A common variant within the HNF1B gene is associated with overall survival of multiple myeloma patients: results from the IMMEnSE consortium and meta-analysis

Polymorphisms within autophagy-related genes as susceptibility biomarkers for pancreatic cancer: A meta-analysis of three large European cohorts and functional characterization

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with patients having unresectable or metastatic disease at diagnosis, with poor prognosis and very short survival. Given that genetic variation within autophagy-related genes influences autophagic flux and susceptibility to solid cancers, we decided to investigate whether 55,583 single nucleotide polymorphisms (SNPs) within 234 autophagy-related genes could influence the risk of developing PDAC in three large independent cohorts of European ancestry including 12,754 PDAC cases and 324,926 controls. The meta-analysis of these populations identified, for the first time, the association of the BIDrs9604789 variant with an increased risk of developing the disease (ORMeta = 1.31, p = 9.67 × 10-6). We also confirmed the association of TP63rs1515496 and TP63rs35389543 variants with PDAC risk (OR = 0.89, p = 6.27 × 10-8 and OR = 1.16, p = 2.74 × 10-5). Although it is known that BID induces autophagy and TP63 promotes cell growth, cell motility and invasion, we also found that carriers of the TP63rs1515496G allele had increased numbers of FOXP3+ Helios+ T regulatory cells and CD45RA+ T regulatory cells (p = 7.67 × 10-4 and p = 1.56 × 10-3), but also decreased levels of CD4+ T regulatory cells (p = 7.86 × 10-4). These results were in agreement with research suggesting that the TP63rs1515496 variant alters binding sites for FOXA1 and CTCF, which are transcription factors involved in modulating specific subsets of regulatory T cells. In conclusion, this study identifies BID as new susceptibility locus for PDAC and confirms previous studies suggesting that the TP63 gene is involved in the development of PDAC. This study also suggests new pathogenic mechanisms of the TP63 locus in PDAC.

Influence of diabetes mellitus on the biochemical parameters and outcomes of multiple myeloma

OBJECTIVE

The incidence of MM in most registries remains stable or showing only a slightly increase. However, prevalence of MM is increasing due to the increase in overall survival in the last two decades. The aim of this study was to observe changes in biochemical parameters during the diagnosis and treatment of MM.

METHODS

A retrospective analysis was made of the biochemical indicators, survival time, and related adverse events of 196 patients with MM.

RESULTS

Of the 196 patients with MM, 26 were diagnosed with DM (DM-MM group) at the first diagnosis, 31 with steroid-induced diabetes mellitus (SID-MM group) during treatment, and 139 without DM (MM group). There was no significant difference between the three groups in the mean age of onset, sex ratio, incidence of hypercalcemia, renal dysfunction, anemia, abnormal lactate dehydrogenase, and median value of D-dimer and fibrinogen during diagnosis and treatment. There was no significant difference in survival time between the SID-MM and MM groups, but there was a significant difference between the DM-MM and MM groups.

CONCLUSION

There was no significant difference between the three groups in the incidence of hypercalcemia, anemia, and renal function impairment. The survival time of patients with DM was shorter than that of patients without DM.

Polymorphisms within Autophagy-Related Genes as Susceptibility Biomarkers for Multiple Myeloma: A Meta-Analysis of Three Large Cohorts and Functional Characterization

Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10^-9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10^-4-5.79 × 10^-14). Mechanistically, we found that the ULK4_rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10^-4), whereas the IKBKE_rs17433804 SNP correlated with the number of transitional CD24⁺CD38⁺ B cells (p = 4.8 × 10^-4) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10^-4). We also found that the CD46_rs1142469 SNP correlated with numbers of CD19⁺ B cells, CD19⁺CD3^- B cells, CD5⁺IgD^- cells, IgM^- cells, IgD^-IgM^- cells, and CD4^-CD8^- PBMCs (p = 4.9 × 10^-4-8.6 × 10^-4) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2A_rs2811710 SNP correlated with levels of CD4⁺EMCD45RO⁺CD27^- cells (p = 9.3 × 10^-4). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3^-, MCP-2^-, and IL20-dependent pathways.

GWAS-Identified Variants for Obesity Do Not Influence the Risk of Developing Multiple Myeloma: A Population-Based Study and Meta-Analysis

Multiple myeloma (MM) is an incurable disease characterized by the presence of malignant plasma cells in the bone marrow that secrete specific monoclonal immunoglobulins into the blood. Obesity has been associated with the risk of developing solid and hematological cancers, but its role as a risk factor for MM needs to be further explored. Here, we evaluated whether 32 genome-wide association study (GWAS)-identified variants for obesity were associated with the risk of MM in 4189 German subjects from the German Multiple Myeloma Group (GMMG) cohort (2121 MM cases and 2068 controls) and 1293 Spanish subjects (206 MM cases and 1087 controls). Results were then validated through meta-analysis with data from the UKBiobank (554 MM cases and 402,714 controls) and FinnGen cohorts (914 MM cases and 248,695 controls). Finally, we evaluated the correlation of these single nucleotide polymorphisms (SNPs) with cQTL data, serum inflammatory proteins, steroid hormones, and absolute numbers of blood-derived cell populations (n = 520). The meta-analysis of the four European cohorts showed no effect of obesity-related variants on the risk of developing MM. We only found a very modest association of the POC5_rs2112347G and ADCY3_rs11676272G alleles with MM risk that did not remain significant after correction for multiple testing (per-allele OR = 1.08, p = 0.0083 and per-allele OR = 1.06, p = 0.046). No correlation between these SNPs and functional data was found, which confirms that obesity-related variants do not influence MM risk.

Current perspectives on interethnic variability in multiple myeloma: Single cell technology, population pharmacogenetics and molecular signal transduction

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This review discusses the emerging single cell technologies and applications in Multiple myeloma (MM), population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction.

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The role(s) of epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of MM are also discussed.

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It is understood that ethnic component acts as a driver of variable response to chemotherapy in different sub-populations globally.

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This review augments our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, myeloma microenvironment at the molecular and cellular level, and developing precision medicine strategies to combat this malignancy.

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The emerging single cell technologies hold great promise for enhancing our understanding of MM tumor heterogeneity and clonal diversity.

Multiple myeloma (MM) is an aggressive cancer characterised by malignancy of the plasma cells and a rising global incidence. The gold standard for optimum response is aggressive chemotherapy followed by autologous stem cell transplantation (ASCT). However, majority of the patients are above 60 years and this presents the clinician with complications such as ineligibility for ASCT, frailty, drug-induced toxicity and differential/partial response to treatment. The latter is partly driven by heterogenous genotypes of the disease in different subpopulations. In this review, we discuss emerging single cell technologies and applications in MM, population pharmacogenetics of MM, resistance to chemotherapy, genetic determinants of drug-induced toxicity, molecular signal transduction, as well as the role(s) played by epigenetics and noncoding RNAs including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) that influence the risk and severity of the disease. Taken together, our discussions further our understanding of genetic variability in ‘myelomagenesis’ and drug-induced toxicity, augment our understanding of the myeloma microenvironment at the molecular and cellular level and provide a basis for developing precision medicine strategies to combat this malignancy.

Type 2 Diabetes-Related Variants Influence the Risk of Developing Prostate Cancer: A Population-Based Case-Control Study and Meta-Analysis

In this study, we have evaluated whether 57 genome-wide association studies (GWAS)-identified common variants for type 2 diabetes (T2D) influence the risk of developing prostate cancer (PCa) in a population of 304 Caucasian PCa patients and 686 controls. The association of selected single nucleotide polymorphisms (SNPs) with the risk of PCa was validated through meta-analysis of our data with those from the UKBiobank and FinnGen cohorts, but also previously published genetic studies. We also evaluated whether T2D SNPs associated with PCa risk could influence host immune responses by analysing their correlation with absolute numbers of 91 blood-derived cell populations and circulating levels of 103 immunological proteins and 7 steroid hormones. We also investigated the correlation of the most interesting SNPs with cytokine levels after in vitro stimulation of whole blood, peripheral mononuclear cells (PBMCs), and monocyte-derived macrophages with LPS, PHA, Pam3Cys, and Staphylococcus Aureus. The meta-analysis of our data with those from six large cohorts confirmed that each copy of the FTO_rs9939609A, HNF1B_rs7501939T, HNF1B_rs757210T, HNF1B_rs4430796G, and JAZF1_rs10486567A alleles significantly decreased risk of developing PCa (p = 3.70 × 10^-5, p = 9.39 × 10^-54, p = 5.04 × 10^-54, p = 1.19 × 10^-71, and p = 1.66 × 10^-18, respectively). Although it was not statistically significant after correction for multiple testing, we also found that the NOTCH2_rs10923931T and RBMS1_rs7593730 SNPs associated with the risk of developing PCa (p = 8.49 × 10^-4 and 0.004). Interestingly, we found that the protective effect attributed to the HFN1B locus could be mediated by the SULT1A1 protein (p = 0.00030), an arylsulfotransferase that catalyzes the sulfate conjugation of many hormones, neurotransmitters, drugs, and xenobiotic compounds. In addition to these results, eQTL analysis revealed that the HNF1B_rs7501939, HNF1B_rs757210, HNF1B_rs4430796, NOTCH2_rs10923931, and RBMS1_rs7593730 SNPs influence the risk of PCa through the modulation of mRNA levels of their respective genes in whole blood and/or liver. These results confirm that functional TD2-related variants influence the risk of developing PCa, but also highlight the need of additional experiments to validate our functional results in a tumoral tissue context.

Haplotypes of single cancer driver genes and their local ancestry in a highly admixed long-lived population of Northeast Brazil

Admixed populations have not been examined in detail in cancer genetic studies. Here, we inferred the local ancestry of cancer-associated single nucleotide polymorphisms (SNPs) and haplotypes of a highly admixed Brazilian population. SNP array was used to genotype 73 unrelated individuals aged 80-102 years. Local ancestry inference was performed by merging genotyped regions with phase three data from the 1000 Genomes Project Consortium using RFmix. The average ancestry tract length was 9.12-81.71 megabases. Strong linkage disequilibrium was detected in 48 haplotypes containing 35 SNPs in 10 cancer driver genes. All together, 19 risk and eight protective alleles were identified in 23 out of 48 haplotypes. Homozygous individuals were mainly of European ancestry, whereas heterozygotes had at least one Native American and one African ancestry tract. Native-American ancestry for homozygous individuals with risk alleles for HNF1B, CDH1, and BRCA1 was inferred for the first time. Results indicated that analysis of SNP polymorphism in the present admixed population has a high potential to identify new ancestry-associated alleles and haplotypes that modify cancer susceptibility differentially in distinct human populations. Future case-control studies with populations with a complex history of admixture could help elucidate ancestry-associated biological differences in cancer incidence and therapeutic outcomes.

Genetically determined telomere length and multiple myeloma risk and outcome

Telomeres are involved in processes like cellular growth, chromosomal stability, and proper segregation to daughter cells. Telomere length measured in leukocytes (LTL) has been investigated in different cancer types, including multiple myeloma (MM). However, LTL measurement is prone to heterogeneity due to sample handling and study design (retrospective vs. prospective). LTL is genetically determined; genome-wide association studies identified 11 SNPs that, combined in a score, can be used as a genetic instrument to measure LTL and evaluate its association with MM risk. This approach has been already successfully attempted in various cancer types but never in MM. We tested the "teloscore" in 2407 MM patients and 1741 controls from the International Multiple Myeloma rESEarch (IMMeNSE) consortium. We observed an increased risk for longer genetically determined telomere length (gdTL) (OR = 1.69; 95% CI 1.36-2.11; P = 2.97 × 10^-6 for highest vs. lowest quintile of the score). Furthermore, in a subset of 1376 MM patients we tested the relationship between the teloscore and MM patients survival, observing a better prognosis for longer gdTL compared with shorter gdTL (HR = 0.93; 95% CI 0.86-0.99; P = 0.049). In conclusion, we report convincing evidence that longer gdTL is a risk marker for MM risk, and that it is potentially involved in increasing MM survival.

Expression quantitative trait loci of genes predicting outcome are associated with survival of multiple myeloma patients

Gene expression profiling can be used for predicting survival in multiple myeloma (MM) and identifying patients who will benefit from particular types of therapy. Some germline single nucleotide polymorphisms (SNPs) act as expression quantitative trait loci (eQTLs) showing strong associations with gene expression levels. We performed an association study to test whether eQTLs of genes reported to be associated with prognosis of MM patients are directly associated with measures of adverse outcome. Using the genotype-tissue expression portal, we identified a total of 16 candidate genes with at least one eQTL SNP associated with their expression with P < 10^-7 either in EBV-transformed B-lymphocytes or whole blood. We genotyped the resulting 22 SNPs in 1327 MM cases from the International Multiple Myeloma rESEarch (IMMEnSE) consortium and examined their association with overall survival (OS) and progression-free survival (PFS), adjusting for age, sex, country of origin and disease stage. Three polymorphisms in two genes (TBRG4-rs1992292, TBRG4-rs2287535 and ENTPD1-rs2153913) showed associations with OS at P < .05, with the former two also associated with PFS. The associations of two polymorphisms in TBRG4 with OS were replicated in 1277 MM cases from the International Lymphoma Epidemiology (InterLymph) Consortium. A meta-analysis of the data from IMMEnSE and InterLymph (2579 cases) showed that TBRG4-rs1992292 is associated with OS (hazard ratio = 1.14, 95% confidence interval 1.04-1.26, P = .007). In conclusion, we found biologically a plausible association between a SNP in TBRG4 and OS of MM patients.

Hepatocyte nuclear factor 1 beta: A perspective in cancer

Hepatocyte nuclear factor 1 beta (HNF1 β/B) exists as a homeobox transcription factor having a vital role in the embryonic development of organs mainly liver, kidney and pancreas. Initially described as a gene causing maturity‐onset diabetes of the young (MODY), HNF1β expression deregulation and single nucleotide polymorphisms in HNF1β have now been associated with several tumours including endometrial, prostate, ovarian, hepatocellular, renal and colorectal cancers. Its function has been studied either as homodimer or heterodimer with HNF1α. In this review, the role of HNF1B in different cancers will be discussed along with the role of its splice variants, and its emerging role as a potential biomarker in cancer.

Host immune genetic variations influence the risk of developing acute myeloid leukaemia: results from the NuCLEAR consortium

The purpose of this study was to conduct a two-stage case control association study including 654 acute myeloid leukaemia (AML) patients and 3477 controls ascertained through the NuCLEAR consortium to evaluate the effect of 27 immune-related single nucleotide polymorphisms (SNPs) on AML risk. In a pooled analysis of cohort studies, we found that carriers of the IL13_rs1295686A/A genotype had an increased risk of AML (P_Corr = 0.0144) whereas carriers of the VEGFA_rs25648T allele had a decreased risk of developing the disease (P_Corr = 0.00086). In addition, we found an association of the IL8_rs2227307 SNP with a decreased risk of developing AML that remained marginally significant after multiple testing (P_Corr = 0.072). Functional experiments suggested that the effect of the IL13_rs1295686 SNP on AML risk might be explained by its role in regulating IL1Ra secretion that modulates AML blast proliferation. Likewise, the protective effect of the IL8_rs2227307 SNP might be mediated by TLR2-mediated immune responses that affect AML blast viability, proliferation and chemorresistance. Despite the potential interest of these results, additional functional studies are still warranted to unravel the mechanisms by which these variants modulate the risk of AML. These findings suggested that IL13, VEGFA and IL8 SNPs play a role in modulating AML risk.

Current and future biomarkers for risk-stratification and treatment personalisation in multiple myeloma

Multiple myeloma, an incurable malignancy of the plasma cells in the bone marrow, has a complex pathogenesis due to clonal heterogeneity. Over the years, many clinical trials and researches have led to the development of effective myeloma treatments, resulting in survival prolongation. Molecular prognostic markers for risk-stratification to predict survival, and predictive markers for treatment response are being extensively explored. This review discusses the current risk-adaptive strategies based on genetic and molecular risk signatures that are in practice to predict survival and describes the future prognostic and predictive biomarkers across the fields of genomics, proteomics, and glycomics in myeloma. Gene expression profiling and next generation sequencing are coming to the forefront of risk-stratification and therapeutic-response prediction. Similarly, proteomic and glycomic-based platforms are gaining momentum in biomarker discovery to predict drug resistance and disease progression.

Identification of novel genetic variants for type 2 diabetes, childhood obesity, and their pleiotropic loci

Obesity has result in increased prevalence of type 2 diabetes (T2D) in children. The genetic mechanisms underlying their relationship, however, are not fully understood. Here, we aim to identify novel SNPs associated with T2D and childhood obesity (CO), especially their pleiotropic loci. We integrated the summary statistics for two independent GWASs of T2D (n = 149,821) and childhood body mass index (CBMI) (n = 35,668) using the pleiotropy-informed conditional false discovery rate (cFDR) method. By leveraging the information of different levels of association for CBMI, we observed a strong enrichment of genetic variants associated with T2D. We identified 139 T2D-associated SNPs with 125 novel ones (cFDR < 0.05). Conditioned on T2D, we identified 37 significant SNPs for CBMI (cFDR < 0.05), including 25 novel ones. The conjunctional cFDR (ccFDR) analysis showed ten novel pleiotropic loci for T2D and CBMI (ccFDR < 0.05). Interestingly, the novel SNP rs1996023 is located at protein coding gene GNPDA2 (ccFDR = 1.28E-02), which has been reported to influence the risk of T2D and CO through central nervous system. Our findings may help to explain a greater proportion of the heritability for human traits and advance the understanding of the common pathophysiology between T2D and CO.

Genetic polymorphisms in genes of class switch recombination and multiple myeloma risk and survival: an IMMEnSE study

Genetic variants in genes acting during the maturation process of immature B-cell to differentiated plasma cell could influence the risk of developing multiple myeloma (MM). During B-cell maturation, several programmed genetic rearrangements occur to increase the variation of the immunoglobulin chains. Class switch recombination (CSR) is one of the most important among these mechanisms. Germline polymorphisms altering even subtly this process could play a role in the etiology and outcome of MM. We performed an association study of 30 genetic variants in the key CSR genes, using 2632 MM patients and 2848 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, the Heidelberg MM Group and the ESTHER cohort. We found an association between LIG4-rs1555902 and decreased MM risk, which approached statistical significance, as well as significant associations between AICDA-rs3794318 and better outcome. Our results add to our knowledge on the genetic component of MM risk and survival.

Inherited variation in the xenobiotic transporter pathway and survival of multiple myeloma patients

Over the past four decades, remarkable progress has been made in the treatment and prognosis of multiple myeloma (MM), although it remains an incurable disease. Chemotherapy resistance is a major hurdle for treatment efficacy. Drug resistance can be innate and so driven by genes involved in the drug metabolism pathways. We performed an association study of 71 germline variants within the major genes in those pathways (ABCB1, ABCC2, ABCG2, and their regulators NR1I2/PXR and NR1I3/CAR) in the International Multiple Myeloma rESEarch (IMMEnSE) consortium, consisting of 1365 MM cases with survival information recruited in 5 European countries. Two of the SNPs showed a significant association with the survival of MM patients, namely rs2235013, located in ABCB1 [Hazard ratio (HR) = 1·52, 95% confidence interval (CI) = 1·18-1·95, P = 0·00087], and rs4148388, located in ABCC2 (HR = 2·15, 95% CI = 1·44-3·22, P = 0·0001). ABCC2 plays an essential role in transporting various anticancer drugs, including several used against MM, out of the cell. In silico analyses predict that the variant alleles of four SNPs in linkage disequilibrium with ABCC2-rs4148388 are associated with increased gene expression. Overexpression of ABCC2 increases drug clearance and therefore may induce drug resistance mechanisms. In conclusion, we found a promising association between ABCC2-rs4148388 and MM outcome that is supported by a plausible biological explanation.

Cumulative evidence for relationships between multiple variants of HNF1B and the risk of prostate and endometrial cancers

Background

To provide a synopsis of the current understanding of the association between variants of HNF1B and cancer susceptibility, we conducted a comprehensive research synopsis and meta-analysis to evaluate associations between HNF1B variants and prostate and endometrial cancers.

Results

Eighteen studies totaling 34,937 patients and 55,969 controls were eligible for this meta-analysis. Four variants showed a significant association with the risk of individual cancer. Strong significant associations were found between rs4430796 A and the risk of both prostate cancer (OR = 1.247, p = 2.21 × 10^− 77) and endometrial cancer (OR = 1.217, p = 8.98 × 10^− 16); the AA, AG genotypes also showed strong significant associations with the risk of prostate cancer (OR1 = 1.517, p = 4.46 × 10^− 22; OR2 = 1.180, p = 0.002). There was a strong significant association between rs7501939 G and the risk of prostate cancer (OR = 1.201, p = 9.31 × 10^− 31). Strong significant association was found between rs11649743 G (OR = 1.138, p = 1.08 × 10^− 12), rs3760511 C (OR = 1.214, p = 1.57 × 10^− 19) and the prostate cancer risk;the GG, AG genotypes of rs11649743 also showed strong significant associations with the risk of prostate cancer (OR1 = 1.496, p = 3.32 × 10^− 6; OR2 = 1.276, p = 7.82 × 10^− 6). All the cumulative epidemiological evidence of associations was graded as strong.

Conclusions

Our study summarizes the evidence and helps to reveal that common variants of HNF1B are associated with risk of prostate and endometrial cancer.