Citations

AbstractElevated blood levels of C‐reactive protein (CRP) have been linked to colorectal cancer (CRC) survival. We evaluated genetic variants associated with CRP levels and their interactions with sex and lifestyle factors in association with CRC‐specific mortality. Our study included 16 142 CRC cases from the International Survival Analysis in Colorectal Cancer Consortium. We identified 618 common single nucleotide polymorphisms (SNPs) associated with CRP levels from the NHGRI‐EBI GWAS Catalog. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations between SNPs and CRC‐specific mortality adjusting for age, sex, genotyping platform/study and principal components. We investigated their interactions with sex and lifestyle factors using likelihood ratio tests. Of 5472 (33.9%) deaths accrued over up to 10 years of follow‐up, 3547 (64.8%) were due to CRC. No variants were associated with CRC‐specific mortality after multiple comparison correction. We observed strong evidence of interaction between variant rs1933736 at FRK gene and sex in relation to CRC‐specific mortality (corrected Pinteraction = .0004); women had higher CRC‐specific mortality associated with the minor allele (HR = 1.11, 95% CI = 1.04‐1.19) whereas an inverse association was observed for men (HR = 0.88, 95% CI = 0.82‐0.94). There was no evidence of interactions between CRP‐associated SNPs and alcohol, obesity or smoking. Our study observed a significant interaction between sex and a CRP‐associated variant in relation to CRC‐specific mortality. Future replication of this association and functional annotation of the variant are needed.

Gastric cancer is a leading cause of death from cancer globally. Gastric cancer is classified into intestinal, diffuse and indeterminate subtypes based on histology according to the Laurén classification. The intestinal and diffuse subtypes, although different in histology, demographics and outcomes, are still treated in the same fashion. This study was designed to discover proteomic signatures of diffuse and intestinal subtypes. Mass spectrometry-based proteomics using tandem mass tags (TMT)-based multiplexed analysis was used to identify proteins in tumor tissues from patients with diffuse or intestinal gastric cancer with adjacent normal tissue control. A total of 7448 or 4846 proteins were identified from intestinal or diffuse subtype, respectively. This quantitative mass spectrometric analysis defined a proteomic signature of differential expression across the two subtypes, which included gremlin1 (GREM1), bcl-2-associated athanogene 2 (BAG2), olfactomedin 4 (OLFM4), thyroid hormone receptor interacting protein 6 (TRIP6) and melanoma-associated antigen 9 (MAGE-A9) proteins. Although GREM1, BAG2, OLFM4, TRIP6 and MAGE-A9 have all been previously implicated in tumor progression and metastasis, they have not been linked to intestinal or diffuse subtypes of gastric cancer. Using immunohistochemical labelling of a tissue microarray comprising of 124 cases of gastric cancer, we validated the proteomic signature obtained by mass spectrometry in the discovery cohort. Our findings should help investigate the pathogenesis of these gastric cancer subtypes and potentially lead to strategies for early diagnosis and treatment.

Abstract Introduction: Treatment resistance remains a challenge that most patients (pts) with MM will encounter in their disease course. With each subsequent line of therapy (LOT), pt outcomes and health-related quality of life (HRQoL) worsen. Pts with MM who are refractory to immunomodulatory drugs, proteasome inhibitors (PIs), and anti-CD38 antibodies (triple-class refractory; TCR) have a poor prognosis and the holistic burden is not well understood. To capture these features, the ongoing prospective Connect ® MM Disease Registry was used to report treatment patterns and outcomes in pts with TCR MM. Methods: Data from September 28, 2009 to February 4, 2021 were used. Eligible pts were ≥18 years of age at first documented diagnosis of MM, which became TCR during their disease course. MM was defined as refractory to therapies based on the International Myeloma Working Group Criteria. Index date was defined as first record of TCR during the disease course. Data analyzed included pt characteristics, treatment patterns pre- and post-index, overall survival (OS), healthcare resource utilization (HCRU), and HRQoL. General HRQoL was captured by EQ-5D-3L utility index (range −0.11-1, higher score indicated better HRQoL), EQ-5D visual analog scale (VAS) score (range 0-100, "worst imaginable" to "best imaginable" health status), and FACT-G total score (range 0-108). Disease-specific HRQoL was measured by FACT-MM total score (range 0-164), FACT-MM Trial Outcome Index (TOI) (range 0-112), and the Brief Pain Inventory (BPI) average pain item (range 0-10, "no pain" to "worst pain you can imagine"). Higher scores indicated better HRQoL for all FACT-related index scores. Cohort-level clinically meaningful change in HRQoL during post-index year 1 was defined as 0.08 for the EQ-5D utility index, 7 for the EQ-5D VAS, and 6-8 points for the FACT-G total score. Validated thresholds were unavailable for other index scores. All statistical analyses were descriptive. Results: This analysis included 240 pts identified from the Registry. Mean age at index date was 68.1 (standard deviation [SD] 10.4) years. Mean time from initial MM diagnosis was 64.1 (SD 26.9) months. 63.3% of pts had prior stem cell transplantation. Mean number of prior LOTs was 4 (SD 1.7). 64.6% of pts had received a subsequent MM LOT since index date. Median follow-up time post-index date was 4.6 months. Treatment pattern analysis of post-index treated pts (Table A) revealed that retreatment with an immunomodulatory drug, PI, or anti-CD38 agent post-index date was common, led by carfilzomib (47.1%) and pomalidomide (40.0%). However, no therapeutic combination was preferred in this pt population. Regarding their index therapy (first post-index LOT), 70.3% and 22.6% were on triplet and quadruplet combination therapy; 3.2% initiated belantamab mafodotin, selinexor, melflufen, and/or idecabtagene vicleucel; mean duration of treatment was 5.6 (SD 6.1) months. For all pts, median OS was 8.9 months; median OS for those who received < 4 prior LOTs (43.8%) versus those who received 4 or more prior LOTs (56.2%) was 10.0 and 8.0 months, respectively. Regarding HCRU during the post-index follow-up, all-cause and MM-related hospitalizations were observed in 49.6% and 23.8% of all eligible pts, respectively. Among these pts, annualized mean number of all-cause/MM-related hospitalization and length of hospital stay were estimated as 8.5 (SD 18.2)/11.0 (SD 25.2) and 64.0 days (SD 80.0)/ 69.2 days (SD 83.7), respectively. Analysis of HRQoL showed a numerical decline in HRQoL relative to index during the 1-year post-index period across all studied HRQoL instruments. There was a clinically meaningful decline in HRQoL from baseline following the index date based on the EQ-5D utility index, EQ-5D VAS, and FACT-G total score (Table B). Conclusion: Pts with TCR MM experienced poor survival, substantial hospitalizations, and a clinically meaningful decline in HRQoL. 35.4% of pts did not receive any new LOTs since the disease became TCR. Among those who did receive subsequent LOTs, re-treatment with an immunomodulatory drug, PI, or anti-CD38 antibody therapy occurred, showing a lack of novel treatment options. This study suggests novel tolerable and efficacious therapeutic agents are needed to address the burden of illness in pts with MM. Figure 1 Figure 1. Disclosures Tang: Bristol-Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Hari: Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Celgene-BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Adaptive Biotech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Karyopharm: Consultancy; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Millenium: Membership on an entity's Board of Directors or advisory committees, Research Funding. Ramasamy: Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Weisel: Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Karyopharm: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Consultancy; Novartis: Honoraria; Pfizer: Honoraria. Joshi: Bristol Myers Squibb: Current Employment. Liu: Bristol Myers Squibb: Current Employment. Che: Bristol Myers Squibb: Current Employment. Hernandez: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Abonour: Jensen: Honoraria, Research Funding; Celgene-BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Honoraria, Research Funding; Takeda: Research Funding. Hardin: Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Rifkin: Sanofi: Membership on an entity's Board of Directors or advisory committees; McKesson: Current Employment, Current equity holder in publicly-traded company; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Fresenius-Kabi: Membership on an entity's Board of Directors or advisory committees; Coherus: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb (Celgene): Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Ailawadhi: BeiGene, Ltd.: Consultancy; Bristol Myers Squibb: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Amgen: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Ascentage: Research Funding; Medimmune: Research Funding; Cellectar: Research Funding; Xencor: Research Funding; GSK: Consultancy, Research Funding; Takeda: Consultancy; Genentech: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Sanofi: Consultancy; Oncopeptides: Consultancy. Lee: Legend Biotech: Consultancy; Sanofi: Consultancy; Oncopetides: Consultancy; Bristol Myers Squibb: Consultancy; Amgen: Consultancy, Research Funding; Celgene: Consultancy; Janssen: Consultancy, Research Funding; Takeda Pharmaceuticals: Consultancy, Research Funding; Karyopharm: Consultancy; Regeneron: Research Funding; Genentech: Consultancy; GlaxoSmithKline: Consultancy, Research Funding. Terebelo: Pharmacylics: Speakers Bureau; Celgene-BMS: Consultancy; Takeda: Speakers Bureau; Janssen: Speakers Bureau. Durie: Amgen, Celgene/Bristol-Myers Squibb, Janssen, and Takeda: Consultancy; Amgen: Other: fees from non-CME/CE services . Narang: Bristol Myers Squibb: Consultancy; TG Pharma: Consultancy. Toomey: Bristol Myers Squibb: Consultancy. Gasparetto: Oncopeptide: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy; Sanofi: Consultancy, Honoraria, Speakers Bureau; Karyopharm: Consultancy, Honoraria, Speakers Bureau; Gsk: Consultancy, Honoraria, Speakers Bureau. Wagner: Celgene-BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Athenex Inc: Consultancy; Eli Lilly, Johnson & Johnson: Other: Spouse, previously held individual stocks;. Jagannath: Janssen Pharmaceuticals: Consultancy; Bristol Myers Squibb: Consultancy; Karyopharm Therapeutics: Consultancy; Legend Biotech: Consultancy; Sanofi: Consultancy; Takeda: Consultancy.

Abstract Background Myocarditis following coronavirus disease 2019 (COVID-19) mRNA vaccines (Pfizer-BioNTech and Moderna) has been increasingly reported. Incidence rates in the general population are lacking, with pericarditis rather than myocarditis diagnostic codes being used to estimate background rates. This comparison is critical for balancing the risk of vaccination with the risk of no vaccination. Methods A retrospective case series was performed using the Mayo Clinic COVID-19 Vaccine Registry. We measured the incidence rate ratio (IRR) for myocarditis temporally related to COVID-19 mRNA vaccination compared with myocarditis in a comparable population from 2016 through 2020. Clinical characteristics and outcomes of the affected patients were collected. A total of 21 individuals were identified, but ultimately 7 patients met the inclusion criteria for vaccine-associated myocarditis. Results The overall IRR of COVID-19–related myocarditis was 4.18 (95% confidence interval [CI], 1.63–8.98), which was entirely attributable to an increased IRR among adult males (IRR, 6.69; 95% CI, 2.35–15.52) compared with females (IRR 1.41; 95% CI, .03–8.45). All cases occurred within 2 weeks of a dose of the COVID-19 mRNA vaccine, with the majority occurring within 3 days (range, 1–13) following the second dose (6 of 7 patients, 86%). Overall, cases were mild, and all patients survived. Conclusions Myocarditis is a rare adverse event associated with COVID-19 mRNA vaccines. It occurs in adult males with significantly higher incidence than in the background population. Recurrence of myocarditis after a subsequent mRNA vaccine dose is not known at this time.

AbstractGermline predisposition syndromes (GPS) result from constitutional aberrations in tumor suppressive and homeostatic genes, increasing risk for neoplasia in affected kindred. In this study, we present clinical and genomic data on 144 Mayo Clinic patients with GPS; 59 evaluated prospectively using an algorithm‐based diagnostic approach in the setting of a dedicated GPS/ inherited bone marrow failure syndrome (IBMFS) clinic. Seventy‐two (50%) patients had IBMFS (telomere biology disorders‐32,Fanconi anemia‐18, Diamond Blackfan Anemia – 11, congenital neutropenia–5, Schwachman‐Diamond Syndrome‐5 and Bloom Syndrome‐1), 27 (19%) had GPS with antecedent thrombocytopenia (RUNX1‐FPD‐15, ANKRD26‐6, ETV6‐2, GATA1‐1, MPL‐3), 28 (19%) had GPS without antecedent thrombocytopenia (GATA2 haploinsufficiency‐16, DDX41‐10, CBL‐1 and CEBPA‐1) and 17 (12%) had general cancer predisposition syndromes (ataxia telangiectasia‐7, heterozygous ATM variants‐3, CHEK2‐2, TP53‐2, CDK2NA‐1, NF1‐1 and Nijmegen Breakage Syndrome‐1). Homozygous and heterozygous ATM pathogenic variants were exclusively associated with lymphoproliferative disorders (LPD), while DDX41 GPS was associated with LPD and myeloid neoplasms. The use of somatic NGS‐testing identified clonal evolution in GPS patients, with ASXL1, RAS pathway genes, SRSF2 and TET2 being most frequently mutated. Fifty‐two (91%) of 59 prospectively identified GPS patients had a change in their management approach, including additional GPS‐related screening in 42 (71%), referral for allogenic HSCT workup and screening of related donors in 16 (27%), medication initiation and selection of specific conditioning regimens in 14 (24%), and genetic counseling with specific intent of fertility preservation and preconceptual counseling in 10 (17%) patients; highlighting the importance of dedicated GPS screening, detection and management programs for patients with hematological neoplasms.

Abstract Eleusine coracana (L.) Gaertn (E. coracana) is one of the highest consuming food crops in Asia and Africa. E. coracana is a plant with several medicinal values including anti-ulcerative, anti-diabetic, anti-viral and anti-cancer properties. However, the anti-inflammatory property of E. coracana remains to be elucidated. Therefore, the objective of present study was to investigate the potential in isolated molecule from E. coracana via a combination of in vitro, in vivo and in silico methods. In this study we have isolated, purified and characterized an anti-inflammatory molecule from E coracana bran extract known as syringol. Purification of syringol was accomplished by combination of GC-MS and RP-HPLC techniques. Syringol significantly inhibited the enzyme activity of sPLA2 (IC50 = 3 µg) and 5-LOX (IC50 = 0.325 µg) in vitro. The inhibition is independent of substrate concentration, calcium ion concentration and was irreversible. Syringol interacts with purified sPLA2 enzymes as evidenced by fluorescence and molecular docking studies. Further, the syringol molecule dose dependently inhibited the development of sPLA2 and carrageenan induced edema. Furthermore, syringol decreases the expression of cPLA2, COX-2, IκBα, p38 and MPO in edematous tissues as demonstrated by western blots. These studies revealed that syringol isolated from E coracana bran may develop as a potent anti-inflammatory molecule.

Introduction: Heart Disease and Stroke Statistics_2014 Update suggests more than 424,000 people suffer out of hospital cardiac arrest (OHCA) in the United States. Hypothesis: We assessed seasonal variation in OHCA from a large national hospitalisation database in the past decade. Methods: The Nationwide Inpatient Sample database was used to estimate the annual number of hospitalisations with from 2000-2011. Identification of out of hospital cardiac arrest related hospitalisations was based on the designation of the International Classification of Diseases (9th Edition) Clinical Modification (ICD-9-CM) diagnosis code 427.5 (OHCA) as the principal discharge diagnosis. The frequency of hospitalisation for each month cumulative over 11 years was calculated and divided by number of days in that month to obtain the mean hospitalisations per day for each month. All calculations were carried out using the weighted estimates approximating nationwide population estimates. Results: An estimated 93,209 hospitalisations with primary diagnosis of OHCA occurred in the United States from the beginning of the calendar year 2000 to the end of the calendar year 2011. The number of hospitalisations per day in each month is shown in Figure 1.The number of hospitalisation was maximum in the winter months and minimum in summer months. Specifically, the mean number of hospitalisation each day (averaged over 11 years) was least in August (242). There was a rising trend from August to January. The average number of hospitalisation was highest in January (310); thereafter, the hospitalisation rate dropped to a nadir in August. There was however no seasonal pattern in inhospital mortality. Conclusions: We identified for the first time in United States an impressive pattern of seasonal variation in hospitalisations for OHCA. Further efforts must be made to identify triggers and methods to prevent OHCA and reduce its burden on health care system.

Introduction: Big data techniques offer a novel opportunity to characterize individuals with extreme phenotypes. In this context, we aimed to describe the prevalence of classical Fredrickson-Levy dyslipidemia phenotypes at the extremes of HDL-C levels in a cross-sectional big data study. Methods: We examined 848,801 U.S. adults and children from the Very Large Database of Lipids 1.0 who were referred for lipoprotein testing from 2009 to 2011. We categorized patients into HDL-C percentile categories (<0.1th, 0.1th to 99th to 99.9th, and >99.9th). We examined the prevalence of Fredrickson-Levy dyslipidemia phenotypes (I, IIa, IIb, III, IV and V) within these categories. We identified those who did not meet criteria for any classical dyslipidemia phenotype as the continuum group. Results: Type I and V were mostly present at extremely low HDL-C levels. Type IIa was more prevalent in high vs. low HDL-C levels. Type III was 2-fold more prevalent in extremely low vs. high HDL-C levels. Type IV was the most prevalent classical dyslipidemia phenotype in our population, and was the most frequent at low HDL-C percentiles. About 50% of the extremely low and 90% of the extremely high HDL-C levels were classified into the continuum group. Conclusion: In our cross-sectional big data analysis, there was a significantly higher prevalence of most classical dyslipidemia phenotypes at extremely low HDL-C compared with extremely high HDL-C levels. Only types I and V were more prevalent in extreme groups than general population. To some extent, very low HDL-C levels may be determined by inheritable, highly atherogenic dyslipidemias.