Genetic Polymorphism in TNF-α-308 G/A and TNF-β +252 A/G, as Prognostic Biomarker in Breast Cancer Patients among Indian Population

Serum protein profiling reveals an inflammation signature as a predictor of early breast cancer survival

BACKGROUND

Breast cancers exhibit considerable heterogeneity in their biology, immunology, and prognosis. Currently, no validated, serum protein-based tools are available to evaluate the prognosis of patients with early breast cancer.

METHODS

The study population consisted of 521 early-stage breast cancer patients with a median follow-up of 8.9 years. Additionally, 61 patients with breast fibroadenoma or atypical ductal hyperplasia were included as controls. We used a proximity extension assay to measure the preoperative serum levels of 92 proteins associated with inflammatory and immune response processes. The invasive cancers were randomly split into discovery (n = 413) and validation (n = 108) cohorts for the statistical analyses.

RESULTS

Using LASSO regression, we identified a nine-protein signature (CCL8, CCL23, CCL28, CSCL10, S100A12, IL10, IL10RB, STAMPB2, and TNFβ) that predicted various survival endpoints more accurately than traditional prognostic factors. In the time-dependent analyses, the prognostic power of the model remained rather stable over time. We also developed and validated a 17-protein model with the potential to differentiate benign breast lesions from malignant lesions (Wilcoxon p < 2.2*10- 16; AUC 0.94).

CONCLUSIONS

Inflammation and immunity-related serum proteins have the potential to rise above the classical prognostic factors of early-stage breast cancer. They may also help to distinguish benign from malignant breast lesions.

Multifunctionality of Calebin A in inflammation, chronic diseases and cancer

Chronic diseases including cancer have high case numbers as well as mortality rates. The efficient treatment of chronic diseases is a major ongoing medical challenge worldwide, because of their complexity and many inflammatory pathways such as JNK, p38/MAPK, MEK/ERK, JAK/STAT3, PI3K and NF-κB among others being implicated in their pathogenesis. Together with the versatility of chronic disease classical mono-target therapies are often insufficient. Therefore, the anti-inflammatory as well as anti-cancer capacities of polyphenols are currently investigated to complement and improve the effect of classical anti-inflammatory drugs, chemotherapeutic agents or to overcome drug resistance of cancer cells. Currently, research on Calebin A, a polyphenolic component of turmeric (Curcuma longa), is becoming of growing interest with regard to novel treatment strategies and has already been shown health-promoting as well as anti-tumor properties, including anti-oxidative and anti-inflammatory effects, in diverse cancer cells. Within this review, we describe already known anti-inflammatory activities of Calebin A via modulation of NF-κB and its associated signaling pathways, linked with TNF-α, TNF-β and COX-2 and further summarize Calebin A’s tumor-inhibiting properties that are known up to date such as reduction of cancer cell viability, proliferation as well as metastasis. We also shed light on possible future prospects of Calebin A as an anti-cancer agent.

Impact of TNF-α Gene Polymorphisms on Pancreatic and Non-Small Cell Lung Cancer-Induced Cachexia in Adult Egyptian Patients: A Focus on Pathogenic Trajectories

Background

Cachexia is a frequent syndrome in pancreatic and non-small cell lung (NSCL) cancer patients. The storm of cancer-induced inflammatory cytokines, in particular TNF-α, is a crucial pathogenic mechanism. Among the molecular alterations accused of cancer-induced cachexia, TNF-α 308 G/A (rs1800629) and −1031T/C (rs1799964) are single-nucleotide polymorphisms (SNPs) within the gene encoding this pro-inflammatory cytokine. Recent studies have demonstrated the crucial role of non-coding microRNAs (miRNAs) in pathogenesis of different diseases including cachexia. Moreover, the mechanistic cytokine signaling pathway of miR-155, as a TNF-α regulator, supports the involvement of SOCS1, TAB2, and Foxp3, which are direct targets of TNF-α gene.

Aim

A case–control study (NCT04131478) was conducted primarily to determine the incidence of TNF-α 308 G/A (rs1800629) and −1031T/C (rs1799964) gene polymorphisms in adult Egyptian patients with local/advanced or metastatic pancreatic or NSCL cancer and investigate both as cachexia risk factors. The association of gene polymorphism with cachexia severity and the expression of miR-155 in cachectic patients were analyzed. A mechanistic investigation of the cytokine signaling pathway, involving SOCS1, TAB2, and Foxp3, was also performed.

Results

In both pancreatic and NSCL cancer cohorts, the mutant TNF-α variant of 308 G/A was positively associated with cachexia; on the contrary, that of 1031T/C was negatively associated with cachexia in the NSCL cancer patients. MiR-155 was higher in cachexia and in alignment with its severity in the cachectic group as compared with the non-cachectic group in both the pancreatic and NSCL cancer patients. Though TAB2 did not change to any significant extent in cachectic patients, the levels of SOCS1 and Foxp3 were significantly lower in the cachectic group as compared with the non-cachectic group.

Conclusion

Carriers of the A allele 308 G/A gene and high miR-155 are at greater risk of cachexia in both the pancreatic and NSCL cancer patients; however, the mutant variant of 1031T/C gene is protective against cachexia in the NSCL cancer patients. Finally, high levels of miR-155 in the cachectic group lead to negative feedback inhibition of both SOCS1 and Foxp3 in both the pancreatic and NSCL cancer patients.

Association between five types of Tumor Necrosis Factor-α gene polymorphism and hepatocellular carcinoma risk: a meta-analysis

BACKGROUND

Research focusing on the relationship between five types of tumor necrosis factor-alpha (TNF-α) SNPs and the risk of hepatocellular carcinoma (HCC) were still controversial. Hereby, we performed a meta-analysis to determine the association between TNF-α promoter SNPs: -1031 T/C, - 863 C/A, - 857 C/T, - 308 G/A, and - 238 G/A with HCC risk.

METHODS

We interrogated articles from journal database: PubMed, Pro-Quest, EBSCO, Science Direct, and Springer to determine the relationship between five types of SNPs in TNF-α gene with HCC risk. RevMan 5.3 software was used for analysis in fixed/random effect models.

RESULTS

This meta-analysis included 23 potential articles from 2004 to 2018 with 3237 HCC cases and 4843 controls. We found that SNP - 863 C/A were associated with a significantly increased HCC risk (A vs C, OR = 1.31, 95% CI = 1.03-1.67). Similar results were obtained in - 857 C/T (TT/CT vs CC, OR = 1.31, 95% CI = 1.06-1.62), - 308 G/A (AA vs GG, OR = 3.14, 95% CI = 2.06-4.79), and - 238 G/A (AA vs GG, OR = 3.87, 95% CI = 1.32-11.34). While no associations were observed between SNP TNF-α - 1031 T/C and HCC risk.

CONCLUSIONS

The present meta-analysis showed that TNFα SNPs -863C/A, - 857 C/T, - 308 G/A, and - 238 G/A were associated with the risk of HCC.

A Quest for New Cancer Diagnosis, Prognosis and Prediction Biomarkers and Their Use in Biosensors Development

Traditional techniques for cancer diagnosis, such as nuclear magnetic resonance, ultrasound and tissue analysis, require sophisticated devices and highly trained personnel, which are characterized by elevated operation costs. The use of biomarkers has emerged as an alternative for cancer diagnosis, prognosis and prediction because their measurement in tissues or fluids, such as blood, urine or saliva, is characterized by shorter processing times. However, the biomarkers used currently, and the techniques used for their measurement, including ELISA, western-blot, polymerase chain reaction (PCR) or immunohistochemistry, possess low sensitivity and specificity. Therefore, the search for new proteomic, genomic or immunological biomarkers and the development of new noninvasive, easier and cheaper techniques that meet the sensitivity and specificity criteria for the diagnosis, prognosis and prediction of this disease has become a relevant topic. The purpose of this review is to provide an overview about the search for new cancer biomarkers, including the strategies that must be followed to identify them, as well as presenting the latest advances in the development of biosensors that possess a high potential for cancer diagnosis, prognosis and prediction, mainly focusing on their relevance in lung, prostate and breast cancers.