Pathobiology of Anaplastic Large Cell Lymphoma

The authors revise the concept of anaplastic large cell lymphoma (ALCL) in the light of the recently updated WHO classification of Tumors of Hematopoietic and Lymphoid Tissues both on biological and clinical grounds. The main histological findings are illustrated with special reference to the cytological spectrum that is indeed characteristic of the tumor. The phenotype is reported in detail: the expression of the ALK protein as well as the chromosomal abnormalities is discussed with their potential pathogenetic implications. The clinical features of ALCL are presented by underlining the difference in terms of response to therapy and survival between the ALK-positive and ALK-negative forms. Finally, the biological rationale for potential innovative targeted therapies is presented

Effect of Contextual Interference in the Practicing of a Computer Task in Individuals Poststroke

Objectives. Sensory and motor alterations resulting from stroke often impair the performance and learning of motor skills. The present study is aimed at investigating whether and how poststroke individuals and age- and sex-matched healthy controls benefit from a contextual interference effect on the practice of a maze task (i.e., constant vs. random practice) performed on the computer. Methods. Participants included 21 poststroke individuals and 21 healthy controls, matched by sex and age (30 to 80 years). Both groups were divided according to the type of the practice (constant or random) presented in the acquisition phase of the learning protocol. For comparison between the groups, types of practice, and blocks of attempts, the analysis of variance with Tukey’s post hoc test (p<0.05) was used. Results. Poststroke individuals presented longer movement times as compared with the control group. In addition, only poststroke individuals who performed the task with random practice showed improved performance at the transfer phase. Moreover, randomized practice enabled poststroke individuals to perform the transfer task similarly to individuals without any neurological impairment. Conclusion. The present findings indicated a significant effect of contextual interference of practice in poststroke individuals, suggesting that applying randomized training must be considered when designing rehabilitation protocols for this population

Avelumab in Combination Regimens for Relapsed/Refractory DLBCL:Results from the Phase Ib JAVELIN DLBCL Study

Background Relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) is associated with a poor prognosis despite the availability of multiple treatment options. Preliminary evidence suggests that DLBCL may be responsive to programmed death ligand 1 (PD-L1)/programmed death 1 inhibitors. Objective The JAVELIN DLBCL study was conducted to assess whether a combination of agents could augment and sustain the antitumor immunity of avelumab, an anti-PD-L1 antibody, in R/R DLBCL. Methods This was a multicenter, randomized, open-label, parallel-arm study with a phase Ib and a phase III component. Reported here are the results from the phase Ib study, wherein 29 adult patients with DLBCL were randomized 1:1:1 to receive avelumab in combination with utomilumab (an immunoglobulin G2 4-1BB agonist) and rituximab (arm A), avelumab in combination with utomilumab and azacitidine (arm B), or avelumab in combination with bendamustine and rituximab (arm C). The primary endpoints were dose-limiting toxicities and objective response as assessed by the investigator per Lugano Response Classification criteria. Results Of the seven patients in arm A, one (14.3%) experienced two grade 3 dose-limiting toxicities (herpes zoster and ophthalmic herpes zoster); no dose-limiting toxicities were reported in arms B or C. No new safety concerns emerged for avelumab. One partial response was reported in arm A, three complete responses in arm C, and no responses in arm B. Given the insufficient antitumor activity in arms A and B and the infeasibility of expanding arm C, the study was discontinued before initiation of the phase III component. Conclusions The low level of clinical activity suggests that PD-L1 inhibitor activity may be limited in R/R DLBCL. ClinicalTrials.gov Identifier NCT02951156

Integrative Genomics Identifies the Molecular Basis of Resistance to Azacitidine Therapy in Myelodysplastic Syndromes

Myelodysplastic syndromes and chronic myelomonocytic leukemia are blood disorders characterized by ineffective hematopoiesis and progressive marrow failure that can transform into acute leukemia. The DNA methyltransferase inhibitor 5-azacytidine (AZA) is the most effective pharmacological option, but only ∼50% of patients respond. A response only manifests after many months of treatment and is transient. The reasons underlying AZA resistance are unknown, and few alternatives exist for non-responders. Here, we show that AZA responders have more hematopoietic progenitor cells (HPCs) in the cell cycle. Non-responder HPC quiescence is mediated by integrin α5 (ITGA5) signaling and their hematopoietic potential improved by combining AZA with an ITGA5 inhibitor. AZA response is associated with the induction of an inflammatory response in HPCs in vivo. By molecular bar coding and tracking individual clones, we found that, although AZA alters the sub-clonal contribution to different lineages, founder clones are not eliminated and continue to drive hematopoiesis even in complete responders

Associations between Smoking and Alcohol and Follicular Lymphoma Incidence and Survival: A Family-Based Case-Control Study in Australia

The association between smoking and alcohol consumption and follicular lymphoma (FL) incidence and clinical outcome is uncertain. We conducted a population-based family case-control study (709 cases: 490 controls) in Australia. We assessed lifetime history of smoking and recent alcohol consumption and followed-up cases (median = 83 months). We examined associations with FL risk using unconditional logistic regression and with all-cause and FL-specific mortality of cases using Cox regression. FL risk was associated with ever smoking (OR = 1.38, 95%CI = 1.08–1.74), former smoking (OR = 1.36, 95%CI = 1.05–1.77), smoking initiation before age 17 (OR = 1.47, 95%CI = 1.06–2.05), the highest categories of cigarettes smoked per day (OR = 1.44, 95%CI = 1.04–2.01), smoking duration (OR = 1.53, 95%CI = 1.07–2.18) and pack-years (OR = 1.56, 95%CI = 1.10–2.22). For never smokers, FL risk increased for those exposed indoors to >2 smokers during childhood (OR = 1.84, 95%CI = 1.11–3.04). For cases, current smoking and the highest categories of smoking duration and lifetime cigarette exposure were associated with elevated all-cause mortality. The hazard ratio for current smoking and FL-specific mortality was 2.97 (95%CI = 0.91–9.72). We found no association between recent alcohol consumption and FL risk, all-cause or FL-specific mortality. Our study showed consistent evidence of an association between smoking and increased FL risk and possibly also FL-specific mortality. Strengthening anti-smoking policies and interventions may reduce the population burden of FL

Occupational exposure to extremely low-frequency magnetic fields and follicular lymphoma risk: a family case-control study

Objectives: We aimed to examine the relationship between occupational exposure to extremely low-frequency magnetic fields (ELF-MFs) and follicular lymphoma (FL) risk. Methods: We conducted a family case-control study between 2011 and 2016 in Australia and included 681 cases. Controls were either a family member of cases (related (n=294), unrelated (n=179)) or were unrelated recruited for a similarly designed Australian multiple myeloma study (n=711). We obtained detailed job histories using lifetime work calendars. We assigned exposure to ELF-MFs using an enhanced job exposure matrix, with a lag period of 10 years. We examined associations with FL risk using logistic regression accounting for relatedness between cases and controls. We performed sensitivity analyses including by control type, by sex, complete case analyses, ELF-MF exposure percentiles in addition to quartiles, ELF-MF exposure in the maximum exposed job, a shorter lag period (1 year) and the cumulative exposure in the most recent time period (1-9 years). Results: We observed no association with the average intensity, duration or lifetime cumulative exposure to occupational ELF-MF exposure in the primary or sensitivity analyses. Conclusions: Our findings do not support an association between occupational ELF-MF exposure and FL risk. Although the inclusion of family members as part of the larger control group may have biased our risk estimates towards the null, findings were similar in sensitivity analyses restricted to cases and unrelated controls. Further research incorporating enhanced exposure assessment to ELF-MF is warranted to inform occupational safety regulations and any potential role in lymphomagenesis.This study was supported by the National Health and Medical Research Council of Australia (ID 1006707). The National Health and Medical Research Council also supported MTvL (ID 1012141). MKO is supported by an International Postgraduate Award Scholarship through the Australian Government Research Training Program (ID 5188838) and a Cancer Institute NSW Translational Cancer Research Network PhD Scholarship Top-up award. MCT is funded by a Ramón y Cajal fellowship (RYC-2017-01892) from the Spanish Ministry of Science, Innovation and Universities and co-funded by the European Social Fund. ISGlobal acknowledges support from the Spanish Ministry of Science and Innovation through the 'Centro de Excelencia Severo Ochoa 2019–2023' Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program. The INTEROCC Study was supported by the NIH (grant no. 1R01CA124759)

Supplementary Tables 1a-3d from A Population-Based Family Case–Control Study of Sun Exposure and Follicular Lymphoma Risk

Supplementary Tables 1a-3d. Supplementary Table 1a: Bayesian information criterion for outdoor hours group-based trajectory model according to number of groups and trajectory outdoor hours. Supplementary Table 1b: Average posterior probability value and odds of correct classification for outdoor hours trajectory groups. Supplementary Table 1c: Estimated probability and the proportion of study members classified in each group according to the maximum posterior probability assignment rule. Supplementary Table 2a: Odds ratios and 95% confidence intervals for FL risk in relation to total lifetime outdoor hours during decade years among cases and related controls.Supplementary Table 2b: Odds ratios and 95% confidence intervals for FL risk in relation to outdoor hours on weekdays, weekends, and holidays at each decade year among cases and related controls. Supplementary Table 2c: Odds ratios and 95% confidence intervals for FL risk in relation to trajectories of outdoor hours across the decade years among cases and related controls. Supplementary Table 2d: Odds ratios and 95% confidence intervals for FL risk in relation to total lifetime outdoor hours during decade years among cases and unrelated controls. Supplementary Table 2e: Odds ratios and 95% confidence intervals for FL risk in relation to outdoor hours on weekdays, weekends, and holidays at each decade year among cases and unrelated controls. Supplementary Table 2f: Odds ratios and 95% confidence intervals for FL risk in relation to trajectories of outdoor hours across the decade years among cases and unrelated controls. Supplementary Table 3a: Bayesian information criterion for outdoor hours group-based trajectory model according to number of groups and trajectory outdoor hours – cases and related controls. Supplementary Table 3b: Bayesian information criterion for outdoor hours group-based trajectory model according to number of groups and trajectory outdoor hours – cases and unrelated controls. Supplementary Table 3c: Average posterior probability value and odds of correct classification for outdoor hours trajectory groups. Supplementary Table 3d: Estimated probability and the proportion of study members classified in each group according to the maximum posterior probability assignment rule.</p

Supplementary Figure 1 from A Population-Based Family Case–Control Study of Sun Exposure and Follicular Lymphoma Risk

Supplementary Figure 1 shows the exclusions for cases and controls during the recruitment processes</p