Citations

CALR (calreticulin) trails JAK 2 as the second most mutated gene in essential thrombocythemia (ET). Mutant CALR in ET is a result of frameshift mutations, caused by exon 9 deletions or insertions; type‐1, 52‐bp deletion (p.L367fs*46), and type‐2, 5‐bp TTGTC insertion (p.K385fs*47) variants constitute more than 80% of these mutations. The current study includes a total of 1027 patients divided into test ( n = 402) and validation ( n = 625) cohorts. Among the 402 ET patients in the test cohort, 227 (57%) harbored JAK 2, 11 (3%) Myeloproliferative leukemia virus oncogene ( MPL ), and 114 (28%) CALR mutations; 12% were wild‐type for all three mutations (i.e., triple‐negative). Among the 114 patients with CALR mutations, 51 (45%) displayed type‐1 and 44 (39%) type‐2 variants; compared to mutant JAK 2, both variants were associated with higher platelet and lower hemoglobin and leukocyte counts. However, male sex was associated with only type‐1 ( P = 0.005) and younger age with type‐2 ( P = 0.001) variants. Notably, platelet count was significantly higher in type‐2 vs. type‐1 CALR ‐mutated patients ( P = 0.03) and the particular observation was validated in the validation cohort that included 111 CALR ‐mutated ET patients ( P = 0.002). These findings, coupled with the recent demonstration of preferential expression of mutant and wild‐type CALR in megakaryocytes, suggest differential effects of CALR variants on thrombopoiesis. Am. J. Hematol. 89:E121–E124, 2014. © 2014 Wiley Periodicals, Inc.

Key Points Alternatively polarized macrophages are abundant constituents of the tumor microenvironment in T-cell lymphoproliferative disorders. GATA-3 expression identifies a subset of PTCL, NOS with a distinct cytokine profile and inferior survival.

Objectives To model renal function after radical nephroureterectomy ( RNU ) for upper tract urothelial carcinoma ( UTUC ). To identify predictors of renal function decline after surgery, thereby allowing the identification of patients likely to be ineligible for cisplatin‐based chemotherapy in the adjuvant setting. Patients and Methods We retrospectively identified 374 patients treated with RNU for UTUC at three centres between 1995 and 2010. Estimated glomerular filtration rate ( eGFR ) was calculated using Chronic Kidney Disease Epidemiology Collaboration equation before RNU and at early (1–5 months after RNU ) and late (>5 months) time points after RNU . Only patients deemed eligible for cisplatin‐based chemotherapy before RNU (preoperative glomerular filtration rate [ GFR ] ≥60 mL/min/1.73 m 2 ) were included. Multivariable analysis identified the preoperative predictors of eGFR after RNU at early postoperative and late postoperative time points. Results A total of 163 patients had an eligible early post‐ RNU eGFR measurement and 172 had an eligible late eGFR measurement. The median eGFR declined by 32% and did not show a significant trend toward recovery over time ( P = 0.4). On multivariable analysis preoperative eGFR and patient age were significantly associated with early and late postoperative eGFR , while C harlson comorbidity index score was significantly associated with late postoperative eGFR alone. Conclusions In patients with normal preoperative eGFR (≥60 mL/min/1.73 m 2 ), renal function decreases by one‐third after RNU and does not show evidence of recovery over time. Elderly patients and those with pre‐ RNU eGFR closer to 60 mL/min/1.73 m 2 (lower eGFR in the present cohort) are more likely to be ineligible for adjuvant cisplatin‐based chemotherapy regimens because of renal function loss after RNU .

ABSTRACTGenes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene‐environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P‐values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.

Abstract BACKGROUND Accurate evaluation of unclassified sequence variants in cancer predisposition genes is essential for clinical management and depends on a multifactorial analysis of clinical, genetic, pathologic, and bioinformatic variables and assays of transcript length and abundance. The integrity of assay data in turn relies on appropriate assay design, interpretation, and reporting. METHODS We conducted a multicenter investigation to compare mRNA splicing assay protocols used by members of the ENIGMA (Evidence-Based Network for the Interpretation of Germline Mutant Alleles) consortium. We compared similarities and differences in results derived from analysis of a panel of breast cancer 1, early onset (BRCA1) and breast cancer 2, early onset (BRCA2) gene variants known to alter splicing (BRCA1: c.135-1G>T, c.591C>T, c.594-2A>C, c.671-2A>G, and c.5467+5G>C and BRCA2: c.426-12_8delGTTTT, c.7988A>T, c.8632+1G>A, and c.9501+3A>T). Differences in protocols were then assessed to determine which elements were critical in reliable assay design. RESULTS PCR primer design strategies, PCR conditions, and product detection methods, combined with a prior knowledge of expected alternative transcripts, were the key factors for accurate splicing assay results. For example, because of the position of primers and PCR extension times, several isoforms associated with BRCA1, c.594-2A>C and c.671-2A>G, were not detected by many sites. Variation was most evident for the detection of low-abundance transcripts (e.g., BRCA2 c.8632+1G>A Δ19,20 and BRCA1 c.135-1G>T Δ5q and Δ3). Detection of low-abundance transcripts was sometimes addressed by using more analytically sensitive detection methods (e.g., BRCA2 c.426-12_8delGTTTT ins18bp). CONCLUSIONS We provide recommendations for best practice and raise key issues to consider when designing mRNA assays for evaluation of unclassified sequence variants.

AbstractTranslational stories range from straightforward to complex. In this commentary, the story of the rapid and successful translation of rituximab therapy for the treatment of non‐Hodgkin's lymphoma (NHL) is examined. Development of this monoclonal antibody therapy began in the late 1980s. In 1994, rituximab received its first approval for the treatment of NHL by the United States Food and Drug Administration (FDA). Rituximab has since been approved for additional indications and has transformed medical practice. However, the social and political implications of these rapid successes are only beginning to become clear. In this commentary, key events in the rapid translation of rituximab from the bench to bedside are highlighted and placed into this historical framework. To accomplish this, the story of rituximab is divided into the following six topics, which we believe to be widely applicable to case studies of translation: (1) underlying disease, (2) key basic science, (3) key clinical studies in translation, (4) FDA approval process, (5) changes to medical practice, and (6) the social and political influences on translation.