ABSTRACT
High-grade serous ovarian cancer (HGSOC) is responsible for the majority of gynecology cancer-related deaths. Patients in remission often relapse with more aggressive forms of disease within 2 years post-treatment. Alternative immuno-oncology (IO) strategies, such as immune checkpoint blockade (ICB) targeting the PD-(L)1 signaling axis, have proven inefficient so far. Our aim is to utilize epigenetic modulators to maximize the benefit of personalized IO combinations in ex vivo 3D patient-derived platforms and in vivo syngeneic models. Using patient-derived tumor ascites, we optimized an ex vivo 3D screening platform (PDOTS), which employs autologous immune cells and circulating ascites-derived tumor cells, to rapidly test personalized IO combinations. Most importantly, patient responses to platinum chemotherapy and poly-ADP ribose polymerase inhibitors in 3D platforms recapitulate clinical responses. Furthermore, similar to clinical trial results, responses to ICB in PDOTS tend to be low and positively correlated with the frequency of CD3+ immune cells and EPCAM+/PD-L1+ tumor cells. Thus, the greatest response observed with anti-PD-1/anti-PD-L1 immunotherapy alone is seen in patient-derived HGSOC ascites, which present with high levels of systemic CD3+ and PD-L1+ expression in immune and tumor cells, respectively. In addition, priming with epigenetic adjuvants greatly potentiates ICB in ex vivo 3D testing platforms and in vivo tumor models. We further find that epigenetic priming induces increased tumor secretion of several key cytokines known to augment T and NK cell activation and cytotoxicity, including IL-6, IP-10 (CXCL10), KC (CXCL1), and RANTES (CCL5). Moreover, epigenetic priming alone and in combination with ICB immunotherapy in patient-derived PDOTS induces rapid upregulation of CD69, a reliable early activation of immune markers in both CD4+ and CD8+ T cells. Consequently, this functional precision medicine approach could rapidly identify personalized therapeutic combinations able to potentiate ICB, which is a great advantage, especially given the current clinical difficulty of testing a high number of potential combinations in patients.
ABSTRACT
Data driven respiratory gating (DDG) in positron emission tomography (PET) imaging extracts respiratory waveforms from the acquired PET data obviating the need for dedicated external devices. DDG performance, however, degrades with decreasing detected number of coincidence counts. In this paper, we assess the clinical impact of reducing injected activity on a new DDG algorithm designed for PET data acquired with continuous bed motion (CBM_DDG) by evaluating CBM_DDG waveforms, tumor quantification, and physician's perception of motion blur in resultant images. Forty patients were imaged on a Siemens mCT scanner in CBM mode. Reduced injected activity was simulated by generating list mode datasets with 50% and 25% of the original data (100%). CBM_DDG waveforms were compared to that of the original data over the range between the aortic arch and the center of the right kidney using the Pearson correlation coefficient (PCC). Tumor quantification was assessed by comparing the maximum standardized uptake value (SUVmax) and peak SUV (SUVpeak) of reconstructed images from the various list mode datasets using elastic motion deblurring (EMDB) reconstruction. Perceived motion blur was assessed by three radiologists of one lesion per patient on a continuous scale from no motion blur (0) to significant motion blur (3). The mean PCC of the 50% and 25% dataset waveforms was 0.74 ± 0.18 and 0.59 ± 0.25, respectively. In comparison to the 100% datasets, the mean SUVmax increased by 2.25% (p = 0.11) for the 50% datasets and by 3.91% (p = 0.16) for the 25% datasets, while SUVpeak changes were within ±0.25%. Radiologist evaluations of motion blur showed negligible changes with average values of 0.21, 0.3, and 0.28 for the 100%, 50%, and 25% datasets. Decreased injected activities degrades the resultant CBM_DDG respiratory waveforms; however this decrease has minimal impact on quantification and perceived image motion blur.
