Citations

LncRNAs play an indispensable role in the process of M1 macrophage via regulating the development of macrophages and their responses to bacterial pathogens and viral infections. However, there are few studies on the lncRNA-mediated functions and regulatory mechanisms of M2 macrophage polarization. In this study, we found a number of differentially expressed lncRNAs between human monocyte derived M0 and M2 macrophages according to array analysis and qRT-PCR validation. The lncRNA RP11-389C8.2 (we named lnc-M2 in this study) was observed to be highly expressed in M2 macrophages. In Situ Localization and Quantification Analysis showed that lnc-M2 was expressed in the nucleus and cytosolic compartments of M2 macrophages. Notably, lnc-M2 knockdown enhanced the phagocytic ability of M2 macrophages. Ulteriorly, the results of RNA-Protein interaction experiments indicated that protein kinase A (PKA) was a lnc-M2 associated RNA-binding protein (RBP). Western blot showed that p-CREB, a well-known key downstream transcription factor of PKA, was lowly phosphorylated in lnc-M2-silencing M2 macrophages. Furthermore, we found that transcriptional factor STAT3 promoted lnc-M2 transcription along with the up-regulation of epigenetic histone modification markers at the lnc-M2 promoter locus, indicating that STAT3 activated lnc-M2 and eventually facilitated the process of M2 macrophage differentiation via the PKA/CREB pathway. Collectively, our date provide evidence that the transcription factor STAT3 can promote the transcription of lnc-M2 and facilitated the process of M2 macrophage differentiation via the PKA/CREB pathway. This study highlights a novel mechanism underlying the M2 macrophage differentiation.

Objective To evaluate patient‐reported outcome (PRO) data from the IMmotion150 study. The phase 2 IMmotion150 study showed improved progression‐free survival with atezolizumab plus bevacizumab vs sunitinib in patients with programmed death‐ligand 1 (PD‐L1)+ tumours and suggested activity of atezolizumab monotherapy in previously untreated metastatic renal cell carcinoma (mRCC). Patients and methods Patients with previously untreated mRCC were randomised to atezolizumab 1200 mg intravenously (i.v.) every 3 weeks ( n = 103), the atezolizumab regimen plus bevacizumab 15 mg/kg i.v. every 3 weeks ( n = 101), or sunitinib 50 mg orally daily (4 weeks on, 2 weeks off; n = 101). The MD Anderson Symptom Inventory (MDASI) and Brief Fatigue Inventory (BFI) were administered on days 1 and 22 of each 6‐week cycle. Time to deterioration (TTD), change from baseline in MDASI core and RCC symptom severity, interference with daily life, and BFI fatigue severity and interference scores were reported for all comers. The TTD was the first ≥2‐point score increase over baseline. Absolute effect size ≥0.2 suggested a clinically important difference with checkpoint inhibitor therapy vs sunitinib. Results Completion rates were >90% at baseline and ≥80% at most visits. Delayed TTD in core and RCC symptoms, symptom interference, fatigue, and fatigue‐related interference was observed with atezolizumab (both alone and in combination) vs sunitinib. Improved TTD (hazard ratio [HR], 95% confidence interval [CI]) was more pronounced with atezolizumab monotherapy: core symptoms, 0.39 (0.22–0.71); RCC symptoms, 0.22 (0.12–0.41); and symptom interference, 0.36 (0.22–0.58). Change from baseline by visit, evaluated by the MDASI, also showed a trend favouring atezolizumab monotherapy vs sunitinib. Small sample sizes may have limited the ability to draw definitive conclusions. Conclusion PROs suggested that atezolizumab alone or with bevacizumab maintained daily function compared with sunitinib. Notably, symptoms were least severe with atezolizumab alone vs sunitinib (IMmotion150; ClinicalTrials.gov Identifier: NCT01984242).

Abstract To study the impact of dose modification and temporary interruption of ibrutinib in routine clinical practice, we conducted a retrospective study of consecutive CLL patients treated with ibrutinib outside the context of a clinical trial at Mayo Clinic, (Rochester, MN) from 11/2013 to 12/2017. Of 209 patients, 131 (74%) had unmutated IGHV , 38 (20%) had TP53 disruption, and 47 (22%) were previously untreated. A total of 87/209 (42%) patients started reduced dose ibrutinib (<420 mg daily; n = 43, physician preference; n = 33, concomitant medications; and n = 11, other). During 281 person‐years of treatment, 91/209 patients had temporary dose interruption (54%, nonhematologic toxicity; 29%, surgical procedures; 10%, hematologic toxicity; and 7%, other). After a median follow‐up of 24 months, the estimated median event‐free survival (EFS) was 36 months, and median overall survival (OS) was not reached. On multivariable analyses, temporary ibrutinib interruption (hazard ratio [HR]: 2.37, P = .006) and TP53 disruption at ibrutinib initiation (HR: 1.81, P = .048) were associated with shorter EFS, whereas only TP53 disruption (HR: 2.38, P = .015) was associated with shorter OS. Initial ibrutinib dose and dose modification during therapy did not appear to impact EFS or OS. These findings illustrate the challenges associated with continuous oral therapy with ibrutinib in patients with CLL.

7526 Background: Stem cell transplant (SCT) was considered to be beneficial in CLL patients with Richter transformation (RT). We report a single center experience of SCT for RT. Methods: CLL patients with biopsy-confirmed RT to DLBCL who underwent SCT were identified from Mayo Clinic CLL database, and clinical information was abstracted by chart review. Survival analysis was done with the Kaplan-Meier method. Results: Twenty-four of 204 RT patients underwent SCT, 20 autologous and 4 allogeneic. The median lines of prior CLL therapy was 1 (range 0-4). Only 4 patients were exposed to ibrutinib prior to RT. The median age at RT diagnosis was 62 (range 41-73). Five of 17 (29%) patients had bulky disease (≥ 5 cm), 12 of 20 (60%) had elevated LDH, and 6 of 15 (40%) had TP53 disruption (del(17p) or TP53 mutation). The median lines of RT therapy prior to SCT was 2 (range 1-4); treatments included R-CHOP-like alone (n = 7), platinum-based alone (n = 1), both R-CHOP-like and platinum-based (n = 11), novel agents (n = 2), and high dose MTX-based (n = 3). Response prior to SCT was CR in 12 (50%) and PR in 12 (50%) patients. The median time from RT diagnosis to SCT was 6.8 months (range 3.3-42.3). After a median follow-up of 52.7 months after SCT, there were 10 RT relapses, 4 CLL progression, and 11 deaths (7 RT, 1 CLL and 3 unrelated). The median progression-free survival (PFS) was 28.5 months (95% CI 8.3-NA; 1-year PFS 61.8%, 2-year PFS 50.5%). The median post-SCT survival was 56.3 months (95% CI 30.6-76.6; 2-year survival 82.0%, 4-year survival 65.6%). Elevated LDH was associated with worse PFS (median 8.9 months vs NA, P= 0.014) and a trend of worse post-SCT survival (53.7 vs 67.4 months, P= 0.153). Other factors including age, prior CLL treatment (untreated vs treated), bulky disease, response prior to SCT, and TP53 disruption were not associated with PFS or post-SCT survival. Among the 4 allogeneic SCT patients, 1 had RT relapse 10.5 months after SCT and was treated with venetoclax, ibrutinib and obinutuzumab and remained alive at last follow-up (12.9 months after SCT). All 3 other patients remained in remission and alive at last follow up (15.6, 16.1 and 108.5 months after SCT, respectively). Conclusions: SCT may benefit select RT patients. The role of SCT in the novel agent era needs further study.

7522 Background: Ibrutinib therapy is associated with an increased risk (~15%) of AF. An accurate risk assessment model for the development of AF in pts starting ibrutinib is not established, and outcomes after AF are not well described. Methods: An IRB approved retrospective review of CLL pts treated with ibrutinib at Mayo Clinic between Oct 2012 and Nov 2018 was conducted. Results: 299 pts were identified with a total of 565 years of ibrutinib exposure (Table). After a median follow-up of 24 months (range 0–70 months), 51 pts developed treatment-emergent AF (13 [25%] CTCAE 3 or higher). Our study assessed 3 clinical prediction models, the Framingham (Schanbel:Lancet 2009), Italian (Visentin:Blood 2018;132:3118), and Shanafelt (Shanafelt:Leuk Lymp; 2017) risk scores. Based on a lower Akaike information criteria, the Italian score was best able to predict risk of treatment emergent AF (2-year risk of AF with score 0 6%; 1-2 8%; 3-4 26%; 5+ 47%). Thirty (61%) pts were treated with medical therapy for AF (27 rate control; 2 rhythm control; 1 both). 16 (31%) pts underwent interventional therapy (3 AV node ablation; 11 cardioversion; and 2 pacemaker). Twelve (23%) pts temporarily held ibrutinib and resumed their original dose, 22 (43%) pts continued reduced dose ibrutinib and 11 (22%) continued their initial ibrutinib dose. Six (12%) pts permanently discontinued ibrutinib. Of 51 pts with treatment-emergent AF, 41 (80%) had a CHA2DS2-VASc score of ≥2 (41% received anticoagulation alone; 12% received antiplatelet therapy alone; 10% received both). No pt developed a thrombotic stroke after treatment-emergent AF. Two major bleeds, (1 GI and 1 intracranial) occurred, one in a pt on concomitant antiplatelet and anticoagulation therapy, and one in a pt receiving neither. The development of AF was associated with shorter event-free survival (HR 2.5, 95%CI 1.5-4.2, p<.001) and shorter overall survival (HR 3.5, 95%CI 2.0-6.3, p<.001). Conclusions: The Italian score was the best predictor of AF development in this cohort of ibrutinib treated pts. Although the vast majority of pts who develop AF after ibrutinib are able to continue therapy, the occurrence of AF appears to be associated with shorter EFS and OS. [Table: see text]

7510 Background: We previously demonstrated that PFS may be a candidate surrogate endpoint for OS in ES-SCLC using data from 3 randomized trials (Foster, Cancer 2011). Here, we sought to formally assess the patient- and trial-level surrogacy of PFS using data from 9 additional randomized phase II and III trials conducted by the NCI-funded cancer cooperative groups since 1986. Methods: Individual patient data from all 12 trials (3178 patients: 9 phase III and 3 phase II) were pooled. OS was the primary endpoint in all phase III trials; 3 phase III and 1 phase II trial were positive per protocol. Patient-level surrogacy (Kendall’s tau) was assessed using the Clayton copula bivariate survival model. Trial-level surrogacy was assessed via association of the log hazard ratios on OS and PFS across trials, including: weighted (by trial size) least squares regression of Cox model effects (R² WLS) and weighted (by trial size) correlation of the copula effects (R² Copula). One trial had 4 treatment arms thus 14 total two-arm comparisons were made. Results: With a median follow-up of 41.8 months in the 106 patients still alive, the median OS and PFS across trials were 9.7 months (95% CI: 9.5, 9.9) and 5.7 months (95% CI: 5.5, 5.8), respectively. There were 3120 PFS events in total (2564 disease progressions and 556 deaths without progression). The median time from progression to death was 4.1 months (95% CI: 3.9, 4.3). PFS showed modest association with OS at the patient-level (tau= 0.56) and at the trial-level (R² WLS = 0.58; R² Copula (standard error) = 0.55 (0.29)). The 95% CIs for the predicted HR for OS given observed HR on PFS under a weighted leave-one-out prediction always included the observed HR for OS; however such intervals were wide, suggesting uncertainty on the practical use of PFS as a surrogate for OS in this setting. Conclusions: PFS failed to demonstrate surrogacy for OS in ES-SCLC based on this large pooled analysis. Given that the difference in the median PFS and OS is less than 6 months, we recommend using OS as the primary endpoint in phase III trials of previously untreated ES-SCLC.

503 Background: To correlate clinical features of estrogen receptor positive breast cancer with somatic mutations, massively parallel sequencing (MPS) was applied to tumor and normal DNAs accrued from patients treated with neoadjuvant aromatase inhibitors (AI). Methods: MPS was applied to 77 baseline tumor biopsy samples from the preoperative letrozole trial (JACS 2009: 208, 906) and the Z1031 trial (JCO 2011: 29, 2342) followed by targeted sequencing in another 240 trial samples. Standard statistical approaches were used to compare mutation status and clinical parameters and pathway-based correlation was used to assess interactions between signaling perturbations induced by gene mutations and response to neoadjuvant AI. Results: Eighteen genes were significantly mutated above background. Aside from PIK3CA mutations, the list is dominated by loss-of-function mutations in tumor suppressor genes. Five (RUNX1, CBFP, MYH9, MLL3 and SF3B1) have been previously linked to benign and malignant hematopoietic disorders. Clinical correlation revealed that TP53 mutation was associated with PAM50 LumB status, high-grade histology and high proliferation rates whereas loss-of-function mutations in MAP3K1 associate with PAM50 lumA status, low proliferation rates, and low grade histology. Mutations in GATA3 were associated with greater suppression of proliferation upon AI treatment suggesting mutGATA3 may predict endocrine response. Notably, mutations in MAP3K1 were more common in PIK3CA mutant cases, suggesting cooperation. Pathway analysis demonstrated that rare MAP2K4 mutations produce similar pathway perturbations as MAP3K1 mutation, a logical finding since MAP2K4 is a substrate for MAP3K1. Signaling network patterns driven by lncRNA MALAT1 mutations were associated with multiple poor clinical outcome features. Rare mutations in druggable kinases included two in the kinase domain of HER2. Conclusions: Tumor heterogeneity in luminal-type breast cancer is driven by specific patterns of somatic mutations, however most druggable or potentially prognostic mutations are infrequent. Prospective clinical trials based on these findings will require comprehensive genome sequencing approaches and large scale investigations.

PurposeTo commission an open source Monte Carlo (MC) dose engine, “MCsquare” for a synchrotron‐based proton machine, integrate it into our in‐house C++‐based I/O user interface and our web‐based software platform, expand its functionalities, and improve calculation efficiency for intensity‐modulated proton therapy (IMPT).MethodsWe commissioned MCsquare using a double Gaussian beam model based on in‐air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread‐out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++‐based dose calculation code and web‐based second check platform “DOSeCHECK.” We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well‐benchmarked GPU‐accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)‐related model‐dependent biological dose calculation.ResultsDifferences between MCsquare calculations and SOBP measurements were <2.5% (<1.5% for ~85% of measurements) in water. The dose distributions calculated using MCsquare agreed well with the results calculated using gMC in patient geometries. The average 3D gamma analysis (2%/2 mm) passing rates comparing MCsquare and gMC calculations in the 12 patient geometries were 98.0 ± 1.0%. The computation time to calculate one IMPT plan in patients’ geometries using an inexpensive CPU workstation (Intel Xeon E5‐2680 2.50 GHz) was 2.3 ± 1.8 min after the variable resolution technique was adopted. All calculations except for one craniospinal patient were finished within 3.5 min.ConclusionsMCsquare was successfully commissioned for a synchrotron‐based proton beam therapy delivery system and integrated into our web‐based second check platform. After adopting CT resampling and implementing LET model‐dependent biological dose calculation capabilities, MCsquare will be sufficiently efficient and powerful to achieve Monte Carlo‐based and LET‐guided robust optimization in IMPT, which will be done in the future studies.