Expression of Genes Related to Lipid Handling and the Obesity Paradox in Melanoma: Database Analysis

The emerging role of fatty acid binding protein 7 (FABP7) in cancers

Fatty acid binding protein 7 (FABP7) is an intracellular protein involved in the uptake, transportation, metabolism, and storage of fatty acids (FAs). FABP7 is upregulated up to 20-fold in multiple cancers, usually correlated with poor prognosis. FABP7 silencing or pharmacological inhibition suggest FABP7 promotes cell growth, migration, invasion, colony and spheroid formation/increased size, lipid uptake, and lipid droplet formation. Xenograft studies show that suppression of FABP7 inhibits tumour formation and tumour growth, and improves host survival. The molecular mechanisms involve promotion of FA uptake, lipid droplets, signalling [focal adhesion kinase (FAK), proto-oncogene tyrosine-protein kinase Src (Src), mitogen-activated protein kinase kinase/p-extracellular signal-regulated kinase (MEK/ERK), and Wnt/β-catenin], hypoxia-inducible factor 1-alpha (Hif1α), vascular endothelial growth factor A/prolyl 4-hydroxylase subunit alpha-1 (VEGFA/P4HA1), snail family zinc finger 1 (Snail1), and twist-related protein 1 (Twist1). The oncogenic capacity of FABP7 makes it a promising pharmacological target for future cancer treatments.

Analysis of gene expression levels and their impact on survival in 31 cancer-types patients identifies novel prognostic markers and suggests unexplored immunotherapy treatment options in a wide range of malignancies

BACKGROUND

Immunotherapy has dramatically improved cancer treatment by inhibiting or activating specific cell receptors, thus unleashing the host anti-tumor response. However, the engagement of the three main immune checkpoints so far identified, CTLA4, PD-1 and PD-L1, is effective in a fraction of patients, therefore novel targets must be identified and tested.

METHODS

We focused our attention on the following nine highly relevant immune checkpoint (ICR) receptors: CTLA4, PD1, PD-L1, LAG3, TIM3, OX40, GITR, 4-1BB and TIGIT. All of them are targets of existing drugs currently under clinical scrutiny in several malignancies. Their expression levels were evaluated in patient tissues of 31 different cancer types vs. proper controls, in a total of 15,038 individuals. This analysis was carried out by interrogating public databases available on GEPIA2 portal and UALCAN portal. By the Principal Component Analysis (PCA) their ability to effectively discriminate patients form controls was then investigated. Expression of the nine ICRs was also related to overall survival in 31 cancer types and expressed as Hazard Ratio, on the GEPIA2 portal and validated, for melanoma patients, in patients-datasets available on PROGgene V2 portal.

RESULTS

Significant differential expression was observed for each ICR molecule in many cancer types. A 7-molecules profile was found to specifically discriminate melanoma patients from controls, while two different 6-molecules profiles discriminate pancreatic cancer patients and Testicular Germ Cell Tumors from matched controls. Highly significant survival improvement was found to be related to the expression levels of all nine ICRs in a wide spectrum of malignancies. For melanoma analysis, the relation with survival observed in TCGA datasets was validated in independent GSE melanoma datasets.

CONCLUSION

Analysis the nine ICR molecules demonstrates that their expression patterns may be considered as markers of disease and strong survival predictors in a variety of malignancies frequently associated to poor prognosis. Thus, the present findings are strongly advocating that exploratory clinical trials are worth to be performed, using available drugs, targeting these molecules.

FABP4 in obesity-associated carcinogenesis: Novel insights into mechanisms and therapeutic implications

The increasing prevalence of obesity worldwide is associated with an increased risk of various diseases, including multiple metabolic diseases, cardiovascular diseases, and malignant tumors. Fatty acid binding proteins (FABPs) are members of the adipokine family of multifunctional proteins that are related to fatty acid metabolism and are divided into 12 types according to their tissue origin. FABP4 is mainly secreted by adipocytes and macrophages. Under obesity, the synthesis of FABP4 increases, and the FABP4 content is higher not only in tissues but also in the blood, which promotes the occurrence and development of various cancers. Here, we comprehensively investigated obesity epidemiology and the biological mechanisms associated with the functions of FABP4 that may explain this effect. In this review, we explore the molecular mechanisms by which FABP4 promotes carcinoma development and the interaction between fat and cancer cells in obese circumstances here. This review leads us to understand how FABP4 signaling is involved in obesity-associated tumors, which could increase the potential for advancing novel therapeutic strategies and molecular targets for the systematic treatment of malignant tumors.

Body size and composition and risk of site-specific cancers in the UK Biobank and large international consortia: A mendelian randomisation study

BACKGROUND

Evidence for the impact of body size and composition on cancer risk is limited. This mendelian randomisation (MR) study investigates evidence supporting causal relationships of body mass index (BMI), fat mass index (FMI), fat-free mass index (FFMI), and height with cancer risk.

METHODS AND FINDINGS

Single nucleotide polymorphisms (SNPs) were used as instrumental variables for BMI (312 SNPs), FMI (577 SNPs), FFMI (577 SNPs), and height (293 SNPs). Associations of the genetic variants with 22 site-specific cancers and overall cancer were estimated in 367,561 individuals from the UK Biobank (UKBB) and with lung, breast, ovarian, uterine, and prostate cancer in large international consortia. In the UKBB, genetically predicted BMI was positively associated with overall cancer (odds ratio [OR] per 1 kg/m2 increase 1.01, 95% confidence interval [CI] 1.00-1.02; p = 0.043); several digestive system cancers: stomach (OR 1.13, 95% CI 1.06-1.21; p < 0.001), esophagus (OR 1.10, 95% CI 1.03, 1.17; p = 0.003), liver (OR 1.13, 95% CI 1.03-1.25; p = 0.012), and pancreas (OR 1.06, 95% CI 1.01-1.12; p = 0.016); and lung cancer (OR 1.08, 95% CI 1.04-1.12; p < 0.001). For sex-specific cancers, genetically predicted elevated BMI was associated with an increased risk of uterine cancer (OR 1.10, 95% CI 1.05-1.15; p < 0.001) and with a lower risk of prostate cancer (OR 0.97, 95% CI 0.94-0.99; p = 0.009). When dividing cancers into digestive system versus non-digestive system, genetically predicted BMI was positively associated with digestive system cancers (OR 1.04, 95% CI 1.02-1.06; p < 0.001) but not with non-digestive system cancers (OR 1.01, 95% CI 0.99-1.02; p = 0.369). Genetically predicted FMI was positively associated with liver, pancreatic, and lung cancer and inversely associated with melanoma and prostate cancer. Genetically predicted FFMI was positively associated with non-Hodgkin lymphoma and melanoma. Genetically predicted height was associated with increased risk of overall cancer (OR per 1 standard deviation increase 1.09; 95% CI 1.05-1.12; p < 0.001) and multiple site-specific cancers. Similar results were observed in analyses using the weighted median and MR-Egger methods. Results based on consortium data confirmed the positive associations between BMI and lung and uterine cancer risk as well as the inverse association between BMI and prostate cancer, and, additionally, showed an inverse association between genetically predicted BMI and breast cancer. The main limitations are the assumption that genetic associations with cancer outcomes are mediated via the proposed risk factors and that estimates for some lower frequency cancer types are subject to low precision.

CONCLUSIONS

Our results show that the evidence for BMI as a causal risk factor for cancer is mixed. We find that BMI has a consistent causal role in increasing risk of digestive system cancers and a role for sex-specific cancers with inconsistent directions of effect. In contrast, increased height appears to have a consistent risk-increasing effect on overall and site-specific cancers.

Anti-tumor Effect of Oleic Acid in Hepatocellular Carcinoma Cell Lines via Autophagy Reduction

Oleic acid (OA) is a component of the olive oil. Beneficial health effects of olive oil are well-known, such as protection against liver steatosis and against some cancer types. In the present study, we focused on OA effects in hepatocellular carcinoma (HCC), investigating responses to OA treatment (50–300 μM) in HCC cell lines (Hep3B and Huh7.5) and in a healthy liver-derived human cell line (THLE-2). Upon OA administration higher lipid accumulation, perilipin-2 increase, and autophagy reduction were observed in HCC cells as compared to healthy cells. OA in the presence of 10% FBS significantly reduced viability of HCC cell lines at 300 μM through Alamar Blue staining evaluation, and reduced cyclin D1 expression in a dose-dependent manner while it was ineffective on healthy hepatocytes. Furthermore, OA increased cell death by about 30%, inducing apoptosis and necrosis in HCC cells but not in healthy hepatocytes at 300 μM dosage. Moreover, OA induced senescence in Hep3B, reduced P-ERK in both HCC cell lines and significantly inhibited the antiapoptotic proteins c-Flip and Bcl-2 in HCC cells but not in healthy hepatocytes. All these results led us to conclude that different cell death processes occur in these two HCC cell lines upon OA treatment. Furthermore, 300 μM OA significantly reduced the migration and invasion of both HCC cell lines, while it has no effects on healthy cells. Finally, we investigated autophagy role in OA-dependent effects by using the autophagy inducer torin-1. Combined OA/torin-1 treatment reduced lipid accumulation and cell death as compared to single OA treatment. We therefore concluded that OA effects in HCC cells lines are, at least, in part dependent on OA-induced autophagy reduction. In conclusion, we report for the first time an autophagy dependent relevant anti-cancer effect of OA in human hepatocellular carcinoma cell lines.

Investigating Serum and Tissue Expression Identified a Cytokine/Chemokine Signature as a Highly Effective Melanoma Marker

Simple Summary

In this study, we investigated the expression of 27 cytokines/chemokines in the serum of 232 individuals (136 melanoma patients vs. 96 controls). It identified several cytokines/chemokines differently expressed in melanoma patients as compared to the healthy controls, as a function of the presence of the melanoma, age, tumor thickness, and gender, indicating different systemic responses to the melanoma presence. We also analyzed the gene expression of the same 27 molecules at the tissue level in 511 individuals (melanoma patients vs. controls). From the gene expression analysis, we identified several cytokines/chemokines showing strongly different expression in melanoma as compared to the controls, and the 4-gene signature “IL-1Ra, IL-7, MIP-1a, and MIP-1b” as the best combination to discriminate melanoma samples from the controls, with an extremely high accuracy (AUC = 0.98). These data indicate the molecular mechanisms underlying melanoma setup and the relevant markers potentially useful to help the diagnosis of biopsy samples.

Abstract

The identification of reliable and quantitative melanoma biomarkers may help an early diagnosis and may directly affect melanoma mortality and morbidity. The aim of the present study was to identify effective biomarkers by investigating the expression of 27 cytokines/chemokines in melanoma compared to healthy controls, both in serum and in tissue samples. Serum samples were from 232 patients recruited at the IDI-IRCCS hospital. Expression was quantified by xMAP technology, on 27 cytokines/chemokines, compared to the control sera. RNA expression data of the same 27 molecules were obtained from 511 melanoma- and healthy-tissue samples, from the GENT2 database. Statistical analysis involved a 3-step approach: analysis of the single-molecules by Mann–Whitney analysis; analysis of paired-molecules by Pearson correlation; and profile analysis by the machine learning algorithm Support Vector Machine (SVM). Single-molecule analysis of serum expression identified IL-1b, IL-6, IP-10, PDGF-BB, and RANTES differently expressed in melanoma (p < 0.05). Expression of IL-8, GM-CSF, MCP-1, and TNF-α was found to be significantly correlated with Breslow thickness. Eotaxin and MCP-1 were found differentially expressed in male vs. female patients. Tissue expression analysis identified very effective marker/predictor genes, namely, IL-1Ra, IL-7, MIP-1a, and MIP-1b, with individual AUC values of 0.88, 0.86, 0.93, 0.87, respectively. SVM analysis of the tissue expression data identified the combination of these four molecules as the most effective signature to discriminate melanoma patients (AUC = 0.98). Validation, using the GEPIA2 database on an additional 1019 independent samples, fully confirmed these observations. The present study demonstrates, for the first time, that the IL-1Ra, IL-7, MIP-1a, and MIP-1b gene signature discriminates melanoma from control tissues with extremely high efficacy. We therefore propose this 4-molecule combination as an effective melanoma marker.

An investigation into the molecular basis of cancer comorbidities in coronavirus infection

Comorbidities in COVID‐19 patients often worsen clinical conditions and may represent death predictors. Here, the expression of five genes, known to encode coronavirus receptors/interactors (ACE2, TMPRSS2, CLEC4M, DPP4 and TMPRSS11D), was investigated in normal and cancer tissues, and their molecular relationships with clinical comorbidities were investigated. Using expression data from GENT2 databases, we evaluated gene expression in all anatomical districts from 32 normal tissues in 3902 individuals. Functional relationships with body districts were analyzed by chilibot. We performed DisGeNet, genemania and DAVID analyses to identify human diseases associated with these genes. Transcriptomic expression levels were then analyzed in 31 cancer types and healthy controls from approximately 43 000 individuals, using GEPIA2 and GENT2 databases. By performing receiver operating characteristic analysis, the area under the curve (AUC) was used to discriminate healthy from cancer patients. Coronavirus receptors were found to be expressed in several body districts. Moreover, the five genes were found to associate with acute respiratory syndrome, diabetes, cardiovascular diseases and cancer (i.e. the most frequent COVID‐19 comorbidities). Their expression levels were found to be significantly altered in cancer types, including colon, kidney, liver, testis, thyroid and skin cancers (P < 0.0001); AUC > 0.80 suggests that TMPRSS2, CLEC4M and DPP4 are relevant markers of kidney, liver, and thyroid cancer, respectively. The five coronavirus receptors are related to all main COVID‐19 comorbidities and three show significantly different expression in cancer versus control tissues. Further investigation into their role may help in monitoring other comorbidities, as well as for follow‐up of patients who have recovered from SARS‐CoV‐2 infection.