PURPOSE Oncology treatment pathways provide decision support and encourage guideline adherence. Pathway data combined with electronic health record (EHR) data can identify patient populations with poor prognoses, low serious illness conversation (SIC) rates, and high acute care utilization that may benefit from targeted interventions. PATIENTS AND METHODS We conducted a retrospective cohort analysis among adults with cancer treated at seven affiliated sites of the Dana-Farber Cancer Institute (DFCI) who had navigations within 21 treatment pathways between July 29, 2019, and March 8, 2023. DFCI clinicians previously identified pathway nodes with an estimated survival less than 1 year, termed poor prognosis (PP) nodes. We combined pathway data with EHR data to calculate the median overall survival (OS) and proportion of patients with SICs, acute care utilization (hospitalizations and emergency department visits), and outpatient palliative care 6 months after treatment node navigation for all, PP, and nonpoor prognosis (nPP) nodes. SICs were identified using the EHR advanced care planning (ACP) tab. RESULTS There were 15,261 navigations for 10,203 patients (median age 66 years, 55% female, 85% White). The median OS was 13.8 months for all nodes, 7.8 months for PP nodes, and 21.0 months for nPP nodes. The ACP section of the EHR rate 6 months after navigation was 19.6% for PP nodes versus 11.0% for nPP nodes. There was substantial intragroup variability in OS and SIC rates among all nodes. SICs were recorded in the ACP tab for only 34.3% of decedents. Patients who navigated to PP nodes had higher levels of acute care utilization and palliative care encounters. CONCLUSION Treatment pathway data enabled identification of patient populations with poor prognoses, low SIC rates, and high acute care utilization.

228 Background: Serious illness conversations (SICs) are discussions between oncology clinicians and patients with cancer about illness understanding and care preferences. SICs are associated with less intensive and more goal-concordant care near the end of life, but many patients die without an SIC. Methods: PATH-SIC is an ongoing, single-center randomized trial (NCT05629065) that enrolls adults without a documented SIC starting a treatment for breast, gastrointestinal, genitourinary, gynecologic, or lung cancers with an expected prognosis of less than one year. The trial examines the effects of clinician- and patient-nudges on SIC documentation within 60 days of patient’s randomization to one of four arms (no nudge, clinician nudge, patient nudge, or both). This embedded mixed methods study recruited patients who still did not have an SIC 60 days from randomization, their caregivers (if present at time of consent) and oncologists. Interviews explored patients’ and caregivers’ 1) experiences with SICs, 2) perceptions about why SICs may not occur, and 3) suggestions to empower others to initiate SICs. Participating oncologists were surveyed by email. We used qualitative content analysis and descriptive statistics to identify themes. Results: The study included 44 participants: 19 patients, 10 caregivers and 15 oncologists. Patients had a median age of 63 years, were 63% female and 58% White and 68% had gastrointestinal cancers. Though no patient had a documented SIC, patients and their oncologists often disagreed about whether an undocumented SIC had occurred previously (Table). Patients’ and caregivers’ reported barriers to SICs included patient factors (lack of readiness, desire to maintain hope, focus on the present), clinician factors (perceived discomfort with prognostic disclosure and SICs), and prognostic uncertainty (current disease control, unpredictable prognosis). Patients’ and caregivers’ reported facilitators to SICs included patient- (self-advocacy, SIC readiness), clinician- (comfortable rapport), disease- (progression, worsening symptoms), and family-related facilitators (advocates for the patient to engage in SICs). To increase SICs, patients and caregivers reported greater acceptance of interventions involving a personal touch (e.g. phone call) over automated processes. Oncologist survey responses were brief. They reported SICs were most frequently triggered by disease progression or treatment intolerance, and recommended longer appointment times and written materials to facilitate SIC. Conclusions: Patient, caregiver and oncologist feedback on barriers and facilitators to SICs provided useful insights to improve interventions to encourage SICs. Patient/oncologist dyad (n=16) concordance of prior SICs. # of dyads Agreed SIC occurred 7 Agreed SIC did not occur 2 Only oncologist reported SIC 6 Only patient reported SIC 1 Total patient/oncologist dyads 16

Purpose Serious illness conversations (SICs) are discussions between clinicians and cancer patients about illness understanding, information preferences, and goals of care. Interventions to prompt SICs increase SIC rates and improve care delivery near the end of life. This embedded sub-study examined SIC barriers and facilitators among “refractory” patients without an SIC despite enrollment in an SIC clinical trial. Design, Setting, and Population We recruited advanced cancer patients with no documented SIC 60 days after randomization in a clinical trial of patient- and clinician-nudges to engage in SICs. We conducted semi-structured interviews with patients and their caregivers if present and brief email surveys with patients’ oncologists. We used qualitative content analysis to identify themes related to SIC barriers and facilitators and to identify strategies to improve SICs. Results Of 44 participants, 19 were patients, 10 were caregivers, and 15 were oncologists. Themes of SIC barriers and facilitators included (1) how patients coped with their illness, which shaped their readiness for SICs; (2) clinician communication style, which shaped ease of having an SIC; (3) prognostic uncertainty and disease stability, which could prompt or justify delaying an SIC; and (4) family members’ presence, which could instigate an SIC. Regarding ways to improve SIC nudges, patients and caregivers had mixed perspectives but often highlighted a preference for interventions with personal touches. Conclusions Patient readiness remains an important barrier even after targeted SIC interventions. Future SIC interventions should consider approaches tailored to patient communication preferences and interventions involving personal interactions.

12027 Background: Treatment pathways are widely used to provide decision support and encourage guideline adherence. Pathways data may be used to identify patients for targeted interventions to improve cancer care. For example, pathways data may enable the identification of patients with poor prognoses for whom serious illness conversations (SICs) should be prioritized to ensure goal-concordant care. Methods: For patients starting new therapies at Dana-Farber, oncologists select a node in clinical pathways to indicate the line of treatment. Subspecialty oncologists identified “poor prognosis” nodes in pathways, defined as therapies for patients with expected survivals of < 12 months and for whom an SIC would be appropriate (e.g., 3 rd -line treatment for metastatic colon cancer). Pathway node navigations for patients with metastatic solid tumor malignancies with poor prognosis nodes (n = 21 disease pathways) were combined with electronic medical record data to identify SIC documentation in an advance care planning module within 6 months of pathway navigation and patients’ dates of death if present. For each node, we calculated the median overall survival (OS), the proportion of patients with an SIC, and the proportion of patients who died before reaching the next node. Results: There were 10,132 navigations for 7,031 patients (median age 67 years, 52% female, 86% White) between 8/16/2019 and 1/4/2023. With each treatment line, patients’ median OS decreased and SIC rates increased (examples for 3 diseases in Table). Among patients who reached poor prognosis nodes, the median OS was 4.9 months, mean SIC rate was 43.8%, and 60.2% of patients died without reaching a subsequent node. For nodes immediately prior to poor prognosis nodes, the median OS was 7.1 months, the mean SIC rate was 25.2%, and 31.3% of patients died without reaching the next node. 46.3% of patients died without reaching a poor prognosis node. The proportion of patients having an SIC at death was 40.9% among all decedents, 50.8% for decedents reaching a poor prognosis node, and 29.3% for decedents who do not reach a poor prognosis node. Conclusions: Clinical pathways can be used as a scalable method to identify patients with metastatic solid tumors and poor prognoses. In our study, only half of patients who reached a poor prognosis node had an SIC before death and nearly half of decedents never reached a poor prognosis node, underscoring the importance of identifying this population to improve end-of-life care. A clinical trial using pathways to identify and deliver interventions to increase SICs is ongoing. [Table: see text]

PDF file - 1196K, Supplementary Figure 1. Phenotypic analysis of FAP+ stromal cells in untreated TC1 flank tumors in C57BL/6 mice. Supplementary Figure 2. Depletion of FAP+ cells. Supplementary Figure 3. Persistence and antitumor activities of FAP-CAR T cells employing either human 4-1BB (73.3-hBBz) or mouse CD28 (73.3-m28z) co-stimulatory domain in mice and their in vitro activity. Supplementary Figure 4. Deletion of DGKzeta enhanced effector functions and in vivo persistence of FAP-CAR T cells. Supplementary Figure 5. Body weight of FAP-CAR T cells-treated mice remained constant or increased. Supplementary Figure 6. Histology of bone marrows and pancreas following treatment with FAP-CAR T cells. Supplementary Figure 7. Activation-induced cell death of FAP-CAR T cells. Supplementary Figure 8. Differential FAP expression on tumor and pancreatic FAP+ stromal cells. Supplementary Figure 9. mAb 73.3 and mAb FAP5 are specific for distinct epitopes of murine FAP expressed by fibroblasts.

BACKGROUND:The 2020-2021 residency application cycle was altered to reduce COVID-19 transmission, with moves to all virtual interviews and no away rotations for medical students. These changes may have affected how students ranked residency programs, such as choosing programs near their medical schools.OBJECTIVE:To determine if a larger percentage of medical students matched to residency programs in the same state as their medical schools in 2021 vs 2018-2020.METHODS:We searched the webpages or emailed student affairs deans of the 155 Liaison Committee on Medical Education accredited MD programs to attain medical school match lists. Differences in the percentage of students matching to residency programs in the same US state as their medical schools in 2021 vs 2018-2020 were compared using chi-square tests.RESULTS:We recorded 36 021 of 79 406 (45%) National Resident Matching Program, 759 of 1720 (44%) ophthalmology, and 586 urology MD residency matches between 2018 and 2021. The percentage of students matching to residency programs in the same state as their medical schools was 35.9% in 2021 versus 34.3% in 2018-2020 (P=.005). Students were more likely to match to programs in the same state as their medical schools in 2021 if they attended a public medical school (40.3% vs 38.5%, P=.009) or applied into specialties where ≥50% of students traditionally perform away rotations (32.2% vs 30.2%, P=.031).CONCLUSIONS:There was a small difference in the percentage of medical students matching to residency programs in the same state as their medical schools in 2021 vs 2018-2020.

e13580 Background: Patients with cancer are at greater risk of developing severe symptoms and dying from COVID-19 than the general population. Early detection of worsening symptoms and rapid nurse practitioner assessment may identify patients with cancer and suspected COVID-19 who require escalation of care while limiting strain on healthcare resources. Methods: We conducted a feasibility study of Cancer COVID Watch, an automated COVID-19 symptom monitoring program with oncology nurse practitioner-led triage among patients with cancer between April 23 and June 30, 2020. Oncology clinicians enrolled 34 patients who tested positive for COVID-19 or were experiencing symptoms concerning for COVID-19. Enrolled patients received twice daily automated text messages over 14 days that asked “How are you feeling compared to 12 hours ago? Better, worse, or the same?” and, if worse, “Is it harder than usual for you to breathe?” Patients who responded “worse” and “yes” were contacted within 1 hour by an oncology nurse practitioner to determine next steps in management. Chi-square and student t-tests are used to compare adherence, demographics, and outcomes between intervention responders and non-responders. Results: Mean age of patients was 62 years, 20 (59%) were female, 13 (38%) Black, 19 (56%) White, and mean ECOG was 1.2. 15 (44%) tested positive for COVID at the time of enrollment, 16 (47%) had a pending or scheduled test, and 2 (6%) tested negative but were enrolled due to concern of a false-negative test. 25 (74%) patients responded to ≥1 text message, and 24 (71%) responded to multiple messages. Patients were more likely to respond if they did not have an outpatient healthcare appointment within 14 days after enrollment (100% vs. 46%, p = 0.001) and if they had a pending or scheduled test versus a positive test at enrollment (88% vs. 53%, p = 0.04). 4 (12%) patients were escalated to the triage line: 1 was advised to present to the ED, and 3 were managed in the outpatient setting. 7 (21%) patients presented to the ED for infectious symptoms within 14 days of enrollment, and 2 (6%) were admitted for worsening COVID-19 symptoms. There was no difference in the ED presentation rate between patients who responded to ≥1 text message and those who did not (20% vs. 22%, p = 0.88). 3 (9%) patients died within 30 days of enrollment; no deaths were attributed to COVID. Participant satisfaction was high (Net Promoter Score 100, n = 4). Conclusions: Intensive remote symptom monitoring and rapid nurse practitioner triage for worsening symptoms is feasible for outpatients with cancer and suspected/confirmed COVID-19 infection. Patients with concerning symptoms were adherent with Cancer COVID Watch and mostly managed in the outpatient setting. Efforts to manage symptomatic patients with cancer during future pandemics could use a similar approach.

PURPOSEPatients with cancer are at greater risk of developing severe symptoms from COVID-19 than the general population. We developed and tested an automated text-based remote symptom-monitoring program to facilitate early detection of worsening symptoms and rapid assessment for patients with cancer and suspected or confirmed COVID-19.METHODSWe conducted a feasibility study of Cancer COVID Watch, an automated COVID-19 symptom-monitoring program with oncology nurse practitioner (NP)-led triage among patients with cancer between April 23 and June 30, 2020. Twenty-six patients with cancer and suspected or confirmed COVID-19 were enrolled. Enrolled patients received twice daily automated text messages over 14 days that asked “How are you feeling compared to 12 hours ago? Better, worse, or the same?” and, if worse, “Is it harder than usual for you to breathe?” Patients who responded worse and yes were contacted within 1 hour by an oncology NP.RESULTSMean age of patients was 62.5 years. Seventeen (65%) were female, 10 (38%) Black, and 15 (58%) White. Twenty-five (96%) patients responded to ≥ 1 symptom check-in, and overall response rate was 78%. Four (15%) patients were escalated to the triage line: one was advised to present to the emergency department (ED), and three were managed in the outpatient setting. Median time from escalation to triage call was 11.5 minutes. Four (15%) patients presented to the ED without first escalating their care via our program. Participant satisfaction was high (Net Promoter Score: 100, n = 4).CONCLUSIONImplementation of an intensive remote symptom monitoring and rapid NP triage program for outpatients with cancer and suspected or confirmed COVID-19 infection is possible. Similar tools may facilitate more rapid triage for patients with cancer in future pandemics.

Due to the global shortage of PPE caused by increasing number of COVID-19 patients in recent months, many hospitals have had difficulty procuring adequate PPE for the clinicians who care for these patients. Faced with a shortage, hospitals have had to implement new PPE conservation policies. In this paper, we describe a tool to help hospitals better project PPE needs under various conservation policies. Though this tool is built on top of projections of the number of hospitalized COVID-19 patients, it is agnostic as to which model--of which many are available--provides these projections. The tool combines COVID-19 patient census projections with information like staffing ratios and frequency of patient contact to provide projections of the number of items of key types of PPE needed under three built-in conservation scenarios: standard, contingency, and crisis. Users are also able to customize the tool to the specifics of their hospital and design custom conservation policies.

Due to the global shortage of PPE caused by increasing number of COVID-19 patients in recent months, many hospitals have had difficulty procuring adequate PPE for the clinicians who care for these patients. Faced with a shortage, hospitals have had to implement new PPE conservation policies. In this paper, we describe a tool to help hospitals better project PPE needs under various conservation policies. Though this tool is built on top of projections of the number of hospitalized COVID-19 patients, it is agnostic as to which model—of which many are available—provides these projections. The tool combines COVID-19 patient census projections with information like staffing ratios and frequency of patient contact to provide projections of the number of items of key types of PPE needed under three built-in conservation scenarios: standard, contingency, and crisis. Users are also able to customize the tool to the specifics of their hospital and design custom conservation policies. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement his work was partially supported by grant R01ES028804-03S1 from the National Institutes of Environmental Health Sciences of the United States National Institutes of Health. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This research did not require IRB oversight, as no data on individuals (human or animal) was collected or accessed. Only information, such as typical shift lengths and staffing ratios, was used. We also used information on recommended usage of several PPE products, which also does not involve any subjects. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data used in this manuscript is given in the appendix.

Rationale: Low and slow patient enrollment remains a barrier to critical care randomized controlled trials (RCTs). Behavioral economic insights suggest that nudges may address some enrollment challenges. Objectives: To evaluate the efficacy of a novel preconsent survey consisting of nudges on critical care RCT enrollment. Methods: We conducted an RCT in 10 intensive care units (ICUs) among surrogate decision-makers (SDMs). The novel multicomponent behavioral nudge survey was administered immediately before soliciting SDMs' informed consent for their patients' participation in a sham trial of two mechanical ventilation weaning approaches in acute respiratory failure. The primary outcome was the enrollment rate for the sham trial. Secondary outcomes included undue and unjust inducements. We also explored SDM and patient predictors of enrollment using multivariate regression. Results: Among 182 SDMs, 93 were randomized to receive the intervention survey and 89 to receive standard informed consent. There was no statistically significant difference in enrollment rates between the intervention (29%) and standard consent (34%) groups (percentage difference, 5%; 95% confidence interval (CI], -9% to 18%; P = 0.50). There was no evidence of undue or unjust inducement. 'White SDMs were more likely to enroll the patient compared with non-white SDMs (odds ratio, 3.7; 95% CI, 1.1 to 12.2; P=0.03). SDMs who perceived a higher risk of participation were less likely to enroll the patient (odds ratio, 0.57; 95% CI, 0.46 to 0.71; P< 0.001). Conclusions: A preconsent behavioral nudge survey among SDMs of patients with acute respiratory failure in the ICU did not increase enrollment rates for a sham RCT compared with standard informed consent procedures.

391 Background: Approximately 30 – 60% of patients with mNSGCT treated with cisplatin-based chemotherapy (CBCT) achieve a complete response (CR), defined as normalization of serum tumor markers with either no RRM or a RRM < 1 cm. While there is universal agreement that patients with a RRM ≥ 1 cm should undergo retroperitoneal lymph node dissection (RPLND), many institutions, including ours, recommend surveillance for patients who achieve a CR. However, studies have not defined which axis of the RRM should be considered when making this decision. Methods: The electronic medical records (2007 – 2017) at the Hospital of the University of Pennsylvania (HUP) were searched to identify good-risk mNSGCT patients treated with CBCT who achieved a CR and underwent surveillance. Consistent with RECIST 1.1, we define a CR as no RRM or a RRM < 1 cm in the transaxial short axis (TSA). We do not consider the transaxial long axis (TLA) or the craniocaudal axis (CCA). A post-hoc review was performed by a blinded radiologist and the RRM dimensions in the TSA, TLA, and CCA were recorded. Differences in the frequency of recurrence between groups with a RRM < 1.0 cm and ≥ 1.0 cm in the TLA and CCA were assessed using the Fischer exact test. Results: 39 patients met study criteria and were included. At a median follow-up of 50.8 months, only 2 patients (5.1%) recurred. Both were successfully treated with RPLND and salvage chemotherapy. Post-hoc review of imaging: median TSA 6 mm (range, 0-11); median TLA 8 mm (range, 0-14); median CCA 11 mm (range, 0-34). Thirteen (33%) and 27 (69%) patients had a RRM ≥ 1 cm in the TLA and CCA, respectively. There were no statistically significant differences in the risk of recurrence between patients with a RRM < 1.0 cm and ≥ 1.0 cm in the TLA (p=0.54) or CCA (p=0.53). Conclusions: Surveillance is an effective strategy in patients with mNSGCT and a post-chemotherapy RRM < 1.0 cm in the TSA. Our study suggests that referencing the TSA and not the TLA or CCA in this decision-making may avoid unnecessary post-chemotherapy RPLND.

Background: Approximately 70% to 80% of patients with metastatic nonseminomatous germ cell tumor (NSGCT) treated with cisplatin-based chemotherapy achieve a complete response, defined as normalization of serum tumor markers and either no residual retroperitoneal mass (RRM) or an RRM < 1.0 cm. While there is universal agreement that patients with an RRM >= 1.0 cm should undergo retroperitoneal lymph node dissection (RPLND), many institutions including ours recommend surveillance for patients who achieve a complete response. However, studies have not defined which axis of the RRM should be considered when deciding between surveillance and RPLND. Patients and Methods: Good-risk metastatic NSGCT patients treated with cisplatin-based chemotherapy who achieved a complete response and underwent surveillance were identified using our institution's electronic medical records. A post-hoc review was performed by a blinded radiologist. The RRM dimensions in the transaxial short axis (TSA), transaxial long axis (TLA), and craniocaudal axis (CCA) were recorded. Differences in the frequency of recurrence between groups with an RRM <1.0 cm and >= 1.0 cm in the TLA and CCA were assessed using the Fisher exact test. Results: Thirty-nine patients who met study criteria were included. At a median follow-up of 63.8 months, 2 patients (5.1%) recurred. Both were successfully treated with salvage chemotherapy and RPLND. Thirteen (33%) and 27 (69%) patients had an RRM >= 1.0 cm in the TLA and CCA, respectively. There were no statistically significant differences in the risk of recurrence between patients with an RRM < 1.0 cm and >= 1.0 cm in the TLA (P = 0.54) or CCA (P = 0.53). Conclusions: Surveillance is an effective strategy in good-risk NSGCT patients with a postchemotherapy RRM < 1.0 cm in the TSA. Our study suggests referencing the TSA and not the TLA or CCA may avoid unnecessary postchemotherapy RPLNDs. (C) 2020 Elsevier Inc. All rights reserved.

Abstract Introduction: Juvenile myelomonocytic leukemia (JMML) is a rare hematological malignancy of early childhood with characteristics of both myeloproliferative neoplasms and myelodysplastic syndromes. JMML shares pathological features and diagnostic criteria with chronic myelomonocytic leukemia (CMML), a malignancy predominantly affecting the elderly. While 85% of patients with JMML have somatic or germline mutations in RAS pathway genes (NF1, NRAS, KRAS, PTPN11, and CBL), the most frequently mutated genes in CMML include TET2, SRSF2, ASXL1, and RAS and are generally somatic-only. The extent to which histone modification genes (ASXL1, EZH2) or spliceosome machinery genes (SF3B1, SRSF2, U2AF1, ZRSR2) play a role in JMML pathogenesis is unclear. Despite mutational differences, both JMML and CMML manifest as myelomonocytic proliferation with varying amounts of dysplasia in the bone marrow. Clusters of clonally-related CD123+ plasmacytoid dendritic cells (PDCs) have been observed in the bone marrow of patients with CMML but have not been investigated in JMML. Here, we report the mutation profiles and immunophenotypic characteristics of JMML specimens from children treated at our institution. Methods: The pathology archives (1987-2017) at the Children's Hospital of Philadelphia (CHOP) were searched to identify JMML cases (n=21) and included formalin fixed paraffin-embedded diagnostic bone marrow biopsies and splenectomy tissue obtained prior to hematopoietic stem cell transplant. JMML diagnosis was confirmed in all cases by clinicopathological review. Cytogenetic analysis and whole genome SNP array were performed at initial clinical presentation. Genomic DNA and RNA were extracted from JMML patients' bone marrow (n=8) and spleen tissue (n=10) for next-generation sequencing analysis of 118 cancer genes for sequence and copy number variants and 110 genes for known and novel fusions via our custom CHOP Hematologic Cancer Panel. CD123 immunohistochemical (IHC) staining was performed on bone marrow and spleen tissues from children with JMML. Presence of CD123+ PDC clusters was evaluated manually and by digital image analysis. CD123 staining was enumerated using the Aperio Image Scope quantitation of membranous staining v9 with the analysis parameters set such that normal endothelial staining was quantified as 1+, and true CD123 staining cells were quantified as 2+ or 3+. The percentage of CD123+ cells (out of total cellularity) was calculated. Bone marrow from patients with non-JMML myeloid malignancies (n=6) and splenectomy tissue from patients with sickle cell anemia (n=8) were used as controls for the CD123 IHC analysis. Results: We confirmed canonical JMML-associated somatic or germline NF1 (n=3), NRAS (n=4), KRAS (n=2), PTPN11 (n=6), or CBL (n=2) mutations in 16 of the 17 (94%) patients with sequencing data. Interestingly, both PTPN11A72T and NF1R2637* mutations were detected in one patient. In addition, we found potential variants in genes affecting histone modifications (ASXL1, DNMT3A, KDM6A, SETD2), spliceosomal processes (SF3B1, U2AF1), transcription (BCOR, RUNX1, ETV6), or cellular growth (SETBP1, BRAF) in 8/17 patients (47%). While mutations in these genes have been well-characterized in other myeloid disorders, many of these alterations have not been reported to date in children with JMML or are currently of unclear biologic and prognostic significance. We also observed increased clustering of CD123+ PDCs in bone marrow and spleens from patients with JMML compared to IHC staining of control tissues. 2.2 ± 0.42% and 1.8 ± 0.74% of cells expressed CD123 in the spleen and bone marrow specimens, respectively. Control bone marrow and spleen samples did not show significant CD123+ staining. Conclusions: Our study demonstrates frequent variants in histone modification, splicing, and transcription-associated genes in JMML specimens in addition to known pathogenic RAS pathway mutations. We further report histopathologic CD123+ PDC clustering in JMML specimens analogous to that observed in CMML, which may aid in the workup of this often difficult-to-diagnose disease. Our findings of genetic and immunophenotypic overlap between JMML and CMML suggest similarities in pathogenesis despite typical presentation at extremes of age. Disclosures Tasian: Aleta Biopharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Gilead Sciences: Research Funding; Incyte Corporation: Research Funding.

Abstract The majority of chimeric antigen receptor (CAR) T-cell research has focused on attacking cancer cells. Here, we show that targeting the tumor-promoting, nontransformed stromal cells using CAR T cells may offer several advantages. We developed a retroviral CAR construct specific for the mouse fibroblast activation protein (FAP), comprising a single-chain Fv FAP [monoclonal antibody (mAb) 73.3] with the CD8α hinge and transmembrane regions, and the human CD3ζ and 4-1BB activation domains. The transduced muFAP-CAR mouse T cells secreted IFN-γ and killed FAP-expressing 3T3 target cells specifically. Adoptively transferred 73.3-FAP-CAR mouse T cells selectively reduced FAPhi stromal cells and inhibited the growth of multiple types of subcutaneously transplanted tumors in wild-type, but not FAP-null immune-competent syngeneic mice. The antitumor effects could be augmented by multiple injections of the CAR T cells, by using CAR T cells with a deficiency in diacylglycerol kinase, or by combination with a vaccine. A major mechanism of action of the muFAP-CAR T cells was the augmentation of the endogenous CD8+ T-cell antitumor responses. Off-tumor toxicity in our models was minimal following muFAP-CAR T-cell therapy. In summary, inhibiting tumor growth by targeting tumor stroma with adoptively transferred CAR T cells directed to FAP can be safe and effective, suggesting that further clinical development of anti-human FAP-CAR is warranted. Cancer Immunol Res; 2(2); 154–66. ©2013 AACR.