A telomere-targeting drug depletes cancer initiating cells and promotes anti-tumor immunity in small cell lung cancer.

There are few effective treatments for small cell lung cancer (SCLC) underscoring the need for innovative therapeutic approaches. This study focuses on exploiting telomerase, a critical SCLC dependency as a therapeutic target. A prominent characteristic of SCLC is their reliance on telomerase activity, a key enzyme essential for their continuous proliferation. Here we utilize a nucleoside analog, 6-Thio-2'-deoxyguanosine (6TdG) currently in phase II clinical trials, that is preferentially incorporated by telomerase into telomeres leading to telomere dysfunction. Using preclinical mouse and human derived models we find low intermittent doses of 6TdG inhibit tumor growth and reduce metastatic burden. Anti-tumor efficacy correlates with a reduction in a subpopulation of cancer initiating like cells (CICs) identified by their expression of L1CAM/CD133 and highest telomerase activity. 6TdG treatment also leads to activation of innate and adaptive anti-tumor responses. Mechanistically, 6TdG depletes CICs and induces type-I interferon signaling leading to tumor immune visibility by activating tumor cell STING signaling. We also observe increased sensitivity to irradiation after 6TdG treatment in both syngeneic and humanized SCLC xenograft models both of which are dependent on the presence of host immune cells. This study underscores the immune-enhancing and metastasis-reducing effects of 6TdG, employing a range of complementary in vitro and in vivo SCLC preclinical models providing a potential therapeutic approach to SCLC.

Assessment of the Cutaneous Hormone Landscapes and Microbiomes in Vulvar Lichen Sclerosus.

Vulvar lichen sclerosus (VLS) is a progressive skin disease of unknown etiology. In this longitudinal case-control exploratory study, we evaluated the hormonal and microbial landscapes in 18 postmenopausal females (mean [SD] age: 64.4 [8.4] years) with VLS and controls. We reevaluated the patients with VLS after 10-14 weeks of daily topical class I steroid. We found that groin cutaneous estrone was lower in VLS than in controls (-22.33, 95% confidence interval [CI] = -36.96 to -7.70; P = .006); cutaneous progesterone was higher (5.73, 95% CI = 3.74-7.73; P < .0001). Forehead 11-deoxycortisol (-0.24, 95% CI = -0.42 to -0.06; P = .01) and testosterone (-7.22, 95% CI = -12.83 to -1.62; P = .02) were lower in disease. With treatment, cutaneous estrone (-7.88, 95% CI = -44.07 to 28.31; P = .62), progesterone (2.02, 95% CI = -2.08 to 6.11; P = .29), and 11-deoxycortisol (-0.13, 95% CI = -0.32 to 0.05; P = .15) normalized; testosterone remained suppressed (-7.41, 95% CI = -13.38 to -1.43; P = .02). 16S ribosomal RNA V1-V3 and ITS1 amplicon sequencing revealed bacterial and fungal microbiome alterations in disease. Findings suggest that cutaneous sex hormone and bacterial microbiome alterations may be associated with VLS in postmenopausal females.

Lupus IgA1 autoantibodies synergize with IgG to enhance plasmacytoid dendritic cell responses to RNA-containing immune complexes.

Autoantibodies to nuclear antigens are hallmarks of systemic lupus erythematosus (SLE) where they contribute to pathogenesis. However, there remains a gap in our knowledge regarding how different isotypes of autoantibodies contribute to this autoimmune disease, including the production of the critical type I interferon (IFN) cytokines by plasmacytoid dendritic cells (pDCs) in response to immune complexes (ICs). We focused on IgA, which is the second-most prevalent isotype in serum and, along with IgG, is deposited in glomeruli in individuals with lupus nephritis. We show that individuals with SLE have serum IgA autoantibodies against most nuclear antigens, correlating with IgG against the same antigen. We investigated whether IgA autoantibodies against a major SLE autoantigen, Smith ribonucleoprotein (Sm/RNP), played a role in IC activation of pDCs. We found that pDCs expressed the IgA-specific Fc receptor, FcαR, and IgA1 autoantibodies synergized with IgG in RNA-containing ICs to generate robust primary blood pDC IFN-α responses in vitro. pDC responses to these ICs required both FcαR and FcγRIIa, showing synergy between these Fc receptors. Sm/RNP IC binding to and internalization by pDCs were greater when ICs contained both IgA1 and IgG. Circulating pDCs from individuals with SLE had higher binding of IgA1-containing ICs and higher expression of FcαR than pDCs from healthy control individuals. Although pDC FcαR expression correlated with the blood IFN-stimulated gene signature in SLE, Toll-like receptor 7 agonists, but not IFN-α, up-regulated pDC FcαR expression in vitro. Together, we show a mechanism by which IgA1 autoantibodies contribute to SLE pathogenesis.

Cmai: Predicting Antigen-Antibody Interactions from Massive Sequencing Data.

The interaction between antigens and antibodies (B cell receptors, BCRs) is the key step underlying the function of the humoral immune system in various biological contexts. The capability to profile the landscape of antigen-binding affinity of a vast number of BCRs will provide a powerful tool to reveal novel insights at unprecedented levels and will yield powerful tools for translational development. However, current experimental approaches for profiling antibody-antigen interactions are costly and time-consuming, and can only achieve low-to-mid throughput. On the other hand, bioinformatics tools in the field of antibody informatics mostly focus on optimization of antibodies given known binding antigens, which is a very different research question and of limited scope. In this work, we developed an innovative Artificial Intelligence tool, Cmai, to address the prediction of the binding between antibodies and antigens that can be scaled to high-throughput sequencing data. Cmai achieved an AUROC of 0.91 in our validation cohort. We devised a biomarker metric based on the output from Cmai applied to high-throughput BCR sequencing data. We found that, during immune-related adverse events (irAEs) caused by immune-checkpoint inhibitor (ICI) treatment, the humoral immunity is preferentially responsive to intracellular antigens from the organs affected by the irAEs. In contrast, extracellular antigens on malignant tumor cells are inducing B cell infiltrations, and the infiltrating B cells have a greater tendency to co-localize with tumor cells expressing these antigens. We further found that the abundance of tumor antigen-targeting antibodies is predictive of ICI treatment response. Overall, Cmai and our biomarker approach filled in a gap that is not addressed by current antibody optimization works nor works such as AlphaFold3 that predict the structures of complexes of proteins that are known to bind.