Primary cutaneous γδ T cell lymphomas (PCGDTLs) represent a heterogeneous group of uncommon but aggressive cancers. Herein, we perform genome-wide DNA, RNA, and T cell receptor (TCR) sequencing on 29 cutaneous γδ lymphomas. We find that PCGDTLs are not uniformly derived from Vδ2 cells. Instead, the cell-of-origin depends on the tissue compartment from which the lymphomas are derived. Lymphomas arising from the outer layer of skin are derived from Vδ1 cells, the predominant γδ cell in the epidermis and dermis. In contrast, panniculitic lymphomas arise from Vδ2 cells, the predominant γδ T cell in the fat. We also show that TCR chain usage is non-random, suggesting common antigens for Vδ1 and Vδ2 lymphomas respectively. In addition, Vδ1 and Vδ2 PCGDTLs harbor similar genomic landscapes with potentially targetable oncogenic mutations in the JAK/STAT, MAPK, MYC, and chromatin modification pathways. Collectively, these findings suggest a paradigm for classifying, staging, and treating these diseases.
Cutaneous T cell lymphomas (CTCLs) are a clinically heterogeneous collection of lymphomas of the skin-homing T cell. To identify molecular drivers of disease phenotypes, we assembled a cohort of CTCLs with representative samples from diverse disease subtypes and stages. Via DNA/RNA-sequencing, immunophenotyping, and ex vivo functional assays, we identified the landscape of putative driver genes, elucidated genetic relationships between CTCLs across disease stages, and inferred molecular subtypes in patients with stage-matched leukemic disease. Collectively, our analysis identified 86 putative driver genes, including 19 genes not previously implicated in this disease. 2 mutations have never been previously described for any cancer. Functionally, multiple mutations augment T cell receptor-dependent proliferation, highlighting the importance of this pathway in lymphomagenesis. To identify putative genetic causes of disease heterogeneity, we examined the distribution of driver genes across clinical cohorts. There are broad similarities across disease stages. Many driver genes are shared by mycosis fungoides (MF) and Sezary syndrome (SS). However, there are significantly more structural variants in leukemic disease, leading to highly recurrent deletions of putative tumor suppressors that are uncommon in early-stage skin-centered MF. For example, TP53 is deleted in 7% and 87% of MF and SS, respectively. In both human and mouse samples, PD1 mutations drive aggressive behavior. PD1 wild-type lymphomas show features of T cell exhaustion. PD1 deletions are sufficient to reverse the exhaustion phenotype, promote a FOXM1-driven transcriptional signature, and predict significantly worse survival. Collectively, our findings clarify CTCL genetics and provide novel insights into pathways driving diverse disease phenotypes.
Background: The rapid global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains the international public health concern of the decade. Early clinical data suggest that patients (pts) with hematologic malignancies are vulnerable to severe forms of SARS-CoV-2 and have higher mortality rates than the general population. Greater understanding of risk factors and outcomes associated with SARS-CoV-2 in pts with hematologic malignancies is crucial in order to develop individualized risk-benefit analyses to guide care. Herein, we report a cohort study from a Comprehensive Cancer Center evaluating outcomes in pts with hematologic malignancies who developed SARS-CoV-2. Methods: Adult pts at Northwestern Memorial Hospital with a current/prior hematologic malignancy and laboratory-confirmed SARS-CoV-2 infection confirmed by quantitative RT-PCR from nasopharyngeal swabs between March-July, 2020 were identified using electronic health records. Data were collected and analyzed based on epidemiologic, laboratory, and clinical characteristics. Severity of illness was defined by level of care (ambulatory, inpatient), need for advanced respiratory support (high flow nasal cannula, BiPAP, mechanical ventilation), incidence of thrombotic events, incidence of acute kidney injury (AKI), and/or death. Statistical analyses of risk factors, severity, and outcomes were performed. Subgroup analyses based on antineoplastic treatment status and receipt of SARS-CoV-2 -directed therapy were made. Active cancer treatment was defined as antineoplastic therapy within 12 months of SARS-CoV-2 diagnosis. Results: Demographic (Table 1) and clinical (Table 2) data were recorded from 73 SARS-CoV-2 infected pts. Sixty (80%) pts had lymphoid and 15 (20%) had myeloid neoplasms, 2 with concurrent lymphoid and myeloid neoplasms. Thirty-seven (51%) pts were undergoing active treatment for their malignancy. Twenty-one pts (29%) were managed in the ambulatory setting while 52 (71%) required hospital admission. Twenty-five (34%) pts required advanced respiratory support including 14 (19%) who required mechanical ventilation. Four pts (6%) had thrombotic events and 31 (42%) received SARS-CoV-2-directed therapies. Sixteen pts (22%) died during the study period. Pts on active cancer treatment had higher rates of hospital admission (81% v 60%; p=0.05) and AKI (51% v 29%; p=0.04) but similar rates of death compared with pts not on active treatment (24% v 20%; p=0.66) (Table 3). Comparing pts who received SARS-CoV-2 -directed therapy versus no therapy: pts on therapy had longer median lengths of stay (11 v 7 days; p=0.04) and higher rates of hospital admission (94% v 55%; p=0.0003) but similar rates of death (23% v 21%; p=0.91); pts in the ICU on SARS-COV-2 -directed therapy had lower rates of death (38% v 88% p=0.02) than pts who did not receive such therapy (Table 4). Twenty-six pts (36%) were tested for viral clearance, defined as two serial negative swabs ≥24 hours apart. Of these, 17 (65%) achieved clearance with a median time of 51 days (range 15-119 days). Thirteen pts (18%) had antibody (Ab) testing. Ten (77%) had detectable Abs: 8 were positive for IgG, 1 for IgG and IgM, and 1 had unspecified positivity. Notably, all 3 pts with undetectable Abs were on active cancer treatment. Conclusion: We demonstrate that pts with hematologic malignancies are exceptionally vulnerable to severe forms of SARS-CoV-2 with high mortality rates. The incidence of thrombotic events was low, an unexpected finding in the setting of a hyperinflammatory syndrome. Prolonged time to viral clearance was observed, a finding which may cause potential delays in the resumption of cancer-directed therapies. Notably, the majority of pts who received antibody testing had detectable antibodies suggesting that pts with hematologic malignancies may be able to mount an immune response to early vaccination. Accordingly, close monitoring, aggressive therapy, and early vaccination, when available, may be warranted for this population. Larger studies are needed to confirm our findings and help guide management of pts with hematologic malignancies during the SARS-CoV-2 pandemic. Disclosures Altman: Bristol-Myers Squibb: Consultancy; Janssen: Consultancy; Immune Pharmaceuticals: Consultancy; Syros: Consultancy; Genentech: Research Funding; Novartis: Consultancy; Amphivena: Research Funding; Amgen: Research Funding; Aprea: Research Funding; ImmunoGen: Research Funding; Celgene: Research Funding; Boehringer Ingelheim: Research Funding; Fujifilm: Research Funding; Kartos: Research Funding; AbbVie: Other: advisory board, Research Funding; Kura Oncology: Other: Scientific Advisory Board - no payment accepted, Research Funding; BioSight: Other: No payment but was reimbursed for travel , Research Funding; Daiichi Sankyo: Other: Advisory Board - no payment but was reimbursed for travel; Agios: Other: advisory board, Research Funding; Glycomimetics: Other: Data safety and monitoring committee; Astellas: Other: Advisory Board, Speaker (no payment), Steering Committee (no payment), Research Funding; Theradex: Other: Advisory Board; ASH: Consultancy; Cancer Expert Now: Consultancy; France Foundation: Consultancy; PeerView: Consultancy; PrIME Oncology: Consultancy. Winter:Delta Fly Pharma: Consultancy; Amgen: Consultancy; Epizyme: Other: DSMB; CVS/Caremark: Consultancy; Ariad/Takeda: Consultancy; Norvartis: Consultancy, Other: DSMB; Merck: Membership on an entity's Board of Directors or advisory committees, Other: advisory board; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Other: advisory board. Gordon:Zylem Biosciences: Patents & Royalties: Patents, No Royalties. Pro:Verastem Oncology: Research Funding. Ma:TG Therapeutics: Research Funding; Juno: Research Funding; Novartis: Research Funding; Kite: Consultancy, Honoraria; Pharmacyclics, LLC, an AbbVie Company: Consultancy, Honoraria, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria, Research Funding, Speakers Bureau; BeiGene: Honoraria, Research Funding, Speakers Bureau; Bioverativ: Consultancy, Honoraria; Genentech: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau. Karmali:BMS/Celgene/Juno: Honoraria, Other, Research Funding, Speakers Bureau; Takeda: Research Funding; Karyopharm: Honoraria; Gilead/Kite: Honoraria, Other, Research Funding, Speakers Bureau; AstraZeneca: Speakers Bureau; BeiGene: Speakers Bureau.
Introduction: HF is a major cause of morbidity and mortality in AML patients. This study was designed as an external evaluation of a risk score to determine the risk of HF in patients treated with anthracyclines for AML. Methods: A validation cohort was composed of 204 consecutive patients with AML treated with anthracyclines. 2DSTE was performed using TomTec software to obtain baseline GLS values. LVEF was calculated using modified Simpson’s biplane method. HF hospitalizations were defined using standard clinical criteria. The HF risk score included a baseline GLS > - 15% (6 points), baseline LVEF<50% (4 points), pre-existing cardiovascular disease (4 points), anthracycline dose >/= 250 mg/m 2 (2 points), and age > 60 years (1 point). Patients were stratified into low (0 to 2 points), medium (3 to 9 points), and high risk (10 to 17 points). Statistical analysis was performed to evaluate event-free survival of the risk categories. Results: The average age of the cohort was 54 with an average risk score of 7 points. 55% of the patients were male. In total, 44 patients (21%) experienced a hospitalization for HF (median time to hospitalization 1 month) within the follow-up period (median 18 months). The observed incidence of HF by risk category was 14% (18 of 130) in the low, 31% (19 of 61) in medium, and 54% (7 of 13) in high risk group. The association between HF and the risk group category was highly significant (p = 0.001). Event-free survival by risk category (Figure 1) was also statistically significant (p = 0.05), with individuals in the high risk category having a reduced event-free survival. Conclusions: This is the first external validation study of a risk score for HF in AML patients. The risk score that we evaluated was successful at identifying patient who were at higher risk of hospitalization for HF. This may be a useful tool in clinical practice to counsel patients regarding the risk of HF after induction chemotherapy with anthracyclines.
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