Masha Kocherginsky

Germline GATA2 deficiency is a pleiotropic condition 1-8 characterized by numerous phenotypes, including monocytopenia, immunodeficiency, microbial susceptibilities, and high rates of myeloid malignancies 1,8. Accurate curation of germline GATA2 variants is critical for patient care and requires well-defined phenotypes associated with GATA2 deficiency. The many phenotypes attributed to the condition render a simple description of GATA2 deficiency difficult, complicating the development of GATA2 variant curation rules. Therefore, the Myeloid Malignancy Variant Curation Expert Panel (MM-VCEP) sought to define GATA2 deficiency based on a statistical comparison of phenotype data. To do so, the MM-VCEP systematically analyzed phenotype data and applied statistical comparisons to define the phenotypic features of GATA2 deficiency to inform germline variant curation. The MM-VCEP assembled an international cohort of 339 people with clinically diagnosed GATA2 deficiency from 16 centers in seven countries. The 73 phenotypes of these individuals were compared statistically to those of control participants from the UK Biobank (UKBB). We compared single phenotypes as well as combinations of two, three, and four phenotypes in people with clinically diagnosed GATA2 deficiency to UKBB controls. We defined GATA2 deficiency as any of the 2,903 combinations of two or three phenotypes with log10Odds Ratio ≥3 (OR ≥ 1000). This definition of GATA2 deficiency will inform gene-specific phenotypic criteria used in GATA2 variant curation guidelines that will facilitate standardized variant curation by clinical laboratories worldwide.

Hepatocellular carcinoma (HCC) is a lethal cancer with an increasing burden. Few clinical trials have evaluated preventive strategies for HCC in high-risk patients with liver cirrhosis. Observational studies show that statins are associated with a reduced HCC risk although a causal link has yet to be established. This multicenter randomized double-blinded, placebo-controlled phase II trial of 40 mg/day oral simvastatin to reduce the likelihood of hepatocarcinogenesis was conducted at four sites in the United States. The primary outcome was the change in serum α-fetoprotein (AFP)-L3% from baseline to 6 months. Secondary biomarker endpoints include changes in serum AFP, serum IL6, serum deoxycholic acid, liver stiffness, Model for End-Stage Liver Disease score, and Fibrosis-4 index score. Comparisons were made using paired t tests or the Wilcoxon rank-sum test. Forty-five participants completed the intervention and final study assessments [mean age, 58 years; female, 42%; Asian, 2.2%; Black or African American, 11%; White, 87%; Hispanic or Latino, 51%; Child-Pugh (CP) A, 69%; CP B, 16%]. Of 45 participants, 10 (22%) had detectable AFP-L3%, which did not differ between the intervention arms. Serum IL6 levels, detectable in all participants, decreased significantly in the simvastatin group compared with the placebo group (P = 0.02). The number and grade of adverse events did not differ between groups. In this randomized controlled trial, simvastatin was well tolerated in patients with liver cirrhosis but did not result in a decrease in AFP-L3%, potentially owing to the low number of participants with detectable AFP/AFP-L3%. Simvastatin did result in a decrease in IL6, offering one potential anticancer mechanism of simvastatin in the setting of cirrhosis. Prevention Relevance:Increasing liver cancer incidence parallels cirrhosis related to nonalcoholic steatohepatitis. Statins have the potential to arrest cirrhosis progression and prevent liver cancer. In a phase IIB trial randomizing patients with cirrhosis to simvastatin versus placebo, we found that simvastatin decreased the inflammation biomarker IL6, but not the primary endpoint of AFP-L3.

Supplemental Table 1. Study Participants Representativeness.

Hepatocellular carcinoma (HCC) is a lethal cancer with an increasing burden. Few clinical trials have evaluated preventive strategies for HCC in high-risk patients with liver cirrhosis. Observational studies show that statins are associated with a reduced HCC risk although a causal link has yet to be established. This multicenter randomized double-blinded, placebo-controlled phase II trial of 40 mg/day oral simvastatin to reduce the likelihood of hepatocarcinogenesis was conducted at four sites in the United States. The primary outcome was the change in serum α-fetoprotein (AFP)-L3% from baseline to 6 months. Secondary biomarker endpoints include changes in serum AFP, serum IL6, serum deoxycholic acid, liver stiffness, Model for End-Stage Liver Disease score, and Fibrosis-4 index score. Comparisons were made using paired t tests or the Wilcoxon rank-sum test. Forty-five participants completed the intervention and final study assessments [mean age, 58 years; female, 42%; Asian, 2.2%; Black or African American, 11%; White, 87%; Hispanic or Latino, 51%; Child-Pugh (CP) A, 69%; CP B, 16%]. Of 45 participants, 10 (22%) had detectable AFP-L3%, which did not differ between the intervention arms. Serum IL6 levels, detectable in all participants, decreased significantly in the simvastatin group compared with the placebo group (P = 0.02). The number and grade of adverse events did not differ between groups. In this randomized controlled trial, simvastatin was well tolerated in patients with liver cirrhosis but did not result in a decrease in AFP-L3%, potentially owing to the low number of participants with detectable AFP/AFP-L3%. Simvastatin did result in a decrease in IL6, offering one potential anticancer mechanism of simvastatin in the setting of cirrhosis. Prevention Relevance: Increasing liver cancer incidence parallels cirrhosis related to nonalcoholic steatohepatitis. Statins have the potential to arrest cirrhosis progression and prevent liver cancer. In a phase IIB trial randomizing patients with cirrhosis to simvastatin versus placebo, we found that simvastatin decreased the inflammation biomarker IL6, but not the primary endpoint of AFP-L3.

Schlafen 5 (SLFN5) is an important regulator of Type I interferon (IFN-I) signaling and tumorigenesis, yet the structural basis for its biologic activity remains unclear. Here, we dissect functional domains of SLFN5 and uncover a key role for its N-terminal Schlafen core domain in IFN-stimulated gene (ISG) expression and glioblastoma proliferation, independently of the SWAVDL motif and the C-terminal Walker A/B motifs. Partial deletions within the core domain or substitution of two arginine residues (R271E/R326E) near the zinc finger motif disrupt chromatin association and phenocopy SLFN5 loss, including de-repression of ISGs that act as immune checkpoints, such as PD-L1 and PD-L2. In contrast, the C-terminal ATPase/helicase activity is dispensable for transcriptional repression and tumor-promoting functions. Structural comparison of human and mouse SLFN5 revealed a conserved architecture, and experimental evidence demonstrates that murine SLFN5 is a functional ortholog of human SLFN5. These findings establish SLFN5 as a key transcriptional modulator of malignant glioblastoma growth by dampening IFN-I responses and have implications for the development of future immunotherapy approaches.

Endometrial cancer (EC) is rising both in incidence and mortality, is involving younger women, and is leading in the United States for gynecological cancer incidence. The application of molecular characterization and targeting treatment to selected molecular types of EC is exemplified by the marked benefit of mismatch repair deficient (dMMR) EC to immune checkpoint inhibitor (ICI) treatment. However, the response to immunotherapy has been less significant in other EC molecular types. We reported previously on the public health relevance of molecular analysis of endometrial cancer types to direct treatment considerations and discussed the limitation in biomarkers predictive of response to immunotherapy or available to examine for treatment selection, outside of mismatch repair deficiency. The current follow-on commentary addresses how new thinking can lead to optimization of immunotherapy applications for endometrial cancer molecular types, how to consider timing and sequencing of immunotherapy with other interventions, and directions for novel immunotherapy combinations. This report outlines key background studies and preclinical observations, directions to overcome inherent resistance, how to leverage ICI to augment clinical response to standard treatments, and considerations for how and when to re-expose patients to ICI treatment(s). The discussions led to potential clinical trial concepts now under development.

Effects of velcrin treatment on SLFN12 protein levels, PDE3A/B binding, and induction of cell death. A, HEL cells were treated with vehicle control (DMSO) or with the indicated doses of BAY 2666605 for 4 or 8 hours. Cell lysates were resolved by SDS-PAGE and immunoblotted with the indicated antibodies. GAPDH is shown as a loading control. B,SLFN12 mRNA expression of HEL cells after BAY 2666605 treatment at the indicated concentrations for 4 hours (left) or 8 hours (right). SLFN12 expression was assessed by qRT-PCR normalized to GAPDH and DMSO was used as a vehicle control (indicated by the dotted line). Data represent means ± SEM of three independent experiments, each conducted in triplicate. At each concentration, statistical significance was determined using a one-sample Student t test compared with 100%; ns, not significant. C, mRNA expression of respective genes in HEL cells transfected with a non-targeting siRNA control (indicated by the dotted line) and siRNA targeting PDE3A (left) or PDE3B (right). Data are expressed as the percentage of respective mRNA expression over non-targeting siRNA control (%) and represent means ± SEM of three independent experiments, each conducted in triplicate. Statistical significance was determined using a one-sample Student t test compared with 100%; ns, not significant, **, P ≤ 0.01. D, Immunoblot analysis of HEL cells. HEL cells were transfected with respective siRNA for 24 hours (see panel C), followed by 8 hours of low (1 μmol/L) or high (10 μmol/L) doses of BAY 2666605, using DMSO as a vehicle control. Cell lysates were resolved by SDS-PAGE and immunoblotted with the indicated antibodies (E). HEL (left) or U937 (right) cells were treated with vehicle control (DMSO) or with low (1 μmol/L) or high (10 μmol/L) concentrations of BAY 2666605 for 24 hours. Cell lysates were resolved by SDS-PAGE and immunoblotted with the indicated antibodies. F and G, Upon treatment with increasing doses of BAY 2666605 for 24 hours, HEL (F) and U937 (G) cells were stained with annexin V/propidium iodide and subjected to flow cytometry. The percentage of apoptotic cells for HEL (F) and U937 (G) cells treated with increasing BAY 2666605 concentrations is shown as mean ± SEM of three independent experiments. Statistical significance was determined using a one-way ANOVA, followed by a Dunnett multiple comparisons test to adjust for multiple comparisons for each dose vs. control; **, P ≤ 0.01; ****, P ≤ 0.0001. H and I, Co-immunoprecipitation analysis of SLFN12 interaction with (H) PDE3A in HEL cells or (I) PDE3B in U937 cells. HEL and U937 cells were treated with low (1 μmol/L) or high (10 μmol/L) concentrations of BAY 2666605 for 24 hours. DMSO was used as vehicle control. Cell lysates were used for immunoprecipitation with anti-PDE3A and anti-PDE3B antibodies or control rabbit immunoglobulin, as indicated. H, After probing for PDE3A, the membrane was stripped and reprobed with antibody for PDE3B. BAY, BAY 2666605; Cl casp-3, cleaved caspase-3; IP, immunoprecipitation; RIgG, rabbit immunoglobulin; WCL, whole-cell lysate.

Figure S1. Dot plot of HEL and U937 cells undergoing apoptosis.

Effects of velcrin treatment on SLFN12 expression in vivo. A, Schematic representation of the treatment regimen used for the xenograft AML mouse model using BAY 2666605 or vehicle control. B, Tumor growth curves of nude (NU/NU) mice treated and challenged with HEL cells. Each point represents the mean tumor volume ± SEM per group for vehicle control (5% ethanol with 95% polyethylene glycol-400)– and BAY 2666605–treated mice (n = 5 for control; n = 4 for treated). Pink bar indicates days in which mice were treated with BAY 2666605 or vehicle control. Tumor growth from the start of treatment (day 14) until the end of treatment (day 18) was analyzed using a mixed-effects linear regression model. Tumor volume was log-transformed to satisfy the normality assumption. Treatment group, time, and their interaction were included as fixed effects and mice as a random effect. The interaction was statistically significant (P < 0.001). The P value comparing treatments at day 18 is reported (*, P = 0.011). C, Tumor lysates from the experiment shown in panel (B) were subjected to SDS-PAGE and probed for SLFN12 protein expression. D, Tumor samples from the same experiment (n = 4 per group) were subjected to RNA-seq. Volcano plot shows the differentially up- or downregulated genes between the velcrin treatment group and the vehicle control group. Genes deemed statistically significant are highlighted in red. Data are from four biological replicates per group (see also Supplementary Fig. S2). E and F, Gene ontology (GO) analysis of differentially expressed genes that were (E) downregulated or (F) upregulated in mouse tumors treated with BAY 2666605 compared with vehicle control–treated mice. Relevant pathways associated with differentially expressed genes are underlined in red. BAY, BAY 2666605; SQ, subcutaneous. [A, Created in BioRender. Guillen Magana, J. (2025) https://BioRender.com/aqz79jx.]

Antileukemic activity of BAY 2666605 in vivo. A, Schematic representation of the experimental approach for the treatment regimen used for the xenograft AML mouse model. B, Tumor volumes (means ± SEM) are shown for mice treated with either vehicle control (5% ethanol with 95% polyethylene glycol-400) or BAY 2666605 (5 mg/kg; n = 10 per group). Pink bars indicate treatment window. Tumor growth from the start of treatment (day 13) until the end of treatment (day 24) was analyzed using a mixed-effects linear regression model. Tumor volume was log-transformed to satisfy the normality assumption. Treatment group, time, and their interaction were included as fixed effects and mice as a random effect. The interaction was statistically significant (P < 0.0001). The P values comparing treatments at each time point were adjusted for multiple comparisons using the Holm–Šídák method; *, P ≤ 0.05. Arrowheads indicate when mice were euthanized because of meeting study endpoints after tumor volume measurement. C, Kaplan–Meier survival analysis for mice treated with BAY 2666605 vs. vehicle control. Mice were compassionately euthanized once tumor volume was ≥2,000 mm3 or weight loss was greater than 20%; ***, P = 0.0004 using a Mantel–Cox (log-rank) test. D, Table summarizing estimated median survival (in days) of mice from each treatment group. BAY, BAY 2666605; SQ, subcutaneous. [A, Created in BioRender. Guillen Magana, J. (2025) https://BioRender.com/yw4tt0f.]