Imaging with [89Zr]Zr-DFO-SC16.56 anti-DLL3 antibody in patients with high-grade neuroendocrine tumours of the lung and prostate: a phase 1/2, first-in-human trial.

BACKGROUND: Delta-like ligand 3 (DLL3) is aberrantly expressed on the surface of small-cell lung cancer (SCLC) and neuroendocrine prostate cancer cells. We assessed the safety and feasibility of the DLL3-targeted imaging tracer [89Zr]Zr-DFO-SC16.56 (composed of the anti-DLL3 antibody SC16.56 conjugated to p-SCN-Bn-deferoxamine [DFO] serving as a chelator for zirconium-89) in patients with neuroendocrine-derived cancer. METHODS: We conducted an open-label, first-in-human study of immunoPET-CT imaging with [89Zr]Zr-DFO-SC16.56. The study was done at Memorial Sloan Kettering Cancer Center, New York, NY, USA. Patients aged 18 years or older with a histologically verified neuroendocrine-derived malignancy and an Eastern Cooperative Oncology Group performance status of 0-2 were eligible. An initial cohort of patients with SCLC (cohort 1) received 37-74 MBq [89Zr]Zr-DFO-SC16.56 as a single intravenous infusion at a total mass dose of 2·5 mg and had serial PET-CT scans at 1 h, day 1, day 3, and day 7 post-injection. The primary outcomes of phase 1 of the study (cohort 1) were to estimate terminal clearance half-time, determine whole organ time-integrated activity coefficients, and assess the safety of [89Zr]Zr-DFO-SC16.56. An expansion cohort of additional patients (with SCLC, neuroendocrine prostate cancer, atypical carcinoid tumours, and non-small-cell lung cancer; cohort 2) received a single infusion of [89Zr]Zr-DFO-SC16.56 at the same activity and mass dose as in the initial cohort followed by a single PET-CT scan 3-6 days later. Retrospectively collected tumour biopsy samples were assessed for DLL3 by immunohistochemistry. The primary outcome of phase 2 of the study in cohort 2 was to determine the potential association between tumour uptake of the tracer and intratumoural DLL3 protein expression, as determined by immunohistochemistry. This study is ongoing and is registered with ClinicalTrials.gov, NCT04199741. FINDINGS: Between Feb 11, 2020, and Jan 30, 2023, 12 (67%) men and six (33%) women were enrolled, with a median age of 64 years (range 23-81). Cohort 1 included three patients and cohort 2 included 15 additional patients. Imaging of the three patients with SCLC in cohort 1 showed strong tumour-specific uptake of [89Zr]Zr-DFO-SC16.56 at day 3 and day 7 post-injection. Serum clearance was biphasic with an estimated terminal clearance half-time of 119 h (SD 31). The highest mean absorbed dose was observed in the liver (1·83 mGy/MBq [SD 0·36]), and the mean effective dose was 0·49 mSv/MBq (SD 0·10). In cohort 2, a single immunoPET-CT scan on day 3-6 post-administration could delineate DLL3-avid tumours in 12 (80%) of 15 patients. Tumoural uptake varied between and within patients, and across anatomical sites, with a wide range in maximum standardised uptake value (from 3·3 to 66·7). Tumour uptake by [89Zr]Zr-DFO-SC16.56 was congruent with DLL3 immunohistochemistry in 15 (94%) of 16 patients with evaluable tissue. Two patients with non-avid DLL3 SCLC and neuroendocrine prostate cancer by PET scan showed the lowest DLL3 expression by tumour immunohistochemistry. One (6%) of 18 patients had a grade 1 allergic reaction; no grade 2 or worse adverse events were noted in either cohort. INTERPRETATION: DLL3 PET-CT imaging of patients with neuroendocrine cancers is safe and feasible. These results show the potential utility of [89Zr]Zr-DFO-SC16.56 for non-invasive in-vivo detection of DLL3-expressing malignancies. FUNDING: National Institutes of Health, Prostate Cancer Foundation, and Scannell Foundation.

First-in-human imaging with [89Zr]Zr-DFO-SC16.56 anti-DLL3 antibody in patients with high-grade neuroendocrine tumors of the lung and prostate.

Background: Delta-like ligand 3 (DLL3) is aberrantly expressed on the cell surface in many neuroendocrine cancers including small cell lung cancer (SCLC) and neuroendocrine prostate cancer (NEPC). Several therapeutic agents targeting DLL3 are in active clinical development. Molecular imaging of DLL3 would enable non-invasive diagnostic assessment to inform the use of DLL3-targeting therapeutics or to assess disease treatment response. Methods: We conducted a first-in-human immuno-positron emission tomography (immunoPET) imaging study of [89Zr]Zr-DFO-SC16.56, composed of the anti-DLL3 antibody SC16.56 conjugated to desferrioxamine (DFO) and the positron-emitting radionuclide zirconium-89, in 18 patients with neuroendocrine cancers. An initial cohort of three patients received 1-2 mCi of [89Zr]Zr-DFO-SC16.56 at a total mass dose of 2·5 mg and underwent serial PET and computed tomography (CT) imaging over the course of one week. Radiotracer clearance, tumor uptake, and radiation dosimetry were estimated. An expansion cohort of 15 additional patients were imaged using the initial activity and mass dose. Retrospectively collected tumor biopsies were assessed for DLL3 by immunohistochemistry (IHC) (n = 16). Findings: Imaging of the initial 3 SCLC patients demonstrated strong tumor-specific uptake of [89Zr]Zr-DFO-SC16.56, with similar tumor: background ratios at days 3, 4, and 7 post-injection. Serum clearance was bi-phasic with an estimated terminal clearance half-time of 119 h. The sites of highest background tracer uptake were blood pool and liver. The normal tissue receiving the highest radiation dose was liver; 1·8 mGy/MBq, and the effective dose was 0.49 mSv/MBq. Tumoral uptake varied both between and within patients, and across anatomic sites, with a wide range in SUVmax (from 3·3 to 66·7). Tumor uptake by [89Zr]Zr-DFO-SC16.56 was associated with protein expression in all cases. Two non-avid DLL3 NEPC cases by PET scanning demonstrated the lowest DLL3 expression by tumor immunohistochemistry. Only one patient had a grade 1 allergic reaction, while no grade ≥2 adverse events noted. Interpretation: DLL3 PET imaging of patients with neuroendocrine cancers is safe and feasible. These results demonstrate the potential utility of [89Zr]Zr-DFO-SC16.56 for non-invasive in vivo detection of DLL3-expressing malignancies. Funding: Supported by NIH R01CA213448 (JTP), R35 CA263816 (CMR), U24 CA213274 (CMR), R35 CA232130 (JSL), and a Prostate Cancer Foundation TACTICAL Award (JSL), Scannell foundation. The Radiochemistry and Molecular Imaging Probes Core Facility is supported by NIH P30 CA08748.

Thermal acclimation alters both basal heat shock protein gene expression and the heat shock response in juvenile lake whitefish (Coregonus clupeaformis).

Long-term temperature shifts associated with seasonal variability are common in temperate regions. However, these natural shifts could place significant strain on thermal stress responses of fishes when combined with mean increases in water temperatures predicted by climate change models. We examined the relationship between thermal acclimation, basal expression of heat shock protein (hsp) genes and the activation of the heat shock response (HSR) in lake whitefish (LWF; Coregonus clupeaformis), a cold water species of cultural and commercial significance. Juveniles were acclimated to either 6, 12, or 18°C water for several months prior to the quantification of hsp mRNA levels in the presence or absence of acute heat shock (HS). Acclimation to 18°C increased basal mRNA levels of hsp70 and hsp47, but not hsc70 or hsp90ß in gill, liver and white muscle, while 6°C acclimation had no effect on basal hsp transcription. Fish in all acclimation groups were capable of eliciting a robust HSR following acute HS, as indicated by the upregulation of hsp70 and hsp47. An increase of only 2°C above the 18°C acclimation temperature was required to trigger these transcriptional changes, suggesting that the HSR may be frequently initiated in LWF populations living at mildly elevated temperatures. Collectively, these expression profiles show that environmental temperature influences both basal hsp levels and the HSR in LWF, and indicate that these fish may have a greater physiological and ecological susceptibility to elevated temperatures than to cooler temperatures.

Divergence of Many-Body Perturbation Theory for Noncovalent Interactions of Large Molecules.

Prompted by recent reports of large errors in noncovalent interaction (NI) energies obtained from many-body perturbation theory (MBPT), we compare the performance of second-order MoÌ·ller-Plesset MBPT (MP2), spin-scaled MP2, dispersion-corrected semilocal density functional approximations (DFAs), and post-Kohn-Sham random phase approximation (RPA) for predicting binding energies of supramolecular complexes contained in the S66, L7, and S30L benchmarks. All binding energies are extrapolated to the basis set limit, corrected for basis set superposition errors, and compared to reference results of the domain-based local pair-natural orbital coupled-cluster (DLPNO-CCSD(T)) or better quality. Our results confirm that MP2 severely overestimates binding energies of large complexes, producing relative errors of over 100% for several benchmark compounds. RPA relative errors consistently range between 5 and 10%, significantly less than reported previously using smaller basis sets, whereas spin-scaled MP2 methods show limitations similar to MP2, albeit less pronounced, and empirically dispersion-corrected DFAs perform almost as well as RPA. Regression analysis reveals a systematic increase of relative MP2 binding energy errors with the system size at a rate of approximately 0.1% per valence electron, whereas the RPA and dispersion-corrected DFA relative errors are virtually independent of the system size. These observations are corroborated by a comparison of computed rotational constants of organic molecules to gas-phase spectroscopy data contained in the ROT34 benchmark. To analyze these results, an asymptotic adiabatic connection symmetry-adapted perturbation theory (AC-SAPT) is developed, which uses monomers at full coupling, whose ground-state density is constrained to the ground-state density of the complex. Using the fluctuation-dissipation theorem, we obtain a nonperturbative "screened second-order" expression for the dispersion energy in terms of monomer quantities, which is exact for non-overlapping subsystems and free of induction terms; a first-order RPA-like approximation to the Hartree, exchange, and correlation kernel recovers the macroscopic Lifshitz limit. The AC-SAPT expansion of the interaction energy is obtained from Taylor expansion of the coupling strength integrand. Explicit expressions for the convergence radius of the AC-SAPT series are derived within RPA and MBPT and numerically evaluated. While the AC-SAPT expansion is always convergent for nondegenerate monomers when RPA is used, it is found to spuriously diverge for second-order MBPT, except for the smallest and least polarizable monomers. The divergence of the AC-SAPT series for MBPT is numerically confirmed within RPA; prior numerical results on the convergence of the SAPT expansion for MBPT methods are revisited and support this conclusion once sufficiently high orders are included. The cause of the failure of MBPT methods for NIs of large systems is missing or incomplete "electrodynamic" screening of the Coulomb interaction due to induced particle-hole pairs between electrons in different monomers, leaving the effective interaction too strong for AC-SAPT to converge. Hence, MBPT cannot be considered reliable for quantitative predictions of NIs, even in moderately polarizable molecules with a few tens of atoms. The failure to accurately account for electrodynamic polarization makes MBPT qualitatively unsuitable for applications such as NIs of nanostructures, macromolecules, and soft materials; more robust nonperturbative approaches such as RPA or coupled cluster methods should be used instead whenever possible.

Performance and Scope of Perturbative Corrections to Random-Phase Approximation Energies.

It has been suspected since the early days of the random-phase approximation (RPA) that corrections to RPA correlation energies result mostly from short-range correlation effects and are thus amenable to perturbation theory. Here we test this hypothesis by analyzing formal and numerical results for the most common beyond-RPA perturbative corrections, including the bare second-order exchange (SOX), second-order screened exchange (SOSEX), and approximate exchange kernel (AXK) methods. Our analysis is facilitated by efficient and robust algorithms based on the resolution-of-the-identity (RI) approximation and numerical frequency integration, which enable benchmark beyond-RPA calculations on medium- and large-size molecules with size-independent accuracy. The AXK method systematically improves upon RPA, SOX, and SOSEX for reaction barrier heights, reaction energies, and noncovalent interaction energies of main-group compounds. The improved accuracy of AXK compared with SOX and SOSEX is attributed to stronger screening of bare SOX in AXK. For reactions involving transition-metal compounds, particularly 3d transition-metal dimers, the AXK correction is too small and can even have the wrong sign. These observations are rationalized by a measure α̅ of the effective coupling strength for beyond-RPA correlation. When the effective coupling strength increases beyond a critical α̅ value of approximately 0.5, the RPA errors increase rapidly and perturbative corrections become unreliable. Thus, perturbation theory can systematically correct RPA but only for systems and properties qualitatively well captured by RPA, as indicated by small α̅ values.

Random-Phase Approximation Methods.

Random-phase approximation (RPA) methods are rapidly emerging as cost-effective validation tools for semilocal density functional computations. We present the theoretical background of RPA in an intuitive rather than formal fashion, focusing on the physical picture of screening and simple diagrammatic analysis. A new decomposition of the RPA correlation energy into plasmonic modes leads to an appealing visualization of electron correlation in terms of charge density fluctuations. Recent developments in the areas of beyond-RPA methods, RPA correlation potentials, and efficient algorithms for RPA energy and property calculations are reviewed. The ability of RPA to approximately capture static correlation in molecules is quantified by an analysis of RPA natural occupation numbers. We illustrate the use of RPA methods in applications to small-gap systems such as open-shell d- and f-element compounds, radicals, and weakly bound complexes, where semilocal density functional results exhibit strong functional dependence.