-targeted agents. To this aim, orthogonal expression analysis of MET was conducted in a population-representative cohort of stage II/III CC patients (n = 240) diagnosed in Northern Ireland from 2004 to 2008. Targeted sequencing was used to determine the relative incidence of MET R970C and MET T992I mutations within the cohort. MET amplification was assessed using dual-colour dual-hapten brightfield in situ hybridisation (DDISH). Expression of transcribed MET and c-MET protein within the cohort was assessed using digital image analysis on MET RNA in situ hybridisation (ISH) and c-MET immunohistochemistry (IHC) stained slides. We found that less than 2% of the stage II/III CC patient population assessed demonstrated a genetic MET aberration. Determination of a high MET RNA-ISH/low c-MET IHC protein subgroup was found to be associated with poor 5-year cancer-specific outcomes compared to patients with concordant MET RNA-ISH and c-MET IHC protein expression (HR 2.12 [95%CI: 1.27-3.68]). The MET RNA-ISH/c-MET IHC protein biomarker paradigm identified in this study demonstrates that subtyping of MET expression may be required to identify MET-addicted malignancies in CC patients who will truly benefit from MET inhibition.

Lipid metabolism in cancer progression and therapeutic strategies

Dysregulated lipid metabolism represents an important metabolic alteration in cancer. Fatty acids, cholesterol, and phospholipid are the three most prevalent lipids that act as energy producers, signaling molecules, and source material for the biogenesis of cell membranes. The enhanced synthesis, storage, and uptake of lipids contribute to cancer progression. The rewiring of lipid metabolism in cancer has been linked to the activation of oncogenic signaling pathways and cross talk with the tumor microenvironment. The resulting activity favors the survival and proliferation of tumor cells in the harsh conditions within the tumor. Lipid metabolism also plays a vital role in tumor immunogenicity via effects on the function of the noncancer cells within the tumor microenvironment, especially immune‐associated cells. Targeting altered lipid metabolism pathways has shown potential as a promising anticancer therapy. Here, we review recent evidence implicating the contribution of lipid metabolic reprogramming in cancer to cancer progression, and discuss the molecular mechanisms underlying lipid metabolism rewiring in cancer, and potential therapeutic strategies directed toward lipid metabolism in cancer. This review sheds new light to fully understanding of the role of lipid metabolic reprogramming in the context of cancer and provides valuable clues on therapeutic strategies targeting lipid metabolism in cancer.

The Potential Role of Changes in the Glucose and Lipid Metabolic Pathways in Gastrointestinal Cancer Progression: Strategy in Cancer Therapy

Background

Changes in cell metabolism are a well-known feature of some cancers, and this may be involved in the etiology of tumor formation and progression, as well as tumor heterogeneity. These changes may affect fatty acid metabolism and glycolysis and are required to provide the increase in energy necessary for the high rate of proliferation of cancer cells. Gastrointestinal cancers remain a difficult-to-treat cancer, particularly as they are usually diagnosed at a late stage of disease and are associated with poor outcomes.

Summary

Recently, the changes in the metabolic pathways, including the expression of the rate-limiting enzymes involved, have been considered to be a potential target for therapy for gastrointestinal tumors.

Key Message

A combination of routine chemotherapy drugs with metabolic inhibitors may improve the effectiveness of treatment.

Computer-Aided Design for Identifying Anticancer Targets in Genome-Scale Metabolic Models of Colon Cancer

Simple Summary

Discovery of anticancer targets with minimal side effects is a major challenge in drug discovery and development. This study developed a fuzzy optimization framework for identifying anticancer targets. The framework was applied to identify not only gene regulator targets but also metabolite- and reaction-centric targets. The computational results show that the combination of a carbon metabolism target and any one-target gene that participates in the sphingolipid, glycerophospholipid, nucleotide, cholesterol biosynthesis, or pentose phosphate pathways is more effective for treatment than one-target inhibition is, and a two-target combination of 5-FU and folate supplement can improve cell viability, reduce metabolic deviation, and reduce side effects of normal cells.

Abstract

The efficient discovery of anticancer targets with minimal side effects is a major challenge in drug discovery and development. Early prediction of side effects is key for reducing development costs, increasing drug efficacy, and increasing drug safety. This study developed a fuzzy optimization framework for Identifying AntiCancer Targets (IACT) using constraint-based models. Four objectives were established to evaluate the mortality of treated cancer cells and to minimize side effects causing toxicity-induced tumorigenesis on normal cells and smaller metabolic perturbations. Fuzzy set theory was applied to evaluate potential side effects and investigate the magnitude of metabolic deviations in perturbed cells compared with their normal counterparts. The framework was applied to identify not only gene regulator targets but also metabolite- and reaction-centric targets. A nested hybrid differential evolution algorithm with a hierarchical fitness function was applied to solve multilevel IACT problems. The results show that the combination of a carbon metabolism target and any one-target gene that participates in the sphingolipid, glycerophospholipid, nucleotide, cholesterol biosynthesis, or pentose phosphate pathways is more effective for treatment than one-target inhibition is. A clinical antimetabolite drug 5-fluorouracil (5-FU) has been used to inhibit synthesis of deoxythymidine-5′-triphosphate for treatment of colorectal cancer. The computational results reveal that a two-target combination of 5-FU and a folate supplement can improve cell viability, reduce metabolic deviation, and reduce side effects of normal cells.

Statins use and the prognosis of colorectal cancer: a meta-analysis

BACKGROUND

Previous observational studies regarding the prognostic value of statin on colorectal cancer (CRC) patients showed various results.

METHODS

Articles regarding the prognostic value of statin on CRC and published in English and before October 2020 were searched in the following databases: PubMed, Web of Science, EMBASE, Medline and Google Scholar. The multivariate hazard ratios (HRs) and their 95% confidence intervals (CI) were computed to explore associations between statins use and overall mortality or cancer-specific mortality of CRC.

RESULTS

The study included 5 retrospective case-control studies (including 475 statins users and 1925 no-statin users) and 11 prospective cohort studies (including 40659 statins users and 344459 no-statin users). The present study showed that statins use might be significantly associated with lower overall mortality in CRC with a random effects model (HR = 0.81, 95% CI 0.76 to 0.86, I² = 61.9%, p value for Q test <0.001). In addition, statins use might be significantly associated with lower cancer-specific mortality in CRC with a random effects model (HR = 0.78, 95% CI 0.72 to 0.85, I² = 57.3%, p value for Q test = 0.007).

CONCLUSIONS

In conclusion, the present study indicated that that statin use was a protective factor for CRC prognosis. However, the relationship between statins use and CRC prognosis requires repeated and large prospective studies to be verified.

A Means of Assessing Deep Learning-Based Detection of ICOS Protein Expression in Colon Cancer

Biomarkers identify patient response to therapy. The potential immune-checkpoint biomarker, Inducible T-cell COStimulator (ICOS), expressed on regulating T-cell activation and involved in adaptive immune responses, is of great interest. We have previously shown that open-source software for digital pathology image analysis can be used to detect and quantify ICOS using cell detection algorithms based on traditional image processing techniques. Currently, artificial intelligence (AI) based on deep learning methods is significantly impacting the domain of digital pathology, including the quantification of biomarkers. In this study, we propose a general AI-based workflow for applying deep learning to the problem of cell segmentation/detection in IHC slides as a basis for quantifying nuclear staining biomarkers, such as ICOS. It consists of two main parts: a simplified but robust annotation process, and cell segmentation/detection models. This results in an optimised annotation process with a new user-friendly tool that can interact with1 other open-source software and assists pathologists and scientists in creating and exporting data for deep learning. We present a set of architectures for cell-based segmentation/detection to quantify and analyse the trade-offs between them, proving to be more accurate and less time consuming than traditional methods. This approach can identify the best tool to deliver the prognostic significance of ICOS protein expression.

Simvastatin treatment varies the radiation response of human breast cells in 2D or 3D culture

Background Statins inhibit the cholesterol biosynthesis and are used as cholesterol-lowering agents in fat-metabolism disorders. Furthermore, several studies state that statins have supportive functions in breast cancer treatment. Therefore, simvastatin (SVA) as a potential radiosensitizer should be investigated on the basis of human breast cells. Methods First, an optimal concentration of SVA for normal (MCF10A) and cancer (MCF-7) cells was identified via growth and cytotoxicity assays that, according to the definition of a radiosensitizer in the narrower sense, enhances the effect of radiation therapy but has no cytotoxic effect. Next, in combination with radiation SVA's influence on DNA repair capacity and clonogenic survival in 2D and 3D was determined. Furthermore cell cycle distribution, expression of survivin and connective tissue growth factor (CTGF) as well as ERK1 map kinase were analysed. Results 1 μM SVA was identified as highest concentration without an influence on cell growth and cytotoxicity and was used for further analyses. In terms of early and residual γH2AX-foci, SVA affected the number of foci in both cell lines with or without irradiation. Different radiation responses were detected in 2D and 3D culture conditions. During the 2D cultivation, a radiosensitizing effect within the clonogenic survival was observable, but not in 3D. Conclusion The present study suggests that SVA may have potential for radiosensitization. Therefore, it is important to further investigate the role of SVA in relation to the extent of radiosensitization and how it could be used to positively influence the therapy of breast cancer or other entities.

Effect of Metabolic Syndrome and Individual Components on Colon Cancer Characteristics and Prognosis

Metabolic syndrome (MS) is recognized as a risk factor for colon cancer (CC). However, whether the cluster of metabolic changes that define MS also influence CC prognosis remains unclear. Thus, our aim was to investigate whether the presence of MS or any of the MS individual components could provide prognostic information on tumor phenotype and survival outcomes. Clinical and pathological data from patients with CC (n = 300) who underwent surgical resection at a single tertiary hospital were retrospectively collected to evaluate presence of MS components and diagnostic criteria, CC phenotype and disease outcomes. Patients were allocated into two groups according to the presence or absence of MS (n = 85 MS vs n = 83 non-MS). The overall prevalence of MS individual components was 82.7% for increased waist-circumference (WC), 61.3% for high blood pressure (BP), 48.8% for low HDL-cholesterol, 39.9% for high fasting glucose, and 33.9% for hypertriglyceridemia. Patients in the MS group presented smaller tumors (p = 0.006) with lower T-stage (p = 0.002). High BP (p = 0.029) and hypertriglyceridemia (p = 0.044) were associated with a smaller tumor size, while low-HDL (p = 0.008) was associated with lower T-stage. After propensity score matching using age, tumor size and staging as covariates high-BP (p = 0.020) and WC (p = 0.003) were found to influence disease-free survival, but not overall survival. In conclusion, despite MS being an established risk factor for CC, our data does not support the hypothesis that MS components have a negative impact on disease extension or prognosis. Nevertheless, a protective role of BP and lipid lowering drugs cannot be excluded.

Identifying mismatch repair-deficient colon cancer: near-perfect concordance between immunohistochemistry and microsatellite instability testing in a large, population-based series

AIMS

Establishing the mismatch repair (MMR) status of colorectal cancers is important to enable the detection of underlying Lynch syndrome and inform prognosis and therapy. Current testing typically involves either polymerase chain reaction (PCR)-based microsatellite instability (MSI) testing or MMR protein immunohistochemistry (IHC). The aim of this study was to compare these two approaches in a large, population-based cohort of stage 2 and 3 colon cancer cases in Northern Ireland.

METHODS AND RESULTS

The study used the Promega pentaplex assay to determine MSI status and a four-antibody MMR IHC panel. IHC was applied to tumour tissue microarrays with triplicate tumour sampling, and assessed manually. Of 593 cases with available MSI and MMR IHC results, 136 (22.9%) were MSI-high (MSI-H) and 135 (22.8%) showed abnormal MMR IHC. Concordance was extremely high, with 97.1% of MSI-H cases showing abnormal MMR IHC, and 97.8% of cases with abnormal IHC showing MSI-H status. Under-representation of tumour epithelial cells in samples from heavily inflamed tumours resulted in misclassification of several cases with abnormal MMR IHC as microsatellite-stable. MMR IHC revealed rare cases with unusual patterns of MMR protein expression, unusual combinations of expression loss, or secondary clonal loss of expression, as further illustrated by repeat immunostaining on whole tissue sections.

CONCLUSIONS

MSI PCR testing and MMR IHC can be considered to be equally proficient tests for establishing MMR/MSI status, when there is awareness of the potential pitfalls of either method. The choice of methodology may depend on available services and expertise.

Research Strategies for Low-Survival Cancers

While substantial progress has been made to improve the diagnosis, prognosis, and survivorship of patients with cancer, certain cancer types, along with metastatic and refractory disease, remain clinical challenges. To improve patient outcomes, ultimately, the cancer research community must meet and overcome these challenges, leading to improved approaches to treat the most difficult cancers. Here, we discuss research progress aimed at gaining a better understanding of the molecular and cellular changes in tumor cells and the surrounding stroma, presented at the 56th Irish Association for Cancer Research (IACR) Annual Conference. With a focus on poor prognosis cancers, such as esophageal and chemo-resistant colorectal cancers, we highlight how detailed molecular knowledge of tumor and stromal biology can provide windows of opportunity for biomarker discovery and therapeutic targets. Even with previously characterized targets, such as phosphoinositide 3-kinase (PI3K), one of the most altered proteins in all human cancers, new insights into how this protein may be more effectively inhibited through novel combination therapies is presented.

QuPath: The global impact of an open source digital pathology system

QuPath, originally created at the Centre for Cancer Research & Cell Biology at Queen's University Belfast as part of a research programme in digital pathology (DP) funded by Invest Northern Ireland and Cancer Research UK, is arguably the most wildly used image analysis software program in the world. On the back of the explosion of DP and a need to comprehensively visualise and analyse whole slides images (WSI), QuPath was developed to address the many needs associated with tissue based image analysis; these were several fold and, predominantly, translational in nature: from the requirement to visualise images containing billions of pixels from files several GBs in size, to the demand for high-throughput reproducible analysis, which the paradigm of routine visual pathological assessment continues to struggle to deliver. Resultantly, large-scale biomarker quantification must increasingly be augmented with DP. Here we highlight the impact of the open source Quantitative Pathology & Bioimage Analysis DP system since its inception, by discussing the scope of scientific research in which QuPath has been cited, as the system of choice for researchers.

Targeting the Mevalonate Pathway in Cancer

The mevalonate synthesis inhibitors, statins, are mainstay therapeutics for cholesterol management and cardiovascular health. Thirty years of research have uncovered supportive roles for the mevalonate pathway in numerous cellular processes that support oncogenesis, most recently macropinocytosis. Central to the diverse mechanisms of statin sensitivity is an acquired dependence on one mevalonate pathway output, protein geranylgeranylation. New chemical prenylation probes and the discovery of a novel geranylgeranyl transferase hold promise to deepen our understanding of statin mechanisms of action. Further, insights into statin selection and the counterproductive role of dietary geranylgeraniol highlight how we should assess statins in the clinic. Lastly, rational combination strategies preview how statins will enter the oncology toolbox.

Lipid-Producing Ciliochoroidal Melanoma with Expression of HMG-CoA Reductase

Uveal melanoma (UM) is the commonest primary intraocular malignancy in adults. There is limited published data on lipid production in UM. Here, we describe the clinical, histological, immunohistochemical, and molecular findings in a ciliochoroidal melanoma with lipid production and expression of the enzyme HMG-CoA reductase. This case highlights an unusual UM tumour phenotype with a high-risk molecular metastatic profile and discusses tumour lipogenesis and activation of the mevalonate pathway as a potential therapeutic target in managing lipidised ciliochoroidal UM.

Targeting SREBP-2-Regulated Mevalonate Metabolism for Cancer Therapy

Recently, targeting metabolic reprogramming has emerged as a potential therapeutic approach for fighting cancer. Sterol regulatory element binding protein-2 (SREBP-2), a basic helix-loop-helix leucine zipper transcription factor, mainly regulates genes involved in cholesterol biosynthesis and homeostasis. SREBP-2 binds to the sterol regulatory elements (SREs) in the promoters of its target genes and activates the transcription of mevalonate pathway genes, such as HMG-CoA reductase (HMGCR), mevalonate kinase and other key enzymes. In this review, we first summarized the structure of SREBP-2 and its activation and regulation by multiple signaling pathways. We then found that SREBP-2 and its regulated enzymes, including HMGCR, FPPS, SQS, and DHCR4 from the mevalonate pathway, participate in the progression of various cancers, including prostate, breast, lung, and hepatocellular cancer, as potential targets. Importantly, preclinical and clinical research demonstrated that fatostatin, statins, and N-BPs targeting SREBP-2, HMGCR, and FPPS, respectively, alone or in combination with other drugs, have been used for the treatment of different cancers. This review summarizes new insights into the critical role of the SREBP-2-regulated mevalonate pathway for cancer and its potential for targeted cancer therapy.

Role of microRNA-33a in malignant cells

Cancer causes most of the mortality and morbidity worldwide, with a significant increase in incidence during recent years. MicroRNAs (miRNAs/miRs) are non-coding small RNAs capable of regulating gene expression. They regulate crucial cellular processes, including proliferation, differentiation, metastasis and apoptosis. Therefore, abnormal miRNA expression is associated with multiple diseases, including cancer. There are two types of cancer-associated miRNAs, oncogenic and tumor suppressor miRNAs, depending on their roles and expression patterns in cancer. Accordingly, miRNAs are considered to be targets for cancer prevention and treatment. miR-33a controls cellular cholesterol uptake and synthesis, which are both closely associated with carcinogenesis. The present review thoroughly describes the roles of miR-33a in more than a dozen types of cancer and the underlying mechanisms. Accordingly, the present review may serve as a guide for researchers studying the involvement of miR-33a in diverse cancer settings.

KRAS Status is Associated with Metabolic Parameters in Metastatic Colorectal Cancer According to Primary Tumour Location

Colorectal cancer (CRC) is characterized by complex interplay between macroenvironmental factors and tumour microenvironment, leading to variable outcomes in CRC patients. To date, there is still a need to identify macroenvironment/microenvironment factors that could define subgroup of patients that would benefit from specific anti-cancer treatment in order to improve patient selection for individualized targeted-based therapy. Aim of this study was to evaluate associations between metabolic parameters and KRAS status in metastatic CRC (mCRC) according to a new tumour site classification. Retrospective data were extracted from a total of 201 patients diagnosed with mCRC between 2012 and 2017 extracted from an established CRC database at our tertiary institute. Clinical-pathological data, including age, gender, BMI, hypertension, diabetes, pre-CRC diagnosis serum lipid levels and KRAS status were recorded. Categorical characteristics were compared using chi-squared test. Continuous characteristics were compared using Mann-Whitney U test. Log rank test was used to compare hazards for survival. In all comparisons, a two-sided P value <0.05 was considered statistically significant. Out of 201 patients, 170 patients with complete serum lipid profile were included in the analysis. In recto-sigmoid cancers there was a statistically significant association between high cholesterol:high-density lipoprotein (chol:HDL) ratio and KRAS mutation (OR 2.69, 95% CI 1.1–6.4, p = 0,02). In non recto-sigmoid cancers, high cholesterol was associated with KRAS WT (OR 0.39, CI 0.15–0.97, p = 0.04). In 22 patients with KRAS mutated recto-sigmoid cancer stage IV at diagnosis normal chol:HDL ratio was associated with a trend to better survival (p = 0.06). High chol:HDL ratio was significantly associated with KRAS mutated metastatic recto-sigmoid cancers. A subgroup of mCRC patients with KRAS mutated recto-sigmoid cancer may benefit from optimal lipid lowering treatment.

Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy

Conventional immunohistochemistry (IHC) is a widely used diagnostic technique in tissue pathology. However, this technique is associated with a number of limitations, including high inter-observer variability and the capacity to label only one marker per tissue section. This review details various highly multiplexed techniques that have emerged to circumvent these constraints, allowing simultaneous detection of multiple markers on a single tissue section and the comprehensive study of cell composition, cellular functional and cell-cell interactions. Among these techniques, multiplex Immunohistochemistry/Immunofluorescence (mIHC/IF) has emerged to be particularly promising. mIHC/IF provides high-throughput multiplex staining and standardized quantitative analysis for highly reproducible, efficient and cost-effective tissue studies. This technique has immediate potential for translational research and clinical practice, particularly in the era of cancer immunotherapy.

Cholesterol and beyond - The role of the mevalonate pathway in cancer biology

Cancer is a multifaceted global disease. Transformation of a normal to a malignant cell takes several steps, including somatic mutations, epigenetic alterations, metabolic reprogramming and loss of cell growth control. Recently, the mevalonate pathway has emerged as a crucial regulator of tumor biology and a potential therapeutic target. This pathway controls cholesterol production and posttranslational modifications of Rho-GTPases, both of which are linked to several key steps of tumor progression. Inhibitors of the mevalonate pathway induce pleiotropic antitumor-effects in several human malignancies, identifying the pathway as an attractive candidate for novel therapies. In this review, we will provide an overview about the role and regulation of the mevalonate pathway in certain aspects of cancer initiation and progression and its potential for therapeutic intervention in oncology.

Greasing the Wheels of the Cancer Machine: The Role of Lipid Metabolism in Cancer

Altered lipid metabolism is among the most prominent metabolic alterations in cancer. Enhanced synthesis or uptake of lipids contributes to rapid cancer cell growth and tumor formation. Lipids are a highly complex group of biomolecules that not only constitute the structural basis of biological membranes but also function as signaling molecules and an energy source. Here, we summarize recent evidence implicating altered lipid metabolism in different aspects of the cancer phenotype and discuss potential strategies by which targeting lipid metabolism could provide a therapeutic window for cancer treatment.

Statin uses and mortality in colorectal cancer patients: An updated systematic review and meta-analysis

BACKGROUND

Colorectal cancer (CRC) remains one of the most common types of cancer and a leading cause of death worldwide. Previous studies indicated that statins may have a potential protective effect on CRC.

METHODS

We conducted this meta-analysis to systematically assess the overall and cancer-specific survival benefit of statin uses on CRC patients. Related references were identified through PubMed, the Cochrane Library, Web of Science, EMBASE, and SCOPUS from inception to August 2017. Adjusted hazard ratios (HRs) were adopted to calculate summary hazard ratios (HRs) with 95% confidence intervals (95% CIs), using a random-effects model.

RESULTS

Total fourteen studies involving 130 994 patients were included in this meta-analysis. Six studies reported the association between pre-diagnosis statin uses and CRC mortality, while 11 studies investigated mortality in patients using statins after CRC diagnosis. For pre-diagnosis statin uses, the pooled HR of all-cause mortality (ACM) was 0.85 (95% CI, 0.79-0.92) and the pooled HR of cancer-specific mortality (CSM) was 0.82 (95% CI, 0.79-0.86). In terms of post-diagnosis statin uses, the pooled HR of ACM was 0.86 (95% CI, 0.76-0.98), and the pooled HR of CSM was 0.79 (95% CI, 0.70-0.89). For post-diagnosis statin uses, there is no difference in ACM when stratified by KRAS gene (KRAS) mutation status. Results of ACM and CSM did not markedly alter in other subgroup analyses.

CONCLUSION

Our meta-analysis demonstrates that both pre-diagnosis and post-diagnosis statin uses are associated with reduced ACM and CSM for CRC patients.

Impact of Metabolic Syndrome Diagnosis and Its Treatment on Survival of Colorectal Cancer Patients

Background

Epidemiologic findings on the effect of metabolic syndrome (MetS) and its treatment on colorectal cancer (CRC) survival have been inconsistent and have not been previously studied in an Arab population such as the Omani population.

Patients and Methods

Data from the hospital records of 301 CRC patients treated in Sultan Qaboos University (SQUH), Oman, from 2006 to 2014 were analyzed retrospectively to determine the effects of MetS and its treatment on CRC survival. Overall survival (OS) by MetS status and by medications for MetS components management was compared with Cox proportional models.

Results

Of the 301 patients, 76 (25.2%) had MetS, 20.3% were on insulin, 23.9% were on metformin, 25.6% took statins, 17.9% were on either angiotensin converting enzyme inhibitors (ACEI) or angiotensin receptor blocker (ARB). Whereas metformin (HR, 0.46, 95% CI, 0.25-0.84) and statins (HR, 0.58; 95% CI, 0.35-0.96) had a protective effect on OS, insulin (HR 1.73, 95% CI, 1.02-2.97) had a detrimental effect. In subgroup analysis of diabetic subjects, a nonsignificant improvement in OS was observed in the metformin treated patients compared to those on other hypoglycemic agents (HR, 0.92, 95% CI, 0.55-1.55). Neither MetS nor antihypertensive drugs had any apparent effect on OS.

Conclusions

Our result suggests that, among CRC patients with MetS, taking metformin and statins may improve overall survival, whereas being on insulin may negatively impact CRC prognosis. Further studies are warranted to determine the exact mechanism through which metformin, statins, and insulin exert their effects on CRC survival.

Cardiovascular medication use and risks of colon cancer recurrences and additional cancer events: a cohort study

Background

Cardiovascular medications may be associated with cancer development, but little is known about their association with cancer recurrence. Medications such as statins and antihypertensives may be commonly used among colon cancer survivors, who are, on average, diagnosed in their mid-60s. We described the associations between statins and antihypertensive medications and colon cancer recurrence in a large, population-based study.

Methods

We conducted a cohort study among adults with stage I-IIIA colon cancer diagnosed in 1995–2014 in two Kaiser Permanente regions, Colorado and Washington. Statin and antihypertensive use were obtained from electronic pharmacy dispensing data. People were classified as medication users on the date of their first dispensing after cohort entry, which started 90 days after completing cancer treatment, continuing through the earliest of death, health plan disenrollment, or chart abstraction. We collected outcome information from medical record abstraction and tumor registries on colon cancer recurrences and second primary cancers. Using Cox proportional hazards multivariable models, we estimated hazard ratios (HRs) with 95% confidence intervals (CIs) for colon cancer recurrences and any cancer event (recurrences and new primaries at any anatomic site) comparing medication users to non-users.

Results

Among 2039 people, 937 (46%) used statins and 1425 (70%) used antihypertensives at any point during a median of 4.9 years of follow-up; 460 people had any additional cancer event, including 152 with a colon cancer recurrence. Statin use was not associated with colon cancer recurrence (HR = 1.09, 95%CI = 0.65–1.85) or any cancer event (HR = 1.12, 95%CI = 0.85–1.47), nor was antihypertensive use associated with recurrence (HR = 0.73, 95%CI = 0.44–1.21) or any cancer event (HR = 0.93, 95%CI = 0.70–1.24).

Conclusions

Our results suggest no association between cardiovascular medication use and the risk of recurrence or any additional cancer, and may provide reassurance to colon cancer survivors.

Cholesterol regulates cell proliferation and apoptosis of colorectal cancer by modulating miR-33a-PIM3 pathway

The relationship between colorectal cancer (CRC) and cholesterol has been confirmed for many years, but the mechanism was not very clear. miR-33a was important in cholesterol metabolism and was abnormally expressed in many tumors, thus our study hypothesized that cholesterol effect on CRC by regulating miR-33a and its target gene PIM3, and verify it by series of assay. From results of CCK8 and flow cytometry, we confirmed cholesterol can stimulate CRC cell proliferation, promote cell cycle progression and inhibit cell apoptosis. miR-33a and SREBP2 mRNA expression were inhibited by cholesterol, and when cells transfected with miR-33a mimics or inhibitor the effect of cholesterol appeared a significant difference than before. In addition, PIM3 showed up-regulation with cholesterol treatment, and it was proved to be the target gene of miR-33a by dual luciferase reporter assay, it modulated CRC cells proliferation and apoptosis by phosphorylating p27, p21 and Bad protein. Thus, it inferred that cholesterol can regulate CRC development by miR-33a-PIM3 pathway.

Validation of the systematic scoring of immunohistochemically stained tumour tissue microarrays using QuPath digital image analysis

AIMS

Output from biomarker studies involving immunohistochemistry applied to tissue microarrays (TMA) is limited by the lack of an efficient and reproducible scoring methodology. In this study, we examine the functionality and reproducibility of biomarker scoring using the new, open-source, digital image analysis software, QuPath.

METHODS AND RESULTS

Three different reviewers, with varying experience of digital pathology and image analysis, applied an agreed QuPath scoring methodology to CD3 and p53 immunohistochemically stained TMAs from a colon cancer cohort (n = 661). Manual assessment was conducted by one reviewer for CD3. Survival analyses were conducted and intra- and interobserver reproducibility assessed. Median raw scores differed significantly between reviewers, but this had little impact on subsequent analyses. Lower CD3 scores were detected in cases who died from colorectal cancer compared to control cases, and this finding was significant for all three reviewers (P-value range = 0.002-0.02). Higher median p53 scores were generated among cases who died from colorectal cancer compared with controls (P-value range = 0.04-0.12). The ability to dichomotise cases into high versus low expression of CD3 and p53 showed excellent agreement between all three reviewers (kappa score range = 0.82-0.93). All three reviewers produced dichotomised expression scores that resulted in very similar hazard ratios for colorectal cancer-specific survival for each biomarker. Results from manual and QuPath methods of CD3 scoring were comparable, but QuPath scoring revealed stronger prognostic stratification.

CONCLUSIONS

Scoring of immunohistochemically stained tumour TMAs using QuPath is functional and reproducible, even among users of limited experience of digital pathology images, and more accurate than manual scoring.

Synergistic inhibition of colon cancer cell growth by a combination of atorvastatin and phloretin

Atorvastatin (ATST), a drug commonly used to reduce the levels of cholesterol and low-density lipoproteins, is a prospective agent for the prevention of colorectal cancer in patients with hyperlipidemia. ATST in combination with functional components is a promising strategy for cancer chemoprevention. In the present study, the growth inhibitory effect of ATST combined with phloretin (PT) on SW620 and HCT116 colon cancer cells was investigated. The results of MTT assays indicated that the combination of PT and ATST markedly reduced cell survival in both cell lines compared with PT or ATST treatment administered individually. The interaction indexes between PT and ATST, which were used to analyze their interaction pattern, were computed by the median-effect equation. The interaction indexes of each PT and ATST concentration pair were <1.0, which indicated a strong synergistic effect between the two compounds. The data obtained by flow cytometry and western blot analysis of cleaved-poly (ADP-ribose) polymerase indicated a synergistic effect resulted in apoptosis and cell cycle arrest at the G₂/M checkpoint. Furthermore, combined treatment with PT and ATST markedly downregulated the expression of cyclin B and upregulated the expression of phospho-cdc2 and Myt1, which suggested that the activation of cdc2 was downregulated. This combined treatment strategy enhanced the anti-cancer activity of ATST at a relatively low dosage and suggested a possible method of preventing colorectal cancer in patients with hyperlipidemia.

Utility of inverse probability weighting in molecular pathological epidemiology

As one of causal inference methodologies, the inverse probability weighting (IPW) method has been utilized to address confounding and account for missing data when subjects with missing data cannot be included in a primary analysis. The transdisciplinary field of molecular pathological epidemiology (MPE) integrates molecular pathological and epidemiological methods, and takes advantages of improved understanding of pathogenesis to generate stronger biological evidence of causality and optimize strategies for precision medicine and prevention. Disease subtyping based on biomarker analysis of biospecimens is essential in MPE research. However, there are nearly always cases that lack subtype information due to the unavailability or insufficiency of biospecimens. To address this missing subtype data issue, we incorporated inverse probability weights into Cox proportional cause-specific hazards regression. The weight was inverse of the probability of biomarker data availability estimated based on a model for biomarker data availability status. The strategy was illustrated in two example studies; each assessed alcohol intake or family history of colorectal cancer in relation to the risk of developing colorectal carcinoma subtypes classified by tumor microsatellite instability (MSI) status, using a prospective cohort study, the Nurses' Health Study. Logistic regression was used to estimate the probability of MSI data availability for each cancer case with covariates of clinical features and family history of colorectal cancer. This application of IPW can reduce selection bias caused by nonrandom variation in biospecimen data availability. The integration of causal inference methods into the MPE approach will likely have substantial potentials to advance the field of epidemiology.