Citations

Survival outcomes for older adults with acute lymphoblastic leukemia (ALL) are poor and optimal management is challenging due to higher-risk leukemia genetics, comorbidities, and lower tolerance to intensive therapy. A critical understanding of these factors guides the selection of frontline therapies and subsequent treatment strategies. In addition, there have been recent developments in minimal/measurable residual disease (MRD) testing and blinatumomab use in the context of MRD-positive disease after therapy. These NCCN Guidelines Insights discuss recent updates to the NCCN Guidelines for ALL regarding upfront therapy in older adults and MRD monitoring/testing in response to ALL treatment.

BackgroundEsophageal carcinoma is the eighth most common cancer in the world. Volumetric‐modulated arc therapy (VMAT) is widely used to treat distal esophageal carcinoma due to high conformality to the target and good sparing of organs at risk (OAR). It is not clear if small‐spot intensity‐modulated proton therapy (IMPT) demonstrates a dosimetric advantage over VMAT. In this study, we compared dosimetric performance of VMAT and small‐spot IMPT for distal esophageal carcinoma in terms of plan quality, plan robustness, and interplay effects.Methods35 distal esophageal carcinoma patients were retrospectively reviewed; 19 patients received small‐spot IMPT and the remaining 16 of them received VMAT. Both plans were generated by delivering prescription doses to clinical target volumes (CTVs) on phase‐averaged 4D‐CT's. The dose‐volume‐histogram (DVH) band method was used to quantify plan robustness. Software was developed to evaluate interplay effects with randomized starting phases for each field per fraction. DVH indices were compared using Wilcoxon rank‐sum test. For fair comparison, all the treatment plans were normalized to have the same CTVhigh D95% in the nominal scenario relative to the prescription dose.ResultsIn the nominal scenario, small‐spot IMPT delivered statistically significantly lower liver Dmean and V30Gy[RBE], lung Dmean, heart Dmean compared with VMAT. CTVhigh dose homogeneity and protection of other OARs were comparable between the two treatments. In terms of plan robustness, the IMPT and VMAT plans were comparable for kidney V18Gy[RBE], liver V30Gy[RBE], stomach V45Gy[RBE], lung Dmean, V5Gy[RBE], and V20Gy[RBE], cord Dmax and , liver Dmean, heart V20Gy[RBE], and V30Gy[RBE], but IMPT was significantly worse for CTVhigh D95%, , and D5%‐D95%, CTVlow D95%, heart Dmean, and V40Gy[RBE], requiring careful and experienced adjustments during the planning process and robustness considerations. The small‐spot IMPT plans still met the standard clinical requirements after interplay effects were considered.ConclusionsSmall‐spot IMPT decreases doses to heart, liver, and total lung compared to VMAT as well as achieves clinically acceptable plan robustness. Our study supports the use of small‐spot IMPT for the treatment of distal esophageal carcinoma.

AKI is a global concern with a high incidence among patients across acute care settings. AKI is associated with significant clinical consequences and increased health care costs. Preventive measures, as well as rapid identification of AKI, have been shown to improve outcomes in small studies. Providing high-quality care for patients with AKI or those at risk of AKI occurs across a continuum that starts at the community level and continues in the emergency department, hospital setting, and after discharge from inpatient care. Improving the quality of care provided to these patients, plausibly mitigating the cost of care and improving short- and long-term outcomes, are goals that have not been universally achieved. Therefore, understanding how the management of AKI may be amenable to quality improvement programs is needed. Recognizing this gap in knowledge, the 22nd Acute Disease Quality Initiative meeting was convened to discuss the evidence, provide recommendations, and highlight future directions for AKI-related quality measures and care processes. Using a modified Delphi process, an international group of experts including physicians, a nurse practitioner, and pharmacists provided a framework for current and future quality improvement projects in the area of AKI. Where possible, best practices in the prevention, identification, and care of the patient with AKI were identified and highlighted. This article provides a summary of the key messages and recommendations of the group, with an aim to equip and encourage health care providers to establish quality care delivery for patients with AKI and to measure key quality indicators.

BackgroundInducible co-stimulator (ICOS) is a CD28-related molecule exclusively expressed on activated T cells and plays a critical role in modulating the immune response in breast cancer. The blockage of ICOS pathway has been shown to inhibit the activity of Type 2 T helper cells, thus potentially protecting against cancer growth. The current study aims to investigate the correlation between inducible co-stimulator ligand (ICOSL) expression in tumor tissues and the prognoses of patients with invasive breast cancer.MethodsTumor samples from 562 Chinese patients with invasive breast carcinomas were collected between 2003 and 2010. The expression of ICOSL on breast tumor and adjacent non-cancerous tissue was determined via immunohistochemistry. The overall survival (OS) of patients with positive and negative ICOSL expression were described using Kaplan–Meier curves, respectively. Parametric correlation method was used to analyze the correlation between ICOSL expression and other clinicopathological parameters. ICOSL was selected as a dependent variable for multivariate analysis.ResultsPositive ICOSL expression was identified on the plasma membrane in both cytoplasm and the nucleus of breast cancer cells. Membrane-expressed ICOSL is determined as an independent prognostic factor for OS in breast cancer but without significantly correlating with other clinicopathologic parameters such as age, menopausal status, depth of invasion, lymph node metastasis status, histologic classification, etc.ConclusionOur study suggests that the up-regulated expression of ICOSL protein in breast tumor cells can be associated with poor prognoses in invasive breast carcinomas.

Single cell sequencing is a technology capable of analyzing the genome of a single cell within a population. This technology is mostly integrated with microfluidics for precise cell manipulation and fluid handling. So far, most of the microfluidic-based single cell genomic studies have been focused on lab-cultured species or cell lines that are relatively easy to handle following standard microfluidic-based protocols without additional adjustments. The major challenges for performing single cell sequencing on clinical samples is the complex nature of the samples which requires additional sample processing steps to obtain intact single cells of interest without using amplification-inhibitive agents. Fluorescent-activated cell sorting is a common option to obtain single cells from clinical samples for single cell applications but requires >100 000 viable cells in suspension and the need for specialized laboratory and personnel. In this work, we present a protocol that can be used to obtain intact epithelial cells from snap-frozen postsurgical human endometrial tissues for single cell whole genome amplification. Our protocol includes sample thawing, cell dissociation, and labeling for genome amplification of targeted cells. Between 80% and 100% of single cell replicates lead to >25 ng of DNA after amplification with no measurable contamination, sufficient for downstream sequencing.

Abstract ctDNA analysis offers a non-invasive approach for monitoring response and resistance to treatment. Serial ctDNA testing during neoadjuvant therapy (NAT) may provide early indicators of emerging resistance and disease progression. In this study, we analyzed ctDNA from high-risk early breast cancer patients who received NAT and definitive surgery in the I-SPY 2 TRIAL (NCT01042379). We hypothesize that (1) assessment of ctDNA levels early in treatment will improve the performance of molecular and imaging-based predictors of pathologic complete response (pCR) to NAT; and (2) levels of ctDNA after NAT are associated with residual cancer burden and recurrence [distant recurrence free survival (DRFS)]. Methods: ctDNA analysis was performed in 84 high-risk stage II and III breast cancer patients randomized to neoadjuvant investigational agent (n=52), AKT inhibitor MK-2206 (M) in combination with paclitaxel (T) followed by doxorubicin and cyclophosphamide (AC) (M+T->AC), or standard-of-care (T->AC) (n=32). HER2+ patients also received trastuzumab (H). Serial plasma was collected before NAT (T0), early treatment (3 weeks, T1), between regimens (12 weeks, T2), and after NAT prior to surgery (T3). Mutational profiles derived from pretreatment tumor biopsy and normal matched DNA whole exome sequencing were used to design personalized assays targeting 16 patient-specific somatic variants to detect ctDNA in serial plasma. Results: Of the 84 patients in this study, 43% were HR-/HER2- (TNBC), 35% HR+/HER2-, and 23% HER2+. In total, 74% (61 of 83), 35% (28 of 79), 14% (9 of 65), and 8% (5 of 61) were positive for ctDNA at timepoints T0, T1, T2, and T3, respectively. At T0, ctDNA positivity and levels (average number of mutant molecules detected per mL) were significantly associated with increased tumor burden (by clinical and MRI examination), more aggressive tumor biology (as reflected in higher Mammaprint scores and grade) and subtype (HER2+ and TNBC). Twenty-seven percent (27%) of the 84 patients achieved a pCR and all patients who were ctDNA-positive at T3 (n=5) did not achieve a pCR. Currently, data are being collected to: (1) assess the relationship of ctDNA and MRI imaging in predicting tumor response to therapy; (2) examine the relationship of ctDNA levels before and after NAT with 3-year DRFS and event-free survival (EFS). The results of these analyses will be presented at the SABCS 2018 meeting. Conclusions: Our study provides a platform to evaluate the clinical significance of ctDNA for serial monitoring of response to NAT. Accurate and early response prediction by highly sensitive ctDNA analysis can facilitate a timely and judicious change in treatment to improve patients' chances of achieving a pCR. Finally, personalized ctDNA testing may complement imaging and pathologic evaluation of tumor response to fine-tune pCR as a surrogate endpoint for improved DRFS and EFS. Citation Format: Magbanua MJM, Brown-Swigart L, Hirst GL, Yau C, Wolf D, Ma AA, Bergin E, Venters S, Sethi H, Wu H-T, Salari R, Tin T, Sawyer S, Louie M, Zimmermann B, Lin C-HJ, Keats J, Liang WS, Cuyugan L, Enriquez D, Tripathy D, Chien AJ, Forero A, DeMichele A, Liu M, Delson AL, Asare S, Esserman L, van't Veer L, I-SPY 2 Consortium. Personalized serial circulating tumor DNA (ctDNA) analysis in high-risk early stage breast cancer patients to monitor and predict response to neoadjuvant therapy and outcome in the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD2-01.

Abstract Background: Late recurrence is characteristic of ER+ breast cancers. Despite an apparently effective adjuvant endocrine therapy, many breast cancers recur years after their initial endocrine treatment. Why some tumors recur early (<3 years) and some recur later (>5 years) is poorly understood. If systemic endocrine therapies killed all cells, recurrence would reflect only the appearance of new disease. Thus, we hypothesized that cells that survive and lie dormant may be driven, in part, by altered wiring of their cell death signaling. We, therefore, studied how cell death signaling is differentially wired in primary tumors that will recur early versus those that will recur later. Method: Genes involved in apoptosis, autophagy, ferroptosis, necrosis, and pyroptosis were identified from KEGG to initiate network feature analysis of gene expression data from public and our first in-house gene expression dataset. Data were collected from ER+ breast cancer pre-endocrine treatment samples with up to 20 years follow-up. Publicly available datasets used were GSE6532, GSE2034, GSE7390, GSE17705, GSE12093, and TCGA. We applied our Knowledge-fused Differential Dependency Network (KDDN) analysis tool to the public datasets; KDDN has provided powerful new insights into signaling in breast and other cancers. Common gene-gene interactions (edges) predicted in at least two different datasets were extracted from all KDDN analyses results. To strengthen the relevance of these features, predicted network edges that represent known protein-protein interactions (PPI) were identified from the STRING database, and these edges were noted in the signaling graphs. Final network graphs were constructed using the common edges from all overlaid networks. We conducted IPA analysis on all nodes in the final network and selected those incorporating network hubs. We took a similar approach to our second in-house dataset, which we used for independent testing. Here, patients were included if their tumor exhibited an initial reduction in volume of at least 40% by four months in response to neo-adjuvant Letrozole. Patients were then classified into two groups during follow-up of up to 3.7 years: i) initial tumor size reduction followed by continued response (expected to recur late); ii) initial reduction followed by tumor regrowth (expected to recur early). KDDN analysis was performed on pretreatment samples from these two groups and a network created annotated with PPI information. Results: MAPK8 and CYCS (Molecular Mechanisms of Cancer, p=1.58E-52), TNFRSF1A Neuroinflammation Signaling Pathway, p=1.26E-54), RELA, and NFKB1 (Colorectal Cancer Metastasis Signaling, p=7.94E-35), were identified as hubs. Hubs may be critical signaling components driving the differences between tumors that will become dormant and recur late. Connections between SLC25A6 and SQSTM1 (p = 0.008), BIRC2 and GABARAP (p = 0.021) in the early group, and AKT3 and IRS2 (p = 0.014) in the late group, were shared between the two final networks. With longer follow-up time on the second in-house dataset, we will better define the two groups and identify additional common phenotype specific gene-gene interactions. Citation Format: Clarke R, Dixon M, Jin L, Pearce D, Turnbull A, Selli C, Hu R, Zwart A, Wang Y, Xuan J, Sengupta S, Sims A, Liu MC. Local network topology differences between early and late recurrence in ER+ breast cancers [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-04-17.