Aberrant Cyclin D1 splicing in cancer: from molecular mechanism to therapeutic modulation

Cyclin D1 (CCND1), a crucial mediator of cell cycle progression, possesses many mutation types with different mutation frequencies in human cancers. The G870A mutation is the most common mutation in CCND1, which produces two isoforms: full-length CCND1a and divergent C-terminal CCND1b. The dysregulation of the CCND1 isoforms is associated with multiple human cancers. Exploring the molecular mechanism of CCND1 isoforms has offer new insight for cancer treatment. On this basis, the alterations of CCND1 gene are described, including amplification, overexpression, and mutation, especially the G870A mutation. Subsequently, we review the characteristics of CCND1 isoforms caused by G870A mutation. Additionally, we summarize cis-regulatory elements, trans-acting factors, and the splice mutation involved in splicing regulation of CCND1. Furthermore, we highlight the function of CCND1 isoforms in cell cycle, invasion, and metastasis in cancers. Importantly, the clinical role of CCND1 isoforms is also discussed, particularly concerning prognosis, chemotherapy, and radiotherapy. Last, emphasis is given to the corrective strategies that modulate the cancerous CCND1 isoforms. Thus, it is highlighting significance of aberrant isoforms of CCND1 as targets for cancer therapy.

Association between common variants in vitamin D receptor gene and susceptibility to Non-Hodgkin's lymphoma: a case-control study

Vitamin D (VDR)-mediated signaling contributes to the cell signaling pathways that affect cancer development. This study is conducted on 104 patients diagnosed with non-Hodgkin's lymphoma (NHL) and 246 healthy subjects to investigate the link between five genetic variants spanning the VDR gene and the risk of this malignancy in Iranian subjects. The PCR-RFLP method was used for the analysis of BsmI (rs1544410), ApaI (rs7975232), FokI (rs2228570) and TaqI (rs731236) variants. A simple Tetra-ARMS-PCR technique was employed for the genotyping of the Cdx2 (rs11568820) variant. No significant link was found between both groups regarding ApaI (rs7975232) and FokI (rs2228570) variants (P > 0.05). Also, different genetic models of TaqI (rs731236), BsmI (rs1544410) and Cdx2 (rs11568820) polymorphisms were significantly correlated to decreased risk of NHL (Odd ratios <1). We found three haplotypes were strongly associated with an increased risk of NHL (P < 0.0001). Linkage-disequilibrium (LD) analysis showed a strong linkage between TaqI (rs731236) and BsmI (rs1544410) among NHL case and control subjects. Our findings indicated that functional variants of the VDR gene are linked to a decreased risk of NHL in our population. Further replication studies in different ethnic groups are needed to validate our results.

DNLC: differential network local consistency analysis

BACKGROUND

The biological network is highly dynamic. Functional relations between genes can be activated or deactivated depending on the biological conditions. On the genome-scale network, subnetworks that gain or lose local expression consistency may shed light on the regulatory mechanisms related to the changing biological conditions, such as disease status or tissue developmental stages.

RESULTS

In this study, we develop a new method to select genes and modules on the existing biological network, in which local expression consistency changes significantly between clinical conditions. The method is called DNLC: Differential Network Local Consistency. In simulations, our algorithm detected artificially created local consistency changes effectively. We applied the method on two publicly available datasets, and the method detected novel genes and network modules that were biologically plausible.

CONCLUSIONS

The new method is effective in finding modules in which the gene expression consistency change between clinical conditions. It is a useful tool that complements traditional differential expression analyses to make discoveries from gene expression data. The R package is available at https://cran.r-project.org/web/packages/DNLC.

Association between Cyclin D1 G870A (rs9344) polymorphism and cancer risk in Indian population: meta-analysis and trial sequential analysis

Introduction: Association between Cyclin D1 (CCND1) single nucleotide polymorphism (SNP) rs9344 and cancer risk is paradoxical. Thus, we performed a meta-analysis to explore the association between CCND1 variant and overall cancer risk in Indian population. Methods: Data from 12 published studies including 3739 subjects were collected using Pubmed and Embase. RevMan (Review Manager) 5.3 was used to perform the meta-analysis. OR with 95%CI were calculated to establish the association. Results: Overall, the cumulative findings demonstrated that CCND1 polymorphism (rs9344) was not significantly associated with cancer risk in all the genetic models studied (dominant model: GG vs GA+AA: OR (95%CI) = 0.81 (0.60-1.09), P=0.17; recessive model: GG+GA vs AA: OR (95%CI) = 1.23 (0.96-1.59), P=0.11; co-dominant model: GG vs AA: OR (95%CI) = 1.35 (0.93-1.97), P=0.12; co-dominant model: (GG vs GA: OR (95%CI) = 1.16 (0.85-1.59), P=0.34; allelic model: A vs G: OR (95%CI) = 1.20 (1.14-2.85), P=0.23; allelic model: G vs A: OR (95%CI) = 0.83 (0.62-1.12), P=0.23). Subgroup analysis according to cancer types presented significant association of CCND1 polymorphism and increased breast cancer risk in dominant model (GG vs GA+AA: OR = 2.75, 95%CI = 1.54-4.90, P=0.0006) and allelic model (G vs A: OR = 1.63, 95%CI = 1.22-2.19, P=0.001). An increased esophageal cancer risk in recessive model (GG+GA vs AA: OR = 1.51, 95%CI = 1.05-2.16, P=0.03) and co-dominant model (GG vs AA: OR = 2.51, 95%CI = 1.10-5.71, P=0.03) was detected. A higher risk for colorectal cancer was detected under both the co-dominant models (GG vs AA: OR = 2.46, 95%CI = 1.34-4.51, P=0.004 and GG vs GA: OR = 1.74, 95%CI = 1.14-2.67, P=0.01). However, in case of cervical cancer risk a non-significant association was reported under the recessive model (GG+GA vs AA: OR = 1.52, 95%CI = 0.60-3.90, P=0.38) with reference to CCND1 polymorphism (rs9344). The trial sequential analysis (TSA) showed that the cumulative Z-curve neither crossed the trial sequential monitoring boundary nor reached the required information size (RIS). Thus, present meta-analysis remained inconclusive due to insufficient evidence. Conclusion:CCND1 polymorphism rs9344 may not have a role in overall cancer susceptibility in Indian population. However, this polymorphism acts as a crucial risk factor for breast, esophageal, and colorectal cancer but not for cervical cancer. Future studies with larger sample size are required to draw a reliable conclusion.