Mansfield, Aaron S

Abstract Understanding how immune checkpoint inhibitors (ICIs) reshape human T-cell responses requires models that move beyond static transcriptomic snapshots and discrete cell-state classifications. Here, we present an integrative AI-enabled virtual cell framework that represents human CD8⁺ T-cell responses as dynamic and computable systems during ICI therapy. By integrating single-cell RNA sequencing with paired T-cell receptor sequencing within the C2S-scale foundation model, we construct a virtual representation of individual T cells, in which each cell is encoded by a unique functional identity that captures its transcriptional, signaling, and clonal characteristics. Using this framework, we identify a previously unrecognized dynamic latent effector state of CD8⁺ T cells characterized by intermediate expression of effector genes, distinct signaling activity, and ongoing clonal expansion. Across independent patient cohorts, the virtual cell model consistently indicates that ICI therapy mainly acts by unmasking pre-existing effector potential rather than inducing de novo effector differentiation. Notably, this latent effector population remains transcriptionally restrained despite active signaling and clonal expansion, revealing a hidden reservoir of antitumor immune capacity. More broadly, our study demonstrates how AI-enabled virtual cell modeling can reconstruct latent cellular states and their dynamic transitions from multidimensional single-cell data. By incorporating functional identity into virtual cell model, this framework uncovers biologically meaningful yet non-obvious T-cell effector program during cancer immunotherapy and provides a generalizable approach for studying immune dynamics in human disease.

Abstract Purpose: Circulating tumor fraction estimate (ctFE) is a machine learning–derived composite metric of circulating tumor DNA (ctDNA) burden. We hypothesized that pre-treatment and early on-treatment ctFE could robustly risk-stratify patients with locally advanced (LA) and oligometastatic non–small cell lung cancer (NSCLC) treated with radiotherapy (RT). Experimental Design: In a prospective phase II clinical trial (NCT03916419), 26 patients with unresectable stage IIB to IIIC NSCLC received magnetic resonance (MR)-guided hypofractionated chemoradiotherapy (chemoRT) followed by immunotherapy. Plasma ctDNA was profiled at baseline and mid-treatment (days 10–14) to derive ctFE and maximum variant allele frequency (Max VAF). A burden-based ctFE threshold derived from baseline samples was applied unchanged to mid-treatment samples and validated in two external cohorts: LA NSCLC treated with chemoRT (LA-RW; n = 94) and oligometastatic NSCLC treated with RT (OM-RW; n = 309). Results: Pre- and mid-treatment ctFE burden strongly stratified overall survival (OS) and progression-free survival (PFS), outperforming Max VAF and ctFE detectability. The baseline ctFE was prognostic for OS (HR 5.93, P = 0.005) and PFS (HR 11.08, P < 0.001) and remained significant at mid-treatment (OS: HR 7.08; PFS: HR 12.06; both P < 0.001). Early ctFE dynamics defined three molecular response groups with OS separation (median OS 60.8 vs. 13.0 vs. 2.9 months; P < 0.001). ctFE remained associated with survival in both validation cohorts. Conclusions: Early ctFE derived from a clinically available, tumor-naïve ctDNA assay enables noninvasive risk stratification in LA and oligometastatic NSCLC treated with RT, supporting its use as a practical biomarker for precision treatment adaptation.

RET fusions appear in 1%-2% of non–small cell lung cancers (NSCLCs). The results from the ARROW study (ClinicalTrials.gov identifier: NCT03037385 ) supported US Food and Drug Administration approval of pralsetinib, an oral selective RET inhibitor, for metastatic RET -altered NSCLC and RET fusion–positive thyroid cancers. ARROW was a phase I/II open-label study of pralsetinib 400 mg once daily in RET fusion–positive NSCLCs. Coprimary end points were overall response rate (ORR) and safety. Key secondary end points included duration of response, progression-free survival, and overall survival (OS). At data lock (May 20, 2024), 281 patients initiated pralsetinib (median treatment duration, 15.0 months). ORR (measurable disease patients; n = 259) was 78% (95% CI, 69 to 86) for treatment-naïve patients and 63% (95% CI, 54 to 71) for prior platinum-based chemotherapy patients. Median OS was 44.3 months (95% CI, 30.9 to 53.1), 50.1 months (95% CI, 28.3 to not reached) in treatment-naïve patients, and 39.7 months (95% CI, 27.8 to 53.2) in prior platinum patients. Common grade ≥3 treatment-related adverse events were anemia (21%), hypertension (15%), and decreased neutrophils (13%). Three treatment-related deaths occurred (pneumonia, n = 2; interstitial lung disease and rhabdomyolysis, n = 1 each). Safety was consistent with previous ARROW reports; no hypersensitivity was reported in patients receiving prior immunotherapies. Pralsetinib produced robust, durable responses with manageable safety in treatment-naïve and previously treated patients with RET fusion–positive NSCLCs, confirming previous findings with longer follow-up.

In this 5-year follow-up from the CheckMate 743 study in patients with unresectable pleural mesothelioma (PM), we evaluated updated efficacy and safety outcomes and biomarkers and performed treatment-switching analyses with first-line nivolumab plus ipilimumab versus chemotherapy. With a median follow-up of 66.8 months, nivolumab plus ipilimumab demonstrated continued overall survival (OS) benefit versus chemotherapy in all randomly assigned patients (5-year OS rates, 14% v 6%; hazard ratio [HR], 0.74 [95% CI, 0.62 to 0.88]); similar benefit was observed regardless of tumor histology. Of biomarker-evaluable patients treated with nivolumab plus ipilimumab (n = 242), high baseline monocytic myeloid-derived suppressor cell (M-MDSC) levels correlated with worse OS versus low M-MDSC levels (HR, 1.25 [95% CI, 1.09 to 1.43]). After adjusting for 24% of patients in the chemotherapy arm who received subsequent immunotherapy, nivolumab plus ipilimumab demonstrated continued OS benefit versus chemotherapy (HR, 0.64 [95% CI, 0.53 to 0.78]). No new safety signals were observed. These results demonstrate long-term, durable clinical benefit with nivolumab plus ipilimumab versus chemotherapy, which continued to be preserved even after treatment-switching adjustment in the chemotherapy arm. Exploratory analyses suggested greater benefit with nivolumab plus ipilimumab in the low M-MDSC subgroup. These results further support first-line nivolumab plus ipilimumab as standard of care for unresectable PM.

Convergent framework for future POC cancer diagnostics aligning clinical needs (why), enabling technologies (how), and translational bridges. It integrates lab-on-chip biosensing and analytics for decentralized, early, longitudinal care.

Abstract High-grade gliomas (HGGs) are aggressive tumors with poor outcomes and limited treatment options. Here, we combined genomic and transcriptomic tumor profiling with drug testing in a patient-derived 3-dimensional culture model to identify individualized treatments and predictive biomarkers. Activity of single agents targeting frequently dysregulated glioma pathways was relatively poor ex vivo and generally reflected historical patient data. However, compounds targeting PI3K, epigenetic, and survival/senescence signaling were effective in some cases. Drug sensitivity correlated with transcriptional rather than genomic features and suggested heterogeneity as a resistance mechanism. Bromodomain and extraterminal domain inhibition was particularly effective in tumors enriched in the mesenchymal transcriptional subtype, promoted proneural transition, and was overcome by upregulated PI3K signaling. Notably, combinations were largely effective, with 6 strategies exhibiting stronger efficacy than corresponding single agents in most cases (58-77%). This study identifies HGG vulnerabilities and associated biomarkers, resistance mechanisms, and effective combination strategies that warrant further clinical validation. Graphical Abstract

Abstract Purpose: Rearranged during transfection (RET) alterations are oncogenic drivers across solid tumors. Selective RET inhibitors (SRI) selpercatinib and pralsetinib have transformed outcomes for patients with RET-altered malignancies. Limited knowledge exists on genomic mechanisms of resistance to SRI. Experimental Design: We established “RETgistry,” a global consortium of patients with advanced RET-altered solid tumors who received SRI and underwent postprogression tissue or plasma biopsies assessed by next-generation sequencing. Frequencies of secondary RET resistance mutations and acquired non-RET gene alterations were determined. Progression-free survival (PFS) and time to treatment discontinuation (TTD) on first SRI were estimated with the Kaplan–Meier method. Results: RETgistry included 109 patients with RET-altered advanced solid tumors (lung, n = 94; thyroid, n = 15) who underwent 143 post-SRI progression biopsies (tissue, 91; plasma, 52). The median PFS and TTD were 13.9 months [95% confidence interval (CI), 10.1–16.6] and 17.3 months (95% CI, 14–20.2), respectively. Secondary RET mutations were detected in 20 (14%) biopsies [lung cancer, 15 (12.4%) and thyroid carcinoma, 5 (22.7%)]. Common acquired off-target alterations involved MET (18.2%; amplification, 15%), TP53 (8.2%), APC (7.6%), KRAS (7.1%), KEAP1 (5.9%), and CDKN2A/B (5.3%). MET alterations were enriched in post-SRI versus pre-SRI specimens (full cohort, 17.6% vs. 2.0%, P = 0.022; lung cancer, 19.1% vs. 2.1%, P = 0.022). Conclusions: The prevalence of secondary RET mutations after SRI was low, underscoring a greater role for off-target resistance. Recurrent acquired alterations involving tumor suppressor genes or upstream regulators of MAPK and PI3K pathways were identified, most commonly MET amplification. Continued efforts to characterize SRI resistance biology are critical to guide the development of novel therapeutic strategies.

ABSTRACTAnetumab ravtansine, like other ADC drugs, has high inter‐patient variability in its pharmacokinetic (PK) and pharmacodynamic (PD) outcomes, which raises concerns about whether current dosing regimens are optimal for patients. The objective of this study was to evaluate covariates, especially body habitus and the innate immune system (IIS), which may affect anetumab ravtansine PK and PD as part of two clinical trials in patients with ovarian cancer and mesothelioma. Biomarkers of Fcγ receptors(FcγR) CD64 on IIS cells, total body weight (TBW), body surface area (BSA), and other covariates, such as sex and age, were analyzed for an association with anetumab ravtansine PK. Higher FcγR CD64, TBW, and BSA were associated with higher clearance (CL) of anetumab ravtansine (p < 0.05). However, there was no relationship between TBW or BSA and FcγR CD64. Female patients had a lower anetumab ravtansine CL (0.030 ± 0.007 L/h) compared to male patients (0.042 ± 0.006 L/h) (p < 0.05). In both studies, patients with stable disease (SD) and partial response (PR) had higher anetumab ravtansine AUC0‐inf compared to patients with progressive disease (PD). Individualizing the dose of anetumab ravtansine and potentially other ADCs based only on TBW is not optimal, whereas precision dosing of an ADC based on the inclusion of novel metrics of IIS biomarkers, body habitus, and sex may be more appropriate to reduce variability in PK exposure, reduce toxicity, and improve response.