A spatial proteomic study of platinum refractory HGSOC implicates dual AKT and WNT activity linked to an immunosuppressive tumor microenvironment.

OBJECTIVE: Advanced-stage high-grade serous ovarian cancer (HGSOC) remains a deadly gynecologic malignancy with high rates of disease recurrence and limited, effective therapeutic options for patients. There is a significant need to better stratify HGSOC patients into platinum refractory (PRF) vs. sensitive (PS) cohorts at baseline to improve therapeutic responses and survival outcomes for PRF HGSOC. METHODS: We performed NanoString for GeoMx Digital Spatial Profile (G-DSP) multiplex protein analysis on PRF and PS tissue microarrays (TMAs) to study the bidirectional communication of cancer cells with immune cells in the tumor microenvironment (TME) of HGSOC. We demonstrate robust stratification of PRF and PS tumors at baseline using multiplex spatial proteomic biomarkers with implications for tailoring subsequent therapy. RESULTS: PS patients had elevated apoptotic and anti-tumor immune profiles, while PRF patients had dual AKT1 and WNT signaling with immunosuppressive profiles. We found that dual activity of AKT1 and WNT signaling supported the exclusion of immune cells, specifically tumor infiltrating lymphocytes (TILs), from the TME in PRF tumors, and this was not observed in PS tumors. The exclusion of immune cells from the TME of PRF tumors corresponded to abnormal endothelial cell structure in tumors with dual AKT1 and WNT signaling activity. CONCLUSIONS: We believe our findings provide improved understanding of tumor-immune crosstalk in HGSOC TME highlighting the importance of the relationship between AKT and WNT pathways, immune cell function, and platinum response in HGSOC.

Evaluating Nurses' Time to Response by Severity and Cancer Stage in a Remote Symptom Monitoring Program for Patients With Breast Cancer.

PURPOSE: Remote symptom monitoring (RSM) using electronic patient-reported outcomes enables patients with cancer to communicate symptoms between in-person visits. A better understanding of key RSM implementation outcomes is crucial to optimize efficiency and guide implementation efforts. This analysis evaluated the association between the severity of patient-reported symptom alerts and time to response by the health care team. METHODS: This secondary analysis included women with stage I-IV breast cancer who received care at a large academic medical center in the Southeastern United States (October 2020-September 2022). Symptom surveys with at least one severe symptom alert were categorized as severe. Response time was categorized as optimal if the alert was closed by a health care team member within 48 hours. Odds ratios (ORs), predicted probabilities, and 95% CIs were estimated using a patient-nested logistic regression model. RESULTS: Of 178 patients with breast cancer included in this analysis, 63% of patients identified as White and 85% of patients had a stage I-III or early-stage cancer. The median age at diagnosis was 55 years (IQR, 42-65). Of 1,087 surveys included, 36% reported at least one severe symptom alert and 77% had an optimal response time by the health care team. When compared with surveys that had no severe symptom alerts, surveys with at least one severe symptom alert had similar odds of having an optimal response time (OR, 0.97; 95% CI, 0.68 to 1.38). The results were similar when stratified by cancer stage. CONCLUSION: Response times to symptom alerts were similar for alerts with at least one severe symptom compared with alerts with no severe symptoms. This suggests that alert management is being incorporated into routine workflows and not prioritized based on disease or symptom alert severity.

Adaptation of Remote Symptom Monitoring Using Electronic Patient-Reported Outcomes for Implementation in Real-World Settings.

PURPOSE: Despite evidence of clinical benefits, widespread implementation of remote symptom monitoring has been limited. We describe a process of adapting a remote symptom monitoring intervention developed in a research setting to a real-world clinical setting at two cancer centers. METHODS: This formative evaluation assessed core components and adaptations to improve acceptability and fit of remote symptom monitoring using Stirman's Framework for Modifications and Adaptations. Implementation outcomes were evaluated in pilot studies at the two cancer centers testing technology (phase I) and workflow (phase II and III) using electronic health data; qualitative evaluation with semistructured interviews of clinical team members; and capture of field notes from clinical teams and administrators regarding barriers and recommended adaptations for future implementation. RESULTS: Core components of remote symptom monitoring included electronic delivery of surveys with actionable symptoms, patient education on the intervention, a system to monitor survey compliance in real time, the capacity to generate alerts, training nurses to manage alerts, and identification of personnel responsible for managing symptoms. In the pilot studies, while most patients completed > 50% of expected surveys, adaptations were identified to address barriers related to workflow challenges, patient and clinician access to technology, digital health literacy, survey fatigue, alert fatigue, and data visibility. CONCLUSION: Using an implementation science approach, we facilitated adaptation of remote symptom monitoring interventions from the research setting to clinical practice and identified key areas to promote effective uptake and sustainability.

Identifying a molecular profile to predict the risk of recurrence in high-intermediate risk endometrial cancer.

BACKGROUND: Patients with high-intermediate risk endometrial cancer (H-IR EMCA) have an elevated risk of recurrence compared to low-risk counterparts. Many H-IR EMCA patients are treated with radiation or chemotherapy, but their overall survival is not significantly impacted by treatment. The objective of this study was to compare molecular profiles of H-IR EMCA patients with disease recurrence to those without to identify characteristics that could better predict patient outcomes. METHODS: Tissue was acquired from H-IR EMCA patients with disease recurrence (n=15) and without disease recurrence (n=15) who had not received adjuvant therapy and performed DNA and RNA analyses. RESULTS: In recurrent population, 5 patients had matchingrecurrent and initial tumor tissues. Of note, 5/7 (71%) African Americanpatients had disease recurrence compared to 10/23 (43%) White patients. Inaddition, several new mutations were found in individual patient's recurrentcompared to initial tumors. CONCLUSIONS: Currently the treatment ofendometrial cancer is rapidly changing with molecular profiling becoming partof the standard of care. Additionally, it and is being incorporated intoclinical trials in this group of patients. The specific gene mutations and RNAexpression signatures that were observed in our small cohort need to bevalidated in larger cohorts to determine their impact.

Profiling of m6A RNA modifications identified an age-associated regulation of AGO2 mRNA stability.

Gene expression is dynamically regulated in a variety of mammalian physiologies. During mammalian aging, there are changes that occur in protein expression that are highly controlled by the regulatory steps in transcription, post-transcription, and post-translation. Although there are global profiles of human transcripts during the aging processes available, the mechanism(s) by which transcripts are differentially expressed between young and old cohorts remains unclear. Here, we report on N6-methyladenosine (m6A) RNA modification profiles of human peripheral blood mononuclear cells (PBMCs) from young and old cohorts. An m6A RNA profile identified a decrease in overall RNA methylation during the aging process as well as the predominant modification on proteincoding mRNAs. The m6A-modified transcripts tend to be more highly expressed than nonmodified ones. Among the many methylated mRNAs, those of DROSHA and AGO2 were heavily methylated in young PBMCs which coincided with a decreased steady-state level of AGO2 mRNA in the old PBMC cohort. Similarly, downregulation of AGO2 in proliferating human diploid fibroblasts (HDFs) also correlated with a decrease in AGO2 mRNA modifications and steady-state levels. In addition, the overexpression of RNA methyltransferases stabilized AGO2 mRNA but not DROSHA and DICER1 mRNA in HDFs. Moreover, the abundance of miRNAs also changed in the young and old PBMCs which are possibly due to a correlation with AGO2 expression as observed in AGO2-depleted HDFs. Taken together, we uncovered the role of mRNA methylation on the abundance of AGO2 mRNA resulting in the repression of miRNA expression during the process of human aging.

Long noncoding RNA complementarity and target transcripts abundance.

Eukaryotic mRNA metabolism regulates its stability, localization, and translation using complementarity with counter-part RNAs. To modulate their stability, small and long noncoding RNAs can establish complementarity with their target mRNAs. Although complementarity of small interfering RNAs and microRNAs with target mRNAs has been studied thoroughly, partial complementarity of long noncoding RNAs (lncRNAs) with their target mRNAs has not been investigated clearly. To address that research gap, our lab investigated whether the sequence complementarity of two lncRNAs, lincRNA-p21 and OIP5-AS1, influenced the quantity of target RNA expression. We predicted a positive correlation between lncRNA complementarity and target mRNA quantity. We confirmed this prediction using RNA affinity pull down, microarray, and RNA-sequencing analysis. In addition, we utilized the information from this analysis to compare the quantity of target mRNAs when two lncRNAs, lincRNA-p21 and OIP5-AS1, are depleted by siRNAs. We observed that human and mouse lincRNA-p21 regulated target mRNA abundance in complementarity-dependent and independent manners. In contrast, affinity pull down of OIP5-AS1 revealed that changes in OIP5-AS1 expression influenced the amount of some OIP5-AS1 target mRNAs and miRNAs, as we predicted from our sequence complementarity assay. Altogether, the current study demonstrates that partial complementarity of lncRNAs and mRNAs (even miRNAs) assist in determining target RNA expression and quantity.