Biomedical subjects

Jeffrey A Meyerhardt

Publications and source records attributed to Jeffrey A Meyerhardt.

3 recordsLinked to original sources

PubMed2026

Addition of High-Dose Vitamin D3 to Standard Treatment in Patients With Metastatic Colorectal Cancer: The SOLARIS Randomized Clinical Trial (Alliance A021703).

IMPORTANCE: In a phase 2 randomized clinical trial, high-dose vitamin D3 added to standard treatment improved progression-free survival (PFS) compared with standard-dose vitamin D3 in patients with metastatic colorectal cancer (mCRC). OBJECTIVE: To determine if high-dose vitamin D3 added to standard chemotherapy improves outcomes in patients with previously untreated mCRC. DESIGN, SETTING, AND PARTICIPANTS: Double-blind phase 3 randomized clinical trial enrolling 455 patients with previously untreated mCRC, conducted in the US through the National Clinical Trials Network from October 2019 to December 2022 (database freeze: July 15, 2024). INTERVENTIONS: mFOLFOX6 (modified FOLFOX6 [5-fluorouracil, leucovorin, oxaliplatin]) or FOLFIRI (5-fluorouracil, leucovorin, irinotecan) plus bevacizumab every 2 weeks with either high-dose vitamin D3 (8000 IU daily × 14 days as loading dose followed by 4000 IU daily) or standard-dose vitamin D3 (400 IU daily) until disease progression, intolerable toxicity, or withdrawal of consent. MAIN OUTCOMES AND MEASURES: The primary end point was PFS assessed by the unstratified log-rank test. Secondary end points included objective response rate, overall survival, and toxicity. Prespecified subgroup analyses of PFS were performed according to known prognostic factors. RESULTS: Among 455 randomized patients (median age, 59 years; 181 [40%] female) with median follow-up 20 months, the median PFS for high-dose vitamin D3 (n = 228) was 11.8 months (95% CI, 10.3-13.3) vs 10.3 months (95% CI, 9.4-12.2) for standard-dose vitamin D3 (n = 227) (1-sided log-rank P = .25). There were no significant differences in objective response rate between high-dose and standard-dose vitamin D3 (51% [95% CI, 44%-58%] vs 44% [95% CI, 37%-50%], respectively; P = .12), or in overall survival (median, 25.6 vs 27.0 months; 1-sided log-rank P = .66). There were no clinically meaningful differences in the most common grade 3 or greater adverse events between the high- and standard-dose groups, including neutropenia (n = 67 [32%] vs n = 62 [30%]) and hypertension (n = 42 [20%] vs n = 49 [23%]) or in incidence of vitamin D-associated toxicities. CONCLUSIONS AND RELEVANCE: Among patients with previously untreated mCRC, addition of high-dose vitamin D3, vs standard-dose vitamin D3, to standard chemotherapy plus bevacizumab did not improve PFS. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04094688.

Aged↗

PubMed2026

Cabozantinib for advanced grade 3 neuroendocrine tumors: subgroup analysis of the phase 3 CABINET trial (Alliance A021602).

Well-differentiated grade 3 neuroendocrine tumors (NETs) have recently been described as a distinct category, and randomized data regarding efficacy of therapy for these patients are scarce. In the phase 3 CABINET trial, cabozantinib improved PFS compared with placebo in patients with advanced, previously treated, progressive extra-pancreatic NETs (epNETs) and pancreatic NETs (pNETs) of all grades. Here, we evaluate if these results remain consistent in a subgroup of patients with well-differentiated G3 NETs. Patients with locally advanced or metastatic epNETs or pNETs were randomized 2:1 in independent cohorts to receive cabozantinib 60 mg daily vs placebo. We analyzed outcomes of the subset of patients with G3 NETs (Ki-67 > 20%), combining patients in the pNET and epNET cohorts due to small sample sizes. Twenty-four patients had G3 NETs, 16 randomized to cabozantinib and 8 to placebo. Primary sites included pancreas (n = 12), GI tract (n = 7), unknown primary sites (n = 3), and lung/thymus (n = 2). Median PFS for patients with G3 NETs treated with cabozantinib was 7.9 vs 3 months with placebo (HR = 0.15, 95% CI: 0.04-0.57, 1-sided log-rank P = 0.0034). The confirmed overall radiographic response rate was 25% (4/16) with cabozantinib vs 0% (0/8) with placebo. Safety outcomes were consistent with published data for the trial as a whole. Subset analysis of the CABINET trial showed improved PFS associated with cabozantinib vs placebo for G3 NETs of pancreatic and extra-pancreatic origin. Despite limited numbers, these results suggest that cabozantinib can be an effective option for patients with advanced G3 NETs. ClinicalTrials.gov Identifier: NCT03375320.

Humans↗

PubMed2025

Tumor-immune partitioning and clustering algorithm for identifying tumor-immune cell spatial interaction signatures within the tumor microenvironment.

BACKGROUND: Growing evidence supports the importance of characterizing the organizational patterns of various cellular constituents in the tumor microenvironment in precision oncology. Most existing data on immune cell infiltrates in tumors, which are based on immune cell counts or nearest neighbor-type analyses, have failed to fully capture the cellular organization and heterogeneity. METHODS: We introduce a computational algorithm, termed Tumor-Immune Partitioning and Clustering (TIPC), that jointly measures immune cell partitioning between tumor epithelial and stromal areas and immune cell clustering versus dispersion. As proof-of-principle, we applied TIPC to a prospective cohort incident tumor biobank containing 931 colorectal carcinoma cases. TIPC identified tumor subtypes with unique spatial patterns between tumor cells and T lymphocytes linked to certain molecular pathologic and prognostic features. T lymphocyte identification and phenotyping were achieved using multiplexed (multispectral) immunofluorescence. In a separate hepatocellular carcinoma cohort, we replaced the stromal component with specific immune cell types-CXCR3+CD68+ or CD8+-to profile their spatial relationships with CXCL9+CD68+ cells. RESULTS: Six unsupervised TIPC subtypes based on T lymphocyte distribution patterns were identified, comprising two cold and four hot subtypes. Three of the four hot subtypes were associated with significantly longer colorectal cancer (CRC)-specific survival compared to a reference cold subtype. Our analysis showed that variations in T-cell densities among the TIPC subtypes did not strictly correlate with prognostic benefits, underscoring the prognostic significance of immune cell spatial patterns. Additionally, TIPC revealed two spatially distinct and cell density-specific subtypes among microsatellite instability-high colorectal cancers, indicating its potential to upgrade tumor subtyping. TIPC was also applied to additional immune cell types, eosinophils and neutrophils, identified using morphology and supervised machine learning; here two tumor subtypes with similarly low densities, namely 'cold, tumor-rich' and 'cold, stroma-rich', exhibited differential prognostic associations. Lastly, we validated our methods and results using The Cancer Genome Atlas colon and rectal adenocarcinoma data (n = 570). Moreover, applying TIPC to hepatocellular carcinoma cases (n = 27) highlighted critical cell interactions like CXCL9-CXCR3 and CXCL9-CD8. CONCLUSIONS: Unsupervised discoveries of microgeometric tissue organizational patterns and novel tumor subtypes using the TIPC algorithm can deepen our understanding of the tumor immune microenvironment and likely inform precision cancer immunotherapy.

Humans↗