Microdissection Methods Utilizing Single-Cell Subtype Analysis and the Impact on Precision Medicine.

Improving the utilization of tumor tissue from diagnostic biopsies is an unmet medical need. This is especially relevant today in the rapidly evolving precision oncology field where tumor genotyping is often essential for the indication of many advanced and targeted therapies. National Comprehensive Cancer Network (NCCN) guidelines now mandate molecular testing for clinically actionable targets in certain malignancies. Utilizing advanced stage lung cancer as an example, an improved genotyping approach for solid tumors is possible. The strategy involves optimization of the microdissection process and analysis of a large number of identical target cells from formalin-fixed paraffin-embedded (FFPE) specimens sharing similar characteristics, in other words, single-cell subtype analysis. The shared characteristics can include immunostaining status, cell phenotype, and/or spatial location within a histological section. Synergy between microdissection and droplet digital PCR (ddPCR) enhances the molecular analysis. We demonstrate here a methodology that illustrates genotyping of a solid tumor from a small tissue biopsy sample in a time- and cost-efficient manner, using immunostain targeting as an example.

Expansion of Human Papillomavirus-Specific T Cells in Periphery and Cervix in a Therapeutic Vaccine Recipient Whose Cervical High-Grade Squamous Intraepithelial Lesion Regressed.

Advances in high-throughput sequencing have revolutionized the manner with which we can study T cell responses. We describe a woman who received a human papillomavirus (HPV) therapeutic vaccine called PepCan, and experienced complete resolution of her cervical high-grade squamous intraepithelial lesion. By performing bulk T cell receptor (TCR) ß deep sequencing of peripheral blood mononuclear cells before and after 4 vaccinations, 70 putatively vaccine-specific clonotypes were identified for being significantly increased using a beta-binomial model. In order to verify the vaccine-specificity of these clonotypes, T cells with specificity to a region, HPV 16 E6 91-115, previously identified to be vaccine-induced using an interferon-γ enzyme-linked immunospot assay, were sorted and analyzed using single-cell RNA-seq and TCR sequencing. HPV specificity in 60 of the 70 clonotypes identified to be vaccine-specific was demonstrated. TCR ß bulk sequencing of the cervical liquid-based cytology samples and cervical formalin-fixed paraffin-embedded samples before and after 4 vaccinations demonstrated the presence of these HPV-specific T cells in the cervix. Combining traditional and cutting-edge immunomonitoring techniques enabled us to demonstrate expansion of HPV-antigen specific T cells not only in the periphery but also in the cervix. Such an approach should be useful as a novel approach to assess vaccine-specific responses in various anatomical areas.

PHF19 inhibition as a therapeutic target in multiple myeloma.

Epigenetic deregulation is increasingly recognized as a contributing pathological factor in multiple myeloma (MM). In particular tri-methylation of H3 lysine 27 (H3K27me3), which is catalyzed by PHD finger protein 19 (PHF19), a subunit of the Polycomb Repressive Complex 2 (PRC2), has recently shown to be a crucial mediator of MM tumorigenicity. Overexpression of PHF19 in MM has been associated with worse clinical outcome. Yet, while there is mounting evidence that PHF19 overexpression plays a crucial role in MM carcinogenesis downstream mechanisms remain to be elucidated. In the current study we use a functional knock down (KD) of PHF19 to investigate the biological role of PHF19 and show that PHF19KD leads to decreased tumor growth in vitro and in vivo. Expression of major cancer players such as bcl2, myc and EGR1 were decreased upon PHF19KD further underscoring the role of PHF19 in MM biology. Additionally, our results highlighted the prognostic impact of PHF19 overexpression, which was significantly associated with worse survival. Overall, our study underscores the premise that targeting the PHF19-PRC2 complex would open up avenues for novel MM therapies.

Exogenous phosphatidic acid reduces acetaminophen-induced liver injury in mice by activating hepatic interleukin-6 signaling through inter-organ crosstalk.

We previously demonstrated that endogenous phosphatidic acid (PA) promotes liver regeneration after acetaminophen (APAP) hepatotoxicity. Here, we hypothesized that exogenous PA is also beneficial. To test that, we treated mice with a toxic APAP dose at 0 h, followed by PA or vehicle (Veh) post-treatment. We then collected blood and liver at 6, 24, and 52 h. Post-treatment with PA 2 h after APAP protected against liver injury at 6 h, and the combination of PA and N-acetyl-l-cysteine (NAC) reduced injury more than NAC alone. Interestingly, PA did not affect canonical mechanisms of APAP toxicity. Instead, transcriptomics revealed that PA activated interleukin-6 (IL-6) signaling in the liver. Consistent with that, serum IL-6 and hepatic signal transducer and activator of transcription 3 (Stat3) phosphorylation increased in PA-treated mice. Furthermore, PA failed to protect against APAP in IL-6-deficient animals. Interestingly, IL-6 expression increased 18-fold in adipose tissue after PA, indicating that adipose is a source of PA-induced circulating IL-6. Surprisingly, however, exogenous PA did not alter regeneration, despite the importance of endogenous PA in liver repair, possibly due to its short half-life. These data demonstrate that exogenous PA is also beneficial in APAP toxicity and reinforce the protective effects of IL-6 in this model.

A meta-analysis of genome-wide association studies of multiple myeloma among men and women of African ancestry.

Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10-6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10-12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

Author Correction: Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma.

The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma.

Genome-wide association studies (GWAS) have transformed our understanding of susceptibility to multiple myeloma (MM), but much of the heritability remains unexplained. We report a new GWAS, a meta-analysis with previous GWAS and a replication series, totalling 9974 MM cases and 247,556 controls of European ancestry. Collectively, these data provide evidence for six new MM risk loci, bringing the total number to 23. Integration of information from gene expression, epigenetic profiling and in situ Hi-C data for the 23 risk loci implicate disruption of developmental transcriptional regulators as a basis of MM susceptibility, compatible with altered B-cell differentiation as a key mechanism. Dysregulation of autophagy/apoptosis and cell cycle signalling feature as recurrently perturbed pathways. Our findings provide further insight into the biological basis of MM.

Detection of Cross-Sample Contamination in Multiple Myeloma Samples and Sequencing Data.

The increasing applicability and sensitivity of next generation sequencing methods exacerbate one of the main issues in the molecular biology laboratory, namely cross-sample contamination. This type of contamination, which could massively increase the rate of false-positive calls in sequencing experiments, can originate at each step during the processing of multiple myeloma samples, such as CD138-selection of tumor cells, RNA and DNA isolation or the processing of sequencing libraries. Here we describe a Droplet Digital PCR (ddPCR) method and a simple bioinformatic solution for the detection of contamination in patient's samples and derived sequencing data, which are based on the same principle: detection of alternative alleles for single-nucleotide polymorphisms (SNPs) that are homozygous according to the control (germ line) sample.

Kinase domain activation through gene rearrangement in multiple myeloma.

Chromosomal rearrangements that result in oncogenic kinase activation are present in many solid and hematological malignancies, but none have been reported in multiple myeloma (MM). Here we analyzed 1421 samples from 958 myeloma patients using a targeted assay and detected fusion genes in 1.5% of patients. These fusion genes were in-frame and the majority of them contained kinase domains from either receptor tyrosine kinases (ALK, ROS1, NTRK3, and FGFR1) or cytoplasmic kinases (BRAF, MAP3K14, and MAPK14), which would result in the activation of MEK/ERK, NF-κB, or inflammatory signaling pathways. Fusion genes were present in smoldering MM, newly diagnosed MM, and relapse patient samples indicating they are not solely late events. Most fusion genes were subclonal in nature, but one EML4-ALK fusion was clonal indicating it is a driver of disease pathogenesis. Samples with fusions of receptor tyrosine kinases were not found in conjunction with clonal Ras/Raf mutations indicating a parallel mechanism of MEK/ERK pathway activation. Fusion genes involving MAP3K14 (NIK), which regulates the NF-κB pathway, were detected as were t(14;17) rearrangements involving NIK in 2% of MM samples. Activation of kinases in myeloma through rearrangements presents an opportunity to use treatments existing in other cancers.

The multiple myeloma risk allele at 5q15 lowers ELL2 expression and increases ribosomal gene expression.

Recently, we identified ELL2 as a susceptibility gene for multiple myeloma (MM). To understand its mechanism of action, we performed expression quantitative trait locus analysis in CD138+ plasma cells from 1630 MM patients from four populations. We show that the MM risk allele lowers ELL2 expression in these cells (Pcombined = 2.5 × 10-27; ßcombined = -0.24 SD), but not in peripheral blood or other tissues. Consistent with this, several variants representing the MM risk allele map to regulatory genomic regions, and three yield reduced transcriptional activity in plasmocytoma cell lines. One of these (rs3777189-C) co-locates with the best-supported lead variants for ELL2 expression and MM risk, and reduces binding of MAFF/G/K family transcription factors. Moreover, further analysis reveals that the MM risk allele associates with upregulation of gene sets related to ribosome biogenesis, and knockout/knockdown and rescue experiments in plasmocytoma cell lines support a cause-effect relationship. Our results provide mechanistic insight into MM predisposition.

Host genetic susceptibility to Clostridium difficile infections in patients undergoing autologous stem cell transplantation: a genome-wide association study.

BACKGROUND: Clostridium difficile infection (CDI) is the most common hospital-acquired infection. Unfortunately, genes that identify CDI-susceptible patients have not been well described. We performed a genome-wide association study (GWAS) to determine genetic variants associated with the development of CDI. METHODS: A cohort study of Caucasian patients undergoing autologous stem cell transplantation for multiple myeloma was performed. Patients were genotyped using Illumina® Whole Genome Genotyping Infinium chemistry. We then compared CDI-positive to CDI-negative patients using logistic regression for baseline clinical factors and false discovery rate (FDR) for genetic factors [single nucleotide polymorphisms (SNPs)]. SNPs associated with CDI at FDR of p < 0.01 were then incorporated into a logistic regression model combining clinical and genetic factors. RESULTS: Of the 646 patients analyzed (59.7% male), 57 patients were tested CDI positive (cases) and were compared to 589 patients who were tested negative (controls). Hemoglobin, albumin, and hematocrit were lower for cases (p < 0.05). Eight SNPs on five genes (FLJ16171, GORASP2, RLBP1L1, ASPH, ATP7B) were associated with CDI at FDR p < 0.01. In the combined clinical and genetic model, low albumin and three genes RLBP1L1, ASPH, and ATP7B were associated with CDI. CONCLUSION: Low serum albumin and genes RLBP1L1 and ASPH located on chromosome 8 and ATP7B on chromosome 13 were associated with CDI. Of particular interest is ATP7B given its copper modulatory role and the sporicidal properties of copper against Clostridium difficile.

Genetic correlation between multiple myeloma and chronic lymphocytic leukaemia provides evidence for shared aetiology.

The clustering of different types of B-cell malignancies in families raises the possibility of shared aetiology. To examine this, we performed cross-trait linkage disequilibrium (LD)-score regression of multiple myeloma (MM) and chronic lymphocytic leukaemia (CLL) genome-wide association study (GWAS) data sets, totalling 11,734 cases and 29,468 controls. A significant genetic correlation between these two B-cell malignancies was shown (Rg = 0.4, P = 0.0046). Furthermore, four of the 45 known CLL risk loci were shown to associate with MM risk and five of the 23 known MM risk loci associate with CLL risk. By integrating eQTL, Hi-C and ChIP-seq data, we show that these pleiotropic risk loci are enriched for B-cell regulatory elements and implicate B-cell developmental genes. These data identify shared biological pathways influencing the development of CLL and, MM and further our understanding of the aetiological basis of these B-cell malignancies.

Clonal selection and double-hit events involving tumor suppressor genes underlie relapse in myeloma.

To elucidate the mechanisms underlying relapse from chemotherapy in multiple myeloma, we performed a longitudinal study of 33 patients entered into Total Therapy protocols investigating them using gene expression profiling, high-resolution copy number arrays, and whole-exome sequencing. The study illustrates the mechanistic importance of acquired mutations in known myeloma driver genes and the critical nature of biallelic inactivation events affecting tumor suppressor genes, especially TP53, the end result being resistance to apoptosis and increased proliferation rates, which drive relapse by Darwinian-type clonal evolution. The number of copy number aberration changes and biallelic inactivation of tumor suppressor genes was increased in GEP70 high risk, consistent with genomic instability being a key feature of high risk. In conclusion, the study highlights the impact of acquired genetic events, which enhance the evolutionary fitness level of myeloma-propagating cells to survive multiagent chemotherapy and to result in relapse.

Genome-wide association study identifies multiple susceptibility loci for multiple myeloma.

Multiple myeloma (MM) is a plasma cell malignancy with a significant heritable basis. Genome-wide association studies have transformed our understanding of MM predisposition, but individual studies have had limited power to discover risk loci. Here we perform a meta-analysis of these GWAS, add a new GWAS and perform replication analyses resulting in 9,866 cases and 239,188 controls. We confirm all nine known risk loci and discover eight new loci at 6p22.3 (rs34229995, P=1.31 × 10(-8)), 6q21 (rs9372120, P=9.09 × 10(-15)), 7q36.1 (rs7781265, P=9.71 × 10(-9)), 8q24.21 (rs1948915, P=4.20 × 10(-11)), 9p21.3 (rs2811710, P=1.72 × 10(-13)), 10p12.1 (rs2790457, P=1.77 × 10(-8)), 16q23.1 (rs7193541, P=5.00 × 10(-12)) and 20q13.13 (rs6066835, P=1.36 × 10(-13)), which localize in or near to JARID2, ATG5, SMARCD3, CCAT1, CDKN2A, WAC, RFWD3 and PREX1. These findings provide additional support for a polygenic model of MM and insight into the biological basis of tumour development.

Genome-wide association study identifies variation at 6q25.1 associated with survival in multiple myeloma.

Survival following a diagnosis of multiple myeloma (MM) varies between patients and some of these differences may be a consequence of inherited genetic variation. In this study, to identify genetic markers associated with MM overall survival (MM-OS), we conduct a meta-analysis of four patient series of European ancestry, totalling 3,256 patients with 1,200 MM-associated deaths. Each series is genotyped for ∼600,000 single nucleotide polymorphisms across the genome; genotypes for six million common variants are imputed using 1000 Genomes Project and UK10K as the reference. The association between genotype and OS is assessed by Cox proportional hazards model adjusting for age, sex, International staging system and treatment. We identify a locus at 6q25.1 marked by rs12374648 associated with MM-OS (hazard ratio=1.34, 95% confidence interval=1.22-1.48, P=4.69 × 10(-9)). Our findings have potential clinical implications since they demonstrate that inherited genotypes can provide prognostic information in addition to conventional tumor acquired prognostic factors.

GWAS of 972 autologous stem cell recipients with multiple myeloma identifies 11 genetic variants associated with chemotherapy-induced oral mucositis.

PURPOSE: High-dose chemotherapy and autologous stem cell transplant (ASCT) to treat multiple myeloma (MM) and other cancers carries the risk of oral mucositis (OM) with sequelae including impaired nutritional and fluid intake, pain, and infectious complications. As a result of these problems, cancer treatment may have to be interrupted or delayed. In this study, we looked beyond OM's known risk factors of renal function and melphalan dose with a genome-wide association study (GWAS) to evaluate whether genetic variants in conjunction with clinical risk factors influence predisposition for OM. METHODS: Genotyping was performed using Illumina HumanOmni1-Quad v1.0 BeadChip and further assessed for data quality. We tested 892,589 germline single-nucleotide polymorphisms (SNPs) for association with OM among 972 Caucasian patients treated with high-dose melphalan and ASCT in Total Therapy clinical trials (TT2, TT3, TT4) for newly diagnosed MM. Statistical analyses included t tests, stepwise regression modeling, and logistic regression modeling to find baseline clinical factors and genotypes associated with OM. RESULTS: We found that 353 (36.3 %) patients had grades 2-4 OM. Type of treatment protocol, baseline estimated glomerular filtration rate, and melphalan dose along with baseline serum albumin and female gender predicted 43.6 % of grades 2-4 OM cases. Eleven SNPs located in or near matrix metalloproteinase 13, JPH3, DHRS7C, CEP192, CPEB1/LINC00692, FBN2, ALDH1A1, and DMRTA1/FLJ35282 were associated with grades 2-4 OM. The addition of these SNPs increased sensitivity in detecting grades 2-4 OM cases to 52 %. CONCLUSIONS: These SNPs may be important for their roles in inflammatory pathways, epithelial healing, and chemotherapy detoxification.

Interleukin-6 receptor polymorphism is prevalent in HIV-negative Castleman Disease and is associated with increased soluble interleukin-6 receptor levels.

Multicentric Castleman Disease is largely driven by increased signaling in the pathway for the plasma cell growth factor interleukin-6. We hypothesized that interleukin-6/interleukin-6 receptor/gp130 polymorphisms contribute to increased interleukin-6 and/or other components of the interleukin-6 signaling pathway in HIV-negative Castleman Disease patients. The study group was composed of 58 patients and 50 healthy donors of a similar racial/ethnic profile. Of seven polymorphisms chosen for analysis, we observed an increased frequency between patients and controls of the minor allele of interleukin-6 receptor polymorphism rs4537545, which is in linkage disequilibrium with interleukin-6 receptor polymorphism rs2228145. Further, individuals possessing at least one copy of the minor allele of either polymorphism expressed higher levels of soluble interleukin-6 receptor. These elevated interleukin-6 receptor levels may contribute to increased interleukin-6 activity through the trans-signaling pathway. These data suggest that interleukin-6 receptor polymorphism may be a contributing factor in Castleman Disease, and further research is warranted.

Prediction of cytogenetic abnormalities with gene expression profiles.

Cytogenetic abnormalities are important clinical parameters in various types of cancer, including multiple myeloma. We developed a model to predict cytogenetic abnormalities in patients with multiple myeloma using gene expression profiling and validated it by different cytogenetic techniques. The model has an accuracy rate up to 0.89. These results provide proof of concept for the hypothesis that gene expression profiling is a superior genomic method for clinical molecular diagnosis and/or prognosis.