David L. Porter
· MDVerifiedUniversity of Pennsylvania · Rehabilitation Medicine
Active 1959–2025
About
David L. Porter, MD, is the Jodi Fisher Horowitz Professor in Leukemia Care Excellence at the University of Pennsylvania. He serves as the Director of the Center for Cell Therapy and Transplant within the Department of Medicine at the Perelman School of Medicine. His educational background includes a B.A. in Biochemistry from the University of Rochester and an M.D. from Brown University. Dr. Porter is recognized for his contributions to leukemia treatment and cellular immunotherapy, with a focus on transplant and adoptive immunotherapy strategies. His work involves advancing therapies for hematologic malignancies, including leukemia, and improving outcomes through innovative cellular therapies and transplantation techniques.
Research topics
- Immunology
- Cancer research
- Medicine
- Internal medicine
- Biology
- Oncology
- Genetics
Selected publications
2025-12-11
articleOpen access<p>Pathways regulated by EGR2 in CD8+ CAR T-cells. (A-C) Top pathways differentially expressed in EGR2 knockout CD8+ CAR-T cells compared to AAVS1 knockout CAR T-cells. Libraries used in this enrichment analysis: A, Reactome 2016. B, NCI-Nature Pathway Interaction Database 2015. C, ARCHS4 transcription factor (TF) co-expression.</p>
Blood · 2025-11-03
articleOpen accessAbstract Introduction Pivotal trials that led to the approval of autologous anti-CD19 CAR T-cell therapy (CART) either excluded patients with prior CD19-directed therapy or required CD19 expression. Therefore, the activity of anti-CD19 CART in patients with CD19-negative lymphoma remains unknown. While due to practice heterogeneity and technical sensitivity, accurate detection of CD19 expression by immunohistochemistry (IHC) or flow cytometry may be limited, these are the only two assays clinically available. As CD19-negative large B-cell lymphoma (LBCL) cases are becoming increasingly frequent, we present the first retrospective multi-center real world experience using CART in patients with CD19-negative LBCL. Method Retrospective data from the Cell Therapy Consortium were utilized for this analysis. LBCL patients treated with autologous anti-CD19 CART in second line and beyond between April 2016 and June 2021, and with available CD19 expression status by either IHC or flow cytometry, were included in this study. Patients who had received prior CD19-directed therapy were excluded. Baseline characteristics prior to the initiation of lymphodepleting chemotherapy were collected. Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) were graded according to American Society for Transplantation and Cellular Therapy guidelines, and response was assessed by investigator according to the Lugano 2014 criteria. Chi-square test or Fisher's exact test was used to evaluate the association between baseline categorical characteristics and CD19 expression, while Wilcoxon rank sum test was used to evaluate the difference in continuous variables between CD19 expression groups. Log-rank test was used to compare the differences in progression-free survival (PFS) or overall survival (OS) between/among patient groups. Results Among 211 LBCL patients, 81 (38.4%) had CD19 status available by IHC, 193 (91.5%) by flow cytometry, and 63 (29.9%) by both. Of interest, no patient who received CART in the second line had CD19 status available, and all patients included in the analysis had received CART in the third line and beyond. Overall, 37 patients (17.5%) were CD19-negative before CAR T-cell therapy by either test. No significant differences in baseline characteristics were observed when comparing CD19-negative to CD19-positive cases, including age, sex, histology, product type, performance status, international prognostic index, refractory status, history of autologous or allogenic stem cell transplant, bridging therapy, and prior lines of treatment, except for a significantly lower median hemoglobin in CD19-positive patients (10.6 vs. 12.0 g/dL, p = 0.0054). CD19-negative patients experienced a 2-fold lower incidence of ICANS of any grade (21.6% vs. 43.1%, p = 0.0151) and over 5-fold lower G3-5 ICANS (5.4% vs. 28.7%, p = 0.0015). No significant differences in CRS of any grade (67.6% vs. 73.0%, p = 0.50), G3-4 CRS (5.4% vs. 8.0%, p = 0.74), and day-30 G3-4 cytopenia (40.0% vs. 54.0%, p = 0.24) were observed when comparing the two groups. At day-90 assessment, no difference in overall response rate (51.7% vs. 60.0%, p = 0.41) or complete response rate (37.9% vs. 51.1%, p = 0.20) was observed when comparing CD19-negative to CD19-positive patients. With a median follow up of 18.7 months (95% confidence interval 14.4 – 21.5), no significant difference in PFS (median 3.48 vs. 7.33 months, estimated 2-year 30.1% vs. 30.6%, p = 0.55) or OS (median 22.3 vs. 13.7 months, estimated 2-year 45.7% vs. 44.4%, p = 0.84) was observed when comparing the two groups. Conclusion Our large real-world experience shows that, when using IHC or flow cytometry for CD19 expression assessment, patients with CD19-negative LBCL experience lower ICANS rates with anti-CD19 CART, potentially due to lower CD19 density, but overall efficacy is comparable to what is observed in CD19-positive LBCL. While our results support the use of anti-CD19 CART in CD19-negative LBCL, future larger studies with more sensitive CD19 testing than IHC and/or flow cytometry are warranted.
Blood · 2025-11-03
articleOpen accessAbstract Emerging evidence implicates tissue resident memory T-cells (TRM) in chronic graft-versus host disease (cGVHD) immunopathology. While traditionally considered confined to tissues, recent studies indicate TRM can re-enter the circulation as “ex-TRM” in inflammatory conditions. However, the role of ex-TRM in cGVHD, and the link between peripheral blood (PB) and tissue-based immunopathology in cGVHD are not well understood. To identify and characterize ex-TRM in cGVHD, we utilized 10X Genomics 5' GEM-X technology to perform single-cell RNA sequencing (scRNA-Seq) and single-cell TCR sequencing (scTCR-Seq) on T-cell selected PBMC samples from patients with newly diagnosed, treatment-naive cGVHD (n=8) and post-allogeneic stem cell transplant (ASCT) matched controls (MC; n=5) who did not develop relapse or acute/chronic GVHD. Quality control (QC), normalization, clustering, principal component analysis, dimensionality reduction, and integration were performed with Seurat v5.2.1 in R v4.4.2. CD8+ effector memory (EM) subsets were re-clustered to enhance resolution for ex-TRM. TCR clonality was assessed in ScRepertoire, and antigen specificity was determined for alpha/beta TCR amino acid sequences using ImmuneWatch DETECT. Differences in continuous variables were assessed using the Wilcoxon rank-sum test, and Bonferroni correction was applied for differential gene expression (DGE) analysis. Significance was set at p &lt; 0.05 All patients received matched donor transplants and tacrolimus and methotrexate for GVHD prophylaxis. There were no significant differences between cGVHD and MC for age, sex, donor type (related vs. unrelated), CMV serostatus, conditioning regimen, or sample timepoint post-ASCT. After QC, 29,107 CD8+ T-cells (17,938 cGVHD and 11,1169 MC) were analyzed. Re-clustering of CD8+ EM cells revealed a distinct cluster expressing canonical TRM markers (CXCR6, ITGA1, ITGAE, CD69) as well as TRM-associated genes CXCL13 and CRTAM, consistent with ex-TRM. To further validate the TRM-like signature, we performed cluster-based module scoring using: 1) the top 100 upregulated genes from our recent publication in TRM vs. non-TRM in explanted lung tissue from pulmonary cGVHD and 2) the top 200 upregulated genes from an external dataset comparing lung TRM to circulating EM T-cells in healthy controls. Module scores for both gene sets were highest in the ex-TRM cluster, confirming TRM-like identity. The ex-TRM cluster included all cGVHD patients and MC in similar proportions. We then compared abundance and gene expression of ex-TRM in cGVHD patients and MC. Ex-TRM as a fraction of CD8+ EM was similar between groups (0.08 vs 0.09). However, cGVHD ex-TRM showed upregulation of cytotoxicity genes (GZMB, GNLY, PRF1), NK-like (NKL) markers (KLRD1, FGFBP2, NKG7), and T-cell exhaustion (Tex)-associated genes (DUSP4, HAVCR2). The median module score for an external Tex gene signature was higher in cGVHD than MC (0.029 vs 0.016, p &lt;0.001). DGE results were consistent after stratification by CMV serostatus. TCR analysis showed similar proportions of hyperexpanded (&gt;100 cells/clonotype) and large (20-100 cells/clonotype) clones in ex-TRM between conditions (30% versus 28%). Normalized entropy scores for ex-TRM were identical (0.92), indicating comparable repertoire diversity. However, hyperexpanded and large clones in cGVHD exhibited even greater upregulation of cytotoxicity, NKL, and Tex genes by log2 fold change than the overall ex-TRM population. Finally, ImmuneWatch DETECT did not find viral epitope-specific clonotypes in ex-TRM from cGVHD patients, suggesting that expansion may reflect alloantigen recognition. In conclusion, we identified circulating ex-TRM during post-ASCT immune reconstitution using canonical TRM markers and module scoring. In cGVHD, ex-TRM had a distinct cytotoxic, NKL, and Tex gene signature, supporting possible antecedent tissue antigen exposure and pathogenicity. Future work will explore protein level validation and assess phenotypic and clonal overlap between ex-TRM and bona fide TRM in affected tissues. With further validation, ex-TRM may provide a surrogate for tissue-resident populations and the foundation for non-invasive biomarkers in cGVHD.
2025-12-11
articleOpen access<p>Gene expression and pathway enrichment analysis of CD8+ T cell clusters. A, Heatmap showing differentially expressed genes between memory-like KLF2+ and exhausted-like MKI67+ CD8+ T-cells. Gene signature scores related to cell cycle and clinical response are indicated on the top bars. B, Top downregulated GO biological processes in EGR2 compared to AAVS1 knockout CAR T-cells.</p>
Blood · 2025-11-03
articleOpen accessAbstract Chimeric antigen T-cell receptor (CART) therapy is highly effective for pts (pts) with relapsed/refractory (R/R) lymphoma/multiple myeloma (MM). However, due to concerns regarding tolerability, older pts are underrepresented in CART trials and real-world studies indicate that CART is underutilized in older adults. Methods to assess fitness for CART are ECOG, clinician gestalt and age. There is interest in improving risk stratification of older adults using objective measures. Fried's frailty phenotype (FP) uses subjective (exhaustion, reported weight loss, activity level) and objective (gait speed, grip strength) measures to categorize pts into fit, pre-frail, and frail. We have previously shown that FP predicts for overall survival (OS) in older stem cell transplant (SCT) recipients. We hypothesize that FP will be associated with progression-free survival (PFS) and OS in older pts with lymphoma/MM undergoing CART therapy. We prospectively enrolled pts ≥ 60 years planned for CART for R/R lymphoma/MM from May 2019 – 2023 on a clinical trial. We performed FP prior to CART infusion, and at 7 days (d), 14d, 21d, 1 month (mo), 3mo, 6mo and 12mo post-infusion. 36 pts were enrolled with a median age at CART infusion of 69 years (Range 60-81). 53% of pts had MM, of whom 63% had intermediate or high-risk disease by R-ISS. The remainder had lymphoma (diffuse large B-cell or follicular lymphoma) with IPI &gt; 2 at diagnosis in 59%. Idecagtagene vicleucel and tisagenlecleucel were the most frequently administered CART products. Median follow up was 33mo. Median prior lines of therapy (LOT) was 3 (Range 1-7) and 47% had prior auto-SCT. Pre-infusion, majority had low ECOG scores (0-1, 81%), including 71% categorized as frail by FP. At pre-infusion FP, 35% of pts were fit (score 0), 44% were prefrail (score 1-2) and 21% were frail (score 3-5). Frail pts were more likely to be admitted for &gt;7d for their CART infusion (OR 7.0, 95% CI 1.02-47.97, p=0.04). Frailty was not associated with risk of CRS, ICANS or 30-day hospital readmission. 13 pts had died by the time of analysis; all but 2 deaths were related to progressive disease. 2 non-disease related deaths were 1 death from COVID and 1 ICANS-related death from teclistamab after relapse 1 year and 2 years after infusion, respectively. At Day 21 post-infusion, 21% were fit, 57% were prefrail, and 21% were frail. At 1mo post-infusion, 25% were fit, 63% were prefrail, and 13% were frail. Being frail by FP at pre-infusion (p&lt;0.001), Day 21 (p=0.03) or 1 month (p=0.009) post-infusion was associated with inferior OS from that time point. Median PFS in pre-infusion fit, prefrail, and frail pts were 23.4mo (95% CI 17.1-NR), 18.4mo (95% CI 6.8-13.8) and 4.0mo (95% CI 2.5-8.4), respectively. 2-year OS estimates were 100%, 93% and 14%, in fit, prefrail and frail pts respectively. 14 of 36 pts maintained or improved their FP from pre-infusion to 1mo; all but 3 received physical therapy (PT) while in hospital with 5 pts continuing PT outpatient. Notably, pts who maintained or improved their FP from pre-infusion to 1mo post-infusion had significantly better OS (p=0.05) than pts who had declines in their scores. Along with pre-infusion, day 21 and 1mo post-infusion FP scores, LDH (Mean 182 U/L) at the time of CART infusion was significantly associated with OS in the univariate Cox proportional hazards model (HR 5.22, 95% CI 1.43-19.18, p=0.013). Several factors including disease type, number of prior lines of therapy, use of bridging, stage at CART, IPI/RISS at diagnosis, HCT-CI, ECOG, presence of extra-nodal disease, CRS, ICANS, gender, age by decade, and BMI did not correlate with outcome. In pts ≥ 60 with R/R lymphoma/MM undergoing CART, 21% were frail by FP prior to CART. Frailty by FP pre-infusion, day 21 and 1mo post-infusion was associated with inferior OS as opposed to ECOG, HCT-CI, age or several disease related risk factors. FP may improve risk stratification in older adults undergoing CART. Pts with improvement in FP within 1mo post-infusion also had better outcomes. While better disease control could contribute to improved FP scores, most pts received PT to reverse frailty. Our future work aims to implement an exercise regimen to improve outcomes and to determine whether frailty is associated with adverse disease biology. Future work to uncover biologic mechanisms of frailty and adverse disease biology may identify novel targets for intervention to improve outcomes for frail pts.
2025-12-11
articleOpen access<p>Genes deferentially expressed in EGR2 compared to AAVS1 knockout CD8+ CAR T-cells. The corresponding log2 fold change values and statistical significance are provided for the listed genes.</p>
2025-12-11
articleOpen access<p>Analysis of survival outcomes and EGR2 gene expression in CD19 CAR T-cell products. The figure presents the P values and hazard ratio of different EGR2 molecular marker stratification points in relation to A, overall survival and B, event-free survival The black arrows indicate the stratification points used in the study. C, EGR2-targeted gene expression scores in CD19 CAR T-cell products from responders and non-responders in pediatric ALL. D, Summary of how EGR2 regulates resistance to CAR T-cell therapy through the type I IFN pathway.</p>
2025-12-11
articleOpen access<p>Epigenetic remodeling of CAR T-cells by EGR2 knockout and effect of type I IFN signaling on the development of memory and exhaustion. A, Volcano plots showing differentially accessible chromatin regions within genes between KLF2+ and MKI67+ CD8+ T-cells. B, Volcano plots depicting differentially accessible chromatin regions within genes between EGR2 and AAVS1 knockout (KO) CD8+ CAR T-cells. C, Representative contour plots showing frequencies of TIM3- and LAG3-expressing CD8+ CAR-T cells after exposure to IFNβ (1ng/mL) following chronic CAR stimulation. D, Proportions of CD27+ (left) or CD62L+ (right) CD8+ CAR-T cells after exposure to IFNβ. E, Representative contour plots showing frequencies of CD45RO+CD27+ CD8+ CAR-T cells after IFNAR blockade (Anifrolumab, 1µg/mL) during chronic antigen stimulation. F, Frequencies of TIM3+LAG3+ CD8+ CAR-T cells after IFNAR blockade. G, Cytolytic capacity of CAR T-cells as measured by normalized cell index kinetics using the xCELLigence real-time cytotoxicity assay following chronic stimulation with target cancer cells in the setting of either IFNβ or IFNAR blockade. H, Normalized cell index at 75 hours after challenge with target cancer cells. All experiments were conducted using healthy donor T-cells from independent donors (Mann-Whitney test, n = 4). *P < 0.05, *P < 0.01, ***P < 0.001, ns.: not significant.</p>
Match Stability with a Costly and Flexible Number of Positions
Games · 2025-05-21
articleOpen accessSenior authorCorrespondingOne of the main goals of two-sided matching mechanisms is to pair two groups of agents in a stable manner. Stability means that no pair of agents has an incentive to deviate from their assigned match. The outcome of such a match can have significant consequences for the participants involved. Most existing research in this field assumes that the quotas of organizations are fixed and externally determined, which may not always be realistic. We introduce the concept of slot stability, which considers the possibility that organizations may want to adjust their quotas after the match process. To address this issue, we propose an algorithm that generates both stable and slot-stable matches by using flexible, endogenous quotas.
2025-12-11
articleOpen access<p>Marker gene expression in CAR T-cell clusters. A, Uniform manifold approximation and projection (UMAP) plot of AAVS1 and EGR2 knockout (KO) CAR T-cell samples is shown. B, UMAP plots showing expression levels of CD4 and CD8. C, Violin plot depicting expression of cluster-defining markers in CD4+ T-cells. D, Differentially expressed genes in IL7R+ versus CTLA4+ CD4+ T-cells. E, Violin plots showing expression levels of cluster-defining markers in CD8+ T-cells. F, Heatmap displaying differentially expressed genes between CD8+ cell clusters. G, Cell cycle scores mapped on UMAP plots.</p>
Recent grants
NIH · $778k · 2012
NIH · $2.2M · 2017
Enhancing Chimeric Antigen Receptor T Cell Therapies for HematologicMalignancies: Beyond CART 19
NIH · $39.1M · 2017–2028
Frequent coauthors
- 231 shared
Noelle V. Frey
California University of Pennsylvania
- 154 shared
Elizabeth O. Hexner
University of Pennsylvania
- 137 shared
Stephen J. Schuster
University of Pennsylvania
- 133 shared
Carl H. June
Parker Institute for Cancer Immunotherapy
- 118 shared
Joseph A. Fraietta
University of Pennsylvania
- 104 shared
Sunita D. Nasta
University of Pennsylvania
- 103 shared
Stephan A. Grupp
Children's Hospital of Philadelphia
- 96 shared
Gabriela Plesa
Education
- 1987
MD
Brown University Warren Alpert Medical School
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
See your match with David L. Porter
PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.
- Free to start
- No credit card
- 30-second signup