Failure of the posterior rods in long thoracolumbar deformity correction cases often requires revision surgery to treat the pseudoarthrosis and prevent loss of correction. While the entire rod can be replaced, this involves opening the entire incision which can lead to increased morbidity. Other clinically advantageous options include minimally invasive surgical approaches such as percutaneous insertion of connectors and additional rods.

Spinal Deformity

Rod

10.1115/sbc2010-19131

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Data from Epigenetic Targeting of Adipocytes Inhibits High-Grade Serous Ovarian Cancer Cell Migration and Invasion

Jessica Tang Nicholas Pulliam Ali Özeş Aaron Buechlein Ning Ding

<div>AbstractOvarian cancer (OC) cells frequently metastasize to the omentum, and adipocytes play a significant role in ovarian tumor progression. Therapeutic interventions targeting aberrant DNA methylation in ovarian tumors have shown promise in the clinic, but the effects of epigenetic therapy on the tumor microenvironment are understudied. Here, we examined the effect of adipocytes on OC cell behavior in culture and impact of targeting DNA methylation in adipocytes on OC metastasis. The presence of adipocytes increased OC cell migration and invasion, and proximal and direct coculture of adipocytes increased OC proliferation alone or after treatment with carboplatin. Treatment of adipocytes with hypomethylating agent guadecitabine decreased migration and invasion of OC cells toward adipocytes. Subcellular protein fractionation of adipocytes treated with guadecitabine revealed decreased DNA methyltransferase 1 (DNMT1) levels even in the presence of DNA synthesis inhibitor, aphidicolin. Methyl-Capture- and RNA-sequencing analysis of guadecitabine-treated adipocytes revealed derepression of tumor-suppressor genes and epithelial–mesenchymal transition inhibitors. SUSD2, a secreted tumor suppressor downregulated by promoter CpG island methylation in adipocytes, was upregulated after guadecitabine treatment, and recombinant SUSD2 decreased OC cell migration and invasion. Integrated analysis of the methylomic and transcriptomic data identified pathways associated with inhibition of matrix metalloproteases and fatty acid α-oxidation, suggesting a possible mechanism of how epigenetic therapy of adipocytes decreases metastasis. In conclusion, the effect of DNMT inhibitor on fully differentiated adipocytes suggests that hypomethylating agents may affect the tumor microenvironment to decrease cancer cell metastasis.Implications: Epigenetic targeting of tumor microenvironment can affect metastatic behavior of ovarian cancer cells. Mol Cancer Res; 16(8); 1226–40. ©2018 AACR.</div>

Serous ovarian cancer

10.1158/1541-7786.c.6540510

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Donor-derived cell free DNA (dd-cfDNA) in pregnant kidney transplant recipients

American Journal of Obstetrics and Gynecology (2023)

Jessica Tang Kate Woodruff Christine Jang Nicole C. Charland Lauren Bass

Cell-free fetal DNA

10.1016/j.ajog.2022.11.717

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OR1-1 | Extracting Data from Catheterization Reports Using Generative AI

Journal of the Society for Cardiovascular Angiography & Interventions (2024)

Yuval Barak–Corren Jessica Tang Christopher L. Smith Ryan Callahan Yoav Dori

In interventional cardiology, critical information often lies in catheterization reports' unstructured text. This poses a challenge in chart review, especially in multi-site studies, where reporting styles and medical terminologies can vary. Generative AI tools like ChatGPT could potentially streamline this process, enhancing uniformity and efficiency. However, the reliability and accuracy of data extraction by such tools remain uncertain. This was the focus of our study. The Children's Hospital of Philadelphia Cardiac Center Data Warehouse was queried for all cardiac catheterization text reports between 06/27/2016 and 12/31/2022 (6.5 years). Only the 'Hemodynamics' section was extracted and used for analysis. Two ChatGPT models, Plus (GPT 4.0, release 05/03/2023) and a fine-tuned ChatGPT 3.0, were used to extract pulmonary (Qp) and systemic flow (Qs) data. The Plus model received detailed instructions and 15 few-shot examples; the ChatGPT 3.0 was trained with 300 report-output pairs. Both models returned their output in a table format, which was used for further analysis. A random sample of 100 cases was used to manually evaluate models' accuracy. A total of 3,351 reports were identified, of which 2,699 (81%) mentioned either Qp or Qs in the text. Both ChatGPT models successfully processed all reports. In the 100-sampled cases, ChatGPT Plus had a 14% error rate, versus 11% for ChatGPT 3.0. Using ChatGPT 4.0 to validate and correct its own results did not lead to improved accuracy. Both models agreed on the Qp, Qs, and Qp:Qs in 84%, 92%, and 76% of the cases, respectively. In a random sample of 100 cases with equal extractions in both models, there was 97% accuracy. The 3 errors included a typo (in original report) and 2 missed values. ChatGPT offers an exciting opportunity for analyzing large amounts of clinical data and for chart review. Nevertheless, it is not free of errors, with an error rate of 11-14% in our study. The use of two different models, each utilizing a different approach, can reduce this error rate to only 2-3%. As these models improve, and as hospitals implement in-house versions that can support protected health information, this could become a powerful tool for future research studies.

10.1016/j.jscai.2024.101401

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Supplemental Figures S1-S7 from An Effective Epigenetic-PARP Inhibitor Combination Therapy for Breast and Ovarian Cancers Independent of BRCA Mutations

Nicholas Pulliam Fang Fang Ali Özeş Jessica Tang Adeoluwa Adewuyi

Supplemental Figure S1: PEO1 cells ectopically expressing vector control or BRCA2 were subjected to (A) RAD51 foci formation assay or (B) treated with increasing concentrations of Cisplatin (CDDP) and subjected to MTT assay for IC50 determination. DNMT1 expression was measured in PEO1 and PEO4 cells treated with or without 1nM Talaz by (C) qRT-PCR or (D) Western blot analysis (bottom: Images were quantified using ImageJ software and quantification is representative of three independent experiments {plus minus} SEM; two-tailed student's t-test). (E) PEO1 (Top) and PEO4 (Bottom) cells were treated with 20nM guadecitabine (Guad) and 1nM talazoparib (Talaz), alone or in combination for 72hrs. 24hrs post treatment caspase 3/7 activity assay was performed. Results are representative of at least three independent experiments. (F) Ovarian cancer cells were treated with the indicated dose of 5- azacytidine (AZA) and talazoparib (Talaz), alone or in combination for 72hrs. Supplemental Figure S2: A panel of OC cell lines (see table for description: Supplemental Table 1) was treated with (A-G) 20nM guadecitabine (Guad), (H-I) 5-azacytidine (AZA), or 1nM talazoparib (Talaz), alone and in combination. Following treatment cells were subjected to clonogenic survival assays and drug synergism analysis; x-axis is indicative of Fraction affected (FA); y-axis is indicative of combination index (CI). Combinations beneath dashed black line are synergistic. Combination treatment schemas are as followed: Priming ('Prime') daily treatment with 20nM Guad for 3 days, 24hrs recovery, followed by one treatment with 1nM Talaz or Co-administration ('Co-ad') treatment with both 20nM guadecitabine (Guad) and 1nM talazoparib (Talaz) on day 1, and 20nM Guad on days 2 and 3. Results are representative of at least three independent experiments {plus minus} SEM. * p<0.01, ** p<0.001, *** p<0.0001 compared to control, # p<0.01, ## p<0.001 relative to bracketed treatment. F. G. C. D. A. B. E. Supplemental S3 Supplemental Figure S3: (A-G) A panel of breast cancer cell lines (see table: Supplemental Table 1) was treated with either 20nM guadecitabine (Guad) or 1nM talazoparib (Talaz), alone and in combination. Following treatment cells were subjected to clonogenic survival assays and drug synergism analysis; x-axis is indicative of Fraction affected (FA); y-axis is indicative of combination index (CI). Combinations beneath dashed black line are synergistic. Combination treatment schemas are as followed: Priming ('Prime') daily treatment with 20nM Guad for 3 days, 24hrs recovery, followed by one treatment with 1nM Talaz or Co-administration ('Co-ad') treatment with both 20nM Guad and 1nM Talaz on day 1, and 20nM Guad on days 2 and 3. Results are representative of at least three independent experiments {plus minus} SEM. * p<0.01, ** p<0.001, *** p<0.0001 compared to control, # p<0.01, ## p<0.001 relative to bracketed treatment. Supplemental Figure S3: (A-G) A panel of breast cancer cell lines (see table: Supplemental Table 1) was treated with either 20nM guadecitabine (Guad) or 1nM talazoparib (Talaz), alone and in combination. Following treatment cells were subjected to clonogenic survival assays and drug synergism analysis; x-axis is indicative of Fraction affected (FA); y-axis is indicative of combination index (CI). Combinations beneath dashed black line are synergistic. Combination treatment schemas are as followed: Priming ('Prime') daily treatment with 20nM Guad for 3 days, 24hrs recovery, followed by one treatment with 1nM Talaz or Co-administration ('Co-ad') treatment with both 20nM Guad and 1nM Talaz on day 1, and 20nM Guad on days 2 and 3. Results are representative of at least three independent experiments {plus minus} SEM. * p<0.01, ** p<0.001, *** p<0.0001 compared to control, # p<0.01, ## p<0.001 relative to bracketed treatment. Supplemental Figure S4: (A) Western blot analysis of PEO4 cells following BRCA2 knock down, compared to vector control knock down. (B) PEO4 cells were treated with 20nM guadecitabine (Guad) and 1nM talazoparib (Talaz), alone and in combination, following knock down of BRCA2 or control. Treated cells were subjected to clonogenic survival assay. Results are representative of three independent experiments. (C) Western blot analysis of PEO4 cells against indicated antibodies ectopically expressing BRCA2, compared to vector control. Low exposure is 10 seconds and high exposure is 30 seconds. Western blot is representative of three individual experiments. (D) Vector control and BRCA2 overexpressing PEO4 cells were treated with 20nM guadecitabine (Guad) and increasing concentrations of talazoparib (Talaz), as indicated by the x-axis, and subjected to cell viability assays. Results are representative of three independent experiments, performed in triplicate {plus minus} SEM. * p<0.01, ** p<0.001, *** p<0.0001 compared to control, # p<0.01, ## p<0.001 relative to bracketed treatment. Supplemental Figure 5: (A) Basal PAR concentration was measured in PEO1 and PEO4 cells by PAR-capture ELISA. Results are representative of three independent experiments {plus minus} SEM (B) Luciferase assay measuring basal ATP levels between PEO1 and PEO4 cells. Results are normalized to PEO1 cell line luciferase activity. Results are representative of two individual (biological) experiments. (C) Basal expression of ROS-associated genes in PEO1 and PEO4 cells was measured by qRT-PCR. Results are normalized to PEO1 cell line expression. (D) PEO1 cells were treated with 20nM guadecitabine (Guad) and 1nM talazoparib (Talaz), alone or in combination, and expression of ROS-associated genes was measured by qRT-PCR. Results are normalized to untreated control. Results are representative of three independent experiments. (E) PEO4 cells were treated with 20nM guadecitabine (Guad) and 1nM talazoparib (Talaz), alone or in combination, and expression of ROS-associated genes was measured by qRTPCR. Results are normalized to untreated control and are representative of three independent experiments. PEO1 and PEO4 cells were treated with 5μM RG108 (non-nucleoside analog DNMTi), 24hr post treatment cells were subjected to (F) western blot analysis against the indicated antibodies and (G) ROS levels measured. Quantification is representative of three individual experiments (Mean {plus minus} SEM; two-tailed student's t-test). * p<0.01, ** p<0.001, *** p<0.0001 compared to control, # p<0.01, ## p<0.001 relative to bracketed treatment. Supplemental Figure 6: (A) PEO4 cells were treated with 1mM H2O2 in the presence and absence of 5μM PKA inhibitor H89, (left) western blot analysis against the indicated antibodies and (right) PAR capture ELISA was performed. (B) Basal cAMP concentrations were measured between PEO1 and PEO4 cells. Results are representative of three independent experiments. (C) OC and breast cancer cell lines were treated with 1nM talazoparib (Talaz) for 24hrs and cAMP levels measured. Quantification is representative of three separate experiments. (D) PEO1 and PEO4 cells were treated with 10μM FSK (adenylate cyclase activator) in the presence and absence of 5μM PKA inhibitor H89 or 1nM talazoparib (Talaz). Western blot analysis of cell lysates against indicated antibodies was performed. Western blot is representative of three individual blots. (E) PEO4 cells were treated with 20nm Guad and the indicated concentrations of Talaz, with or without 5μM PKA inhibitor H89 pre-treatment for 24hrs. Treated cells were subjected to colony formation assays (F) PEO1 cells were treated with 1nM talazoparib (Talaz) in the presence and absence of 5μM H89 (PKA inhibitor), and cell viability assay was performed. Results are representative of three individual experiments, performed in duplicate (Mean {plus minus} SEM). * p<0.01, ** p<0.001, *** p<0.0001 compared to control, # p<0.01, ## p<0.001 relative to bracketed treatment. Supplemental Figure 7: (A) A2780 cells were treated with 500nM AZA, 1nM Talaz or the combination, and subjected to (Top) western blot analysis, following chromatin isolation. (Bottom) Quantification of PARP1 chromatin localization is representative of three independent experiments, and performed using ImageJ software. (B) PEO1 and PEO4 cells were treated with 20nM guadecitabine (Guad) or 1μM veliparib (Velip), alone and in combination for 72hrs, and clonogenic survival assay performed. Quantification is representative three individual experiments (Mean {plus minus} SEM). (C) PEO1 and PEO4 cells were treated with 1μM veliparib (Velip) and cAMP levels measured. Quantification is representative of three separate experiments (Mean {plus minus} SEM; two-tailed student's t-test). (D) Proposed model: (Left; "Priming") DNMTi increases intracellular ROS accumulation. Increased ROS promotes rapid PARP activation by stimulation of the cAMP/PKA signal transduction pathway, priming the cell towards PARPi sensitivity. (Right, "Trapping") DNMTi-PARPi co-administration induces DNMT1 and PARP1 localization to DNA, increasing DNA damage. Both contribute to PARPi response, regardless of BRCA status and function. * p<0.05, ** p<0.01, *** p<0.001 compared to control, # p<0.01, ## p<0.001 relative to bracketed treatment.

PARP inhibitor

BRCA Mutation

10.1158/1078-0432.22469796.v1

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Table S1 from An Effective Epigenetic-PARP Inhibitor Combination Therapy for Breast and Ovarian Cancers Independent of BRCA Mutations

Nicholas Pulliam Fang Fang Ali Özeş Jessica Tang Adeoluwa Adewuyi

Description of cell lines used in the study

PARP inhibitor

Table (database)

BRCA Mutation

10.1158/1078-0432.22469793.v1