An Antiherpesviral Host-Directed Strategy Based on CDK7 Covalently Binding Drugs: Target-Selective, Picomolar-Dose, Cross-Virus Reactivity.

The repertoire of currently available antiviral drugs spans therapeutic applications against a number of important human pathogens distributed worldwide. These include cases of the pandemic severe acute respiratory coronavirus type 2 (SARS-CoV-2 or COVID-19), human immunodeficiency virus type 1 (HIV-1 or AIDS), and the pregnancy- and posttransplant-relevant human cytomegalovirus (HCMV). In almost all cases, approved therapies are based on direct-acting antivirals (DAAs), but their benefit, particularly in long-term applications, is often limited by the induction of viral drug resistance or side effects. These issues might be addressed by the additional use of host-directed antivirals (HDAs). As a strong input from long-term experiences with cancer therapies, host protein kinases may serve as HDA targets of mechanistically new antiviral drugs. The study demonstrates such a novel antiviral strategy by targeting the major virus-supportive host kinase CDK7. Importantly, this strategy focuses on highly selective, 3D structure-derived CDK7 inhibitors carrying a warhead moiety that mediates covalent target binding. In summary, the main experimental findings of this study are as follows: (1) the in vitro verification of CDK7 inhibition and selectivity that confirms the warhead covalent-binding principle (by CDK-specific kinase assays), (2) the highly pronounced antiviral efficacies of the hit compounds (in cultured cell-based infection models) with half-maximal effective concentrations that reach down to picomolar levels, (3) a particularly strong potency of compounds against strains and reporter-expressing recombinants of HCMV (using infection assays in primary human fibroblasts), (4) additional activity against further herpesviruses such as animal CMVs and VZV, (5) unique mechanistic properties that include an immediate block of HCMV replication directed early (determined by Western blot detection of viral marker proteins), (6) a substantial drug synergism in combination with MBV (measured by a Loewe additivity fixed-dose assay), and (7) a strong sensitivity of clinically relevant HCMV mutants carrying MBV or ganciclovir resistance markers. Combined, the data highlight the huge developmental potential of this host-directed antiviral targeting concept utilizing covalently binding CDK7 inhibitors.

Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification.

OBJECTIVE: To evaluate performance of AI as a standalone reader in ultra-low-dose CT lung cancer baseline screening, and compare it to that of experienced radiologists. METHODS: 283 participants who underwent a baseline ultra-LDCT scan in Moscow Lung Cancer Screening, between February 2017-2018, and had at least one solid lung nodule, were included. Volumetric nodule measurements were performed by five experienced blinded radiologists, and independently assessed using an AI lung cancer screening prototype (AVIEW LCS, v1.0.34, Coreline Soft, Co. ltd, Seoul, Korea) to automatically detect, measure, and classify solid nodules. Discrepancies were stratified into two groups: positive-misclassification (PM); nodule classified by the reader as a NELSON-plus /EUPS-indeterminate/positive nodule, which at the reference consensus read was < 100 mm3, and negative-misclassification (NM); nodule classified as a NELSON-plus /EUPS-negative nodule, which at consensus read was ≥ 100 mm3. RESULTS: 1149 nodules with a solid-component were detected, of which 878 were classified as solid nodules. For the largest solid nodule per participant (n = 283); 61 [21.6 %; 53 PM, 8 NM] discrepancies were reported for AI as a standalone reader, compared to 43 [15.1 %; 22 PM, 21 NM], 36 [12.7 %; 25 PM, 11 NM], 29 [10.2 %; 25 PM, 4 NM], 28 [9.9 %; 6 PM, 22 NM], and 50 [17.7 %; 15 PM, 35 NM] discrepancies for readers 1, 2, 3, 4, and 5 respectively. CONCLUSION: Our results suggest that through the use of AI as an impartial reader in baseline lung cancer screening, negative-misclassification results could exceed that of four out of five experienced radiologists, and radiologists' workload could be drastically diminished by up to 86.7%.

Automated Detection Algorithm of Breast Masses in Three-Dimensional Ultrasound Images.

OBJECTIVES: We propose an automatic breast mass detection algorithm in three-dimensional (3D) ultrasound (US) images using the Hough transform technique. METHODS: One hundred twenty-five cropped images containing 68 benign and 60 malignant masses are acquired with clinical diagnosis by an experienced radiologist. The 3D US images are masked, subsampled, contrast-adjusted, and median-filtered as preprocessing steps before the Hough transform is used. Thereafter, we perform 3D Hough transform to detect spherical hyperplanes in 3D US breast image volumes, generate Hough spheres, and sort them in the order of votes. In order to reduce the number of the false positives in the breast mass detection algorithm, the Hough sphere with a mean or grey level value of the centroid higher than the mean of the 3D US image is excluded, and the remaining Hough sphere is converted into a circumscribing parallelepiped cube as breast mass lesion candidates. Finally, we examine whether or not the generated Hough cubes were overlapping each other geometrically, and the resulting Hough cubes are suggested as detected breast mass candidates. RESULTS: An automatic breast mass detection algorithm is applied with mass detection sensitivity of 96.1% at 0.84 false positives per case, quite comparable to the results in previous research, and we note that in the case of malignant breast mass detection, every malignant mass is detected with false positives per case at a rate of 0.62. CONCLUSIONS: The breast mass detection efficiency of our algorithm is assessed by performing a ROC analysis.

Sunlight UV-induced skin cancer relies upon activation of the p38α signaling pathway.

The activation of cellular signal transduction pathways by solar ultraviolet (SUV) irradiation plays a vital role in skin tumorigenesis. Although many pathways have been studied using pure ultraviolet A (UVA) or ultraviolet B (UVB) irradiation, the signaling pathways induced by SUV (i.e., sunlight) are not understood well enough to permit improvements for prevention, prognosis, and treatment. Here, we report parallel protein kinase array studies aimed at determining the dominant signaling pathway involved in SUV irradiation. Our results indicated that the p38-related signal transduction pathway was dramatically affected by SUV irradiation. SUV (60 kJ UVA/m(2)/3.6 kJ UVB/m(2)) irradiation stimulates phosphorylation of p38α (MAPK14) by 5.78-fold, MSK2 (RPS6KA4) by 6.38-fold, and HSP27 (HSPB1) by 34.56-fold compared with untreated controls. By investigating the tumorigenic role of SUV-induced signal transduction in wild-type and p38 dominant-negative (p38 DN) mice, we found that p38 blockade yielded fewer and smaller tumors. These results establish that p38 signaling is critical for SUV-induced skin carcinogenesis.