Citations

Immune checkpoint inhibitors (ICIs) and brentuximab vedotin (BV) are novel agents for classic Hodgkin lymphoma, including relapse after autologous stem cell transplant (ASCT). However, their impact on survival post-ASCT relapse, in comparison with conventional therapy, is less known due to the lack of randomized controlled trials. Clinical characteristics and outcomes of 115 patients with relapse (or progression) after ASCT are studied. After a median follow-up of 8.59 years from post-ASCT relapse, the median progression-free survival (PFS) and overall survival (OS) were 0.91 and 5.07 years, respectively. Median lines of therapy after post-ASCT relapse was 2 (range, 1–12). The median PFS was not reached (NR) versus 1.11 versus 0.50 versus 0.85 versus 0.78 years (P = 0.006) and OS was NR versus 7.60 versus 3.08 versus 3.51 versus 3.17 years (P = 0.28) in patients first treated with ICIs versus BV versus investigational agents versus chemotherapy versus radiation therapy (RT). First-line treatment with novel agents (ie, ICIs and BV) was associated with superior outcomes compared with investigational agents and chemotherapy/RT with a median PFS of 1.65 versus 0.50 versus 0.79 years (P = 0.003) and a median OS of 7.60 versus 3.08 versus 3.32 years (P = 0.08). Regardless of lines of therapy, the treatment with ICIs had the most favorable outcome with a median PFS and OS of 3.98 and NR years, respectively. Allogeneic stem cell transplant (allo-SCT) was done in 23 patients (20%), and the median post-allo-SCT PFS and OS were 1.31 and 2.35 years, respectively. In conclusion, survival following post-ASCT relapse improves significantly when patients receive novel agents.

Abstract Low count (LC) MBL is characterized by a circulating population of clonal B-cells and is a precursor state to CLL. Most individuals with LC MBL do not progress to CLL and never come to clinical attention. An active area of research is to identify factors that distinguish those individuals with MBL who progress from those who do not. Currently, 41 single nucleotide polymorphisms (SNPs) are known to be associated with CLL risk, and a portion of these SNPs have also been found to be associated with MBL risk. We hypothesize that these CLL-susceptibility SNPs associated with both MBL and CLL risk are SNPs associated with developing a B-cell clone; whereas the remaining SNPs found not to be associated with MBL risk are associated with progression of the B-cell clone (i.e., progression from MBL to CLL). To test this hypothesis, we evaluated the association of these 41 SNPs with risk of progression to CLL using a case-control study of 1,911 CLL cases and 1,579 individuals with MBL from Mayo Clinic. Individuals with MBL were identified through screening using 8-color flow cytometry assay. Individuals with LC MBL (defined by having a clonal B-cell population with the percent clonal B-cells out of total B-cell count <85%) who had an immunophenotype consistent with CLL were included as controls. CLL cases were obtained through the Mayo Clinic hematology practice. DNA was genotyped from whole blood. We analyzed the 41 CLL susceptibility SNPs with risk of progression to CLL using logistic regression and estimated odds ratio (OR) and 95% confidence interval (CI), adjusting for sex and age. We evaluated the CLL polygenic risk score (CLL-PRS), comprised of a weighted average of the 41 SNPs, with risk of CLL. Out of the 41 established CLL susceptibility SNPs, 15 were associated with CLL progression from MBL to CLL (all P<0.05). Nine of these 15 significant SNPs were not previously found to be associated with risk of MBL. The most significant SNPs were rs9880772 (OR=1.23, CI: 1.11-1.36, P=6.1 × 10−5), rs888096 (OR=1.25, CI: 1.12-1.38, P=3.0 × 10−5), and rs305065 (OR=1.28, CI: 1.14-1.43, P=1.5 × 10−5). One SNP (rs77551289) had a suggestive association (OR=1.21, P=0.069). The remaining 25 SNPs had no evidence of association with progression (ORs ranging between 0.9-1.1 and all P>0.1). The CLL-PRS was also associated with CLL risk (continuous OR = 1.25, CI: 1.15 - 1.35, P = 6.7 × 10−8). In our study accounting for the presence of B-cell clonal population, we identified 15 out of 41 CLL-susceptibility SNPs to be significantly associated with progression from LC MBL to CLL. The remaining 25 non-significant CLL-SNPs were not associated with progression and may instead be associated with development or initiation of the B-cell clone. These findings suggest that the established CLL susceptibility SNPs may play differing role (i.e., development or progression of the clone) in the etiology of CLL. Citation Format: Raphael Mwangi, Geffen Kleinstern, Sara J. Achenbach, Dennis Robinson, Aaron D. Norman, Kari G. Rabe, Janet E. Olson, Neil E. Kay, Rosalie G. Waller, Nicholas J. Boddicker, James R. Cerhan, Esteban Braggio, Sameer A. Parikh, Curtis A. Hanson, Celine M. Vachon, Tait Shanafelt, Susan L. Slager. Genetic variants associated with progression from monoclonal B-cell lymphocytosis (MBL) to chronic lymphocytic leukemia (CLL). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5222.

Abstract Diffuse large B-cell lymphoma (DLBCL) is clinically and biologically heterogenous. Based on gene expression profiling of the tumor, DLBCL is classified into two major molecular subtypes linked to cell-of-origin (COO): germinal center (GCB) and activated B-Cell (ABC). The GCB subtype is characterized by a high prevalence of somatic mutations, particularly in apoptosis genes (e.g., BCL2) which is characteristic of follicular lymphoma (FL, another GCB lymphoma). The development of the validated NanoString gene expression test as well as immunohistochemistry markers that work in formalin-fixed, paraffin-embedded tissue allows for the classification of DLBCL by COO in epidemiological studies. We hypothesized that integration of COO with germline genetics could provide insight into the underlying biology driving this heterogeneity, as well as insight into putative function of germline risk variants. Prior genome wide association studies (GWAS) have identified 7 SNPs in 6 susceptibility loci for DLBCL, including: 2p23.3 (rs79480871 NCOA1), 3q13.33 (rs9831894 CD86), 3p24.1 (rs6773363 EOMES), 6p21.33 (rs2523607 HLA-B), 6p25.3 (rs116446171 EXOC2), and 8q24.21 (rs13255292 and rs4733601 PVT1 and MYC). Two of these loci were also identified in FL GWAS (different lead SNPs): 6p21.33 (rs3130437) and 8q24.21 (rs13254990 PVT1). Additional published FL susceptibility loci include: 3q28 (rs6444305 LPP), 6p21.32 (rs9268839), 11q23.3 (rs4938573 CXCR5), 11q24.3 (rs4937362 ETS1), and 18q21.33 (rs17749561 BCL2). Here we evaluated whether the published DLBCL/FL loci differ by COO molecular subtypes. We evaluated each of the 14 DLBCL/FL SNPs by case-case (GCB vs. nonGCB DLBCL) and polytomous case-control (GCB, nonGCB, and FL vs. controls) analyses. DLBCL cases were classified into GCB vs. nonGCB based on best available data from NanoString, RNAseq, followed by the Hans algorithm. A total of 778 DLBCL cases (470 GCB and 308 nonGCB), 1,050 FL cases, and 1,383 controls were analyzed. Odds ratios (OR) based on ordinal encoding of each SNP and 95% CI were calculated for each of the comparison groups. The ORs for four GWAS SNPs were significantly elevated in GCB vs. nonGCB DLBCL as well as in FL; two were FL GWAS SNPs from the HLA region (6p21.32 and 6p21.33) and the other two (BCL2 and ETS1) are important in the germinal center program. In contrast, one SNP (EXOC2) was significantly elevated in nonGCB-DLBCL and was not associated with GCB-DLBCL or FL; this SNP is also near IRF4 (MUM1), a gene important in the ABC program. For the remaining SNPs, there were suggestive associations for GCB-DLBCL and FL versus nonGCB DLBCL (CD86, CXCR5); nonGCB-DLBCL vs. GCB-DLBCL and FL (NCOA1, PVT1); and associations that showed no pattern with COO (EOMES, LPP, HLA-B and MYC). These findings provide insight into the shared pathogenesis of FL and GCB-DLBCL to inform etiologic mechanisms and risk assessment. Citation Format: Rosalie Griffin Waller, Dennis P. Robinson, Anne J. Novak, Lisa M. Rimsza, Kerstin Wenzl, Rebecca L. King, Andrew L. Feldman, Matthew J. Maurer, Grzegorz S. Nowakowski, Brian K. Link, Thomas M. Habermann, Susan L. Slager, James R. Cerhan. Etiologic heterogeneity of genetic risk for DLBCL cell-of origin molecular subtypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1181.

Abstract TP53 aberrations, including mutations and deletion of 17p13, are important adverse prognostic markers in chronic lymphocytic leukemia (CLL) but are less studied in high count monoclonal B-cell lymphocytosis (HCMBL), an asymptomatic pre-malignant stage of CLL. Here we estimated the prevalence and impact of TP53 aberrations in 1,230 newly diagnosed treatment-naïve individuals (849 CLL, 381 HCMBL). We defined TP53 state as: wild-type (no TP53 mutations and normal 17p), single-hit (del(17p) or one TP53 mutation), or multi-hit (TP53 mutation and del(17p), TP53 mutation and loss of heterozygosity, or multiple TP53 mutations). Cox regression was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for time to first treatment and overall survival by TP53 state. We found 64 (7.5%) CLL patients and 17 (4.5%) HCMBL individuals had TP53 mutations with variant allele fraction >10%. Del(17p) was present in 58 (6.8%) of CLL and 11 (2.9%) of HCMBL cases. Most individuals had wild-type (N=1,128, 91.7%) TP53 state, followed by multi-hit (N=55, 4.5%) and then single-hit (N=47, 3.8%) TP53 state. The risk of shorter time to therapy and death increased with the number of TP53 abnormalities. Compared to wild-type patients, multi-hit patients had 3-fold and single-hit patients had 1.5-fold increased risk of requiring therapy. Multi-hit patients also had 2.9-fold increased risk of death compared to wild-type. These results remained stable after accounting for other known poor prognostic factors. Both TP53 mutations and del(17p) may provide important prognostic information for HCMBL and CLL that would be missed if only one were measured.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

ImportanceAnthracyclines increase the risk for congestive heart failure (CHF); however, long-term cumulative incidence and risk factors for CHF after anthracycline therapy are not well defined in population-based studies.ObjectiveTo compare the long-term cumulative incidence of CHF in patients with breast cancer or lymphoma treated with anthracycline therapy compared with healthy controls from the same community.Design, Setting, and ParticipantsThis retrospective population-based case-control study included data from the Rochester Epidemiology Project. Participants included residents of Olmsted County, Minnesota, diagnosed with breast cancer or lymphoma from January 1985 through December 2010 matched for age, sex, and comorbidities with healthy controls, with a final ratio of 1 case to 1.5 controls. Statistical analysis was performed between July 2017 and February 2022.ExposuresCancer treatment and CHF risk factors.Main Outcomes and MeasuresThe main outcome was new-onset CHF, as defined by the modified Framingham criteria. Cox proportional hazards regression was used to estimate hazard ratios (HRs) to compare the risk of CHF in participants with cancer vs controls, adjusted for age, sex, diabetes, hypertension, hyperlipidemia, coronary artery disease, obesity, and smoking history.ResultsA total of 2196 individuals were included, with 812 patients with cancer and 1384 participants without cancer. The mean (SD) age was 52.62 (14.56) years and 1704 participants (78%) were female. Median (IQR) follow-up was 8.6 (5.2-13.4) years in the case group vs 12.5 (8.7-17.5) years in the control group. Overall, patients with cancer had higher risk of CHF compared with the control cohort even after adjusting for age, sex, diabetes, hypertension, coronary artery disease, hyperlipidemia, obesity, and smoking status (HR, 2.86 [95% CI, 1.90-4.32]; P < .001). After adjusting for the same variables, CHF risk was greater for patients with cancer receiving anthracycline (HR, 3.25 [95% CI, 2.11-5.00]; P < .001) and was attenuated and lost statistical significance for patients with cancer not receiving anthracyclines (HR, 1.78 [95% CI, 0.83-3.81]; P = .14). Higher cumulative incidence for patients treated with anthracyclines vs comparator cohort was observed at 1 year (1.81% vs 0.09%), 5 years (2.91% vs 0.79%), 10 years (5.36% vs 1.74%), 15 years (7.42% vs 3.18%), and 20 years (10.75% vs 4.98%) (P < .001). There were no significant differences in risk of CHF for patients receiving anthracycline at a dose of less than 180 mg/m2 compared with those at a dose of 180 to 250 mg/m2 (HR, 0.54 [95% CI, 0.19-1.51]) or at a dose of more than 250 mg/m2 (HR, 1.23 [95% CI, 0.52-2.91]). At diagnosis, age was an independent risk factor associated with CHF (HR per 10 years, 2.77 [95% CI, 1.99-3.86]; P < .001).Conclusions and RelevanceIn this retrospective population-based case-control study, anthracyclines were associated with an increased risk of CHF early during follow-up, and the increased risk persisted over time. The cumulative incidence of CHF in patients with breast cancer or lymphoma treated with anthracyclines at 15 years was more than 2-fold that of the control group.

Abstract Context Metformin is the first-line drug for treating diabetes but has a high failure rate. Objective To identify demographic and clinical factors available in the electronic health record (EHR) that predict metformin failure. Methods A cohort of patients with at least 1 abnormal diabetes screening test that initiated metformin was identified at 3 sites (Arizona, Mississippi, and Minnesota). We identified 22 047 metformin initiators (48% female, mean age of 57 ± 14 years) including 2141 African Americans, 440 Asians, 962 Other/Multiracial, 1539 Hispanics, and 16 764 non-Hispanic White people. We defined metformin failure as either the lack of a target glycated hemoglobin (HbA1c) (<7%) within 18 months of index or the start of dual therapy. We used tree-based extreme gradient boosting (XGBoost) models to assess overall risk prediction performance and relative contribution of individual factors when using EHR data for risk of metformin failure. Results In this large diverse population, we observed a high rate of metformin failure (43%). The XGBoost model that included baseline HbA1c, age, sex, and race/ethnicity corresponded to high discrimination performance (C-index of 0.731; 95% CI 0.722, 0.740) for risk of metformin failure. Baseline HbA1c corresponded to the largest feature performance with higher levels associated with metformin failure. The addition of other clinical factors improved model performance (0.745; 95% CI 0.737, 0.754, P < .0001). Conclusion Baseline HbA1c was the strongest predictor of metformin failure and additional factors substantially improved performance suggesting that routinely available clinical data could be used to identify patients at high risk of metformin failure who might benefit from closer monitoring and earlier treatment intensification.

Abstract The prognostic relevance of diagnosis to treatment interval (DTI) in patients with newly diagnosed mantle cell lymphoma (MCL) is unknown. Hence, we sought to evaluate the impact of DTI on outcomes in MCL using 3 large datasets (1) the University of Iowa/Mayo Clinic Specialized Program of Research Excellence Molecular Epidemiology Resource, (2) patients enrolled in the ALL Age Asthma Cohort/CALGB 50403, and (3) a multisitecohort of patients with MCL. Patients were a priori divided into 2 groups, 0 to 14 days (short DTI) and 15 to 60 days (long DTI). The patients in whom observation was deemed appropriate were excluded. One thousand ninety-seven patients newly diagnosed with MCL and available DTI were included in the study. The majority (73%) had long DTI (n=797). Patients with short DTI had worse eastern cooperative oncology group performance status (ECOG PS ≥2), higher lactate dehydrogenase, bone marrow involvement, more frequent B symptoms, higher MCL International Prognostic Index (MIPI ≥6.2), and were less likely to receive intensive induction therapy than long DTI group. The median progression-free survival (2.5 years vs 4.8 years, p<0.0001) and overall survival (7.8 years vs. 11.8 years, p<0.0001) were significantly inferior in the short DTI group than the long DTI cohort and remained significant for progression-free survival and overall survival in multivariable analysis. We show that the DTI is an important prognostic factor in patients newly diagnosed with MCL and is strongly associated with adverse clinical factors and poor outcomes. DTI should be reported in all the patients newly diagnosed with MCL who are enrolling in clinical trials and steps must be taken to ensure selection bias is avoided.