Substance use disorders, such as alcoholism and drug addiction, are a widespread and hazardous public health issue. Technology designed for the needs and values of people in recovery may be able to supplement traditional treatment options, enhance long-term abstinence maintenance, and create new opportunities for social support. We conducted a series of participatory design workshops with women in recovery from substance use disorders to identify design opportunities for supportive technologies that align with the specific values, practices and traditions of the recovery community. Through a data-driven inductive qualitative analysis, we identify five major themes that may be addressed with technology: 1) supporting twelve-step traditions and practices, 2) management of restlessness and moments of crisis, 3) agency and control over privacy and personal safety, 4) tracking progress and maintaining motivation, and 5) constructing a new normal. We connect these themes to specific implications for design.
Substance use disorders (SUDs) are characterized by an inability to decrease a substance use (e.g., alcohol or opioids) despite negative repercussions. SUDs are clinically diagnosable, hazardous, and considered a public health issue. Sponsorship, a specialized type of peer mentorship, is vital in the recovery process and originates from 12-step fellowship programs such as Alcoholics Anonymous (AA) and Narcotics Anonymous (NA). To investigate sponsorship relationship practices and to identify design opportunities for digitally-mediated peer support, we conducted 27 in-depth interviews with members of AA and NA. We identified five key sponsorship relationship practices relevant for designing social computing tools to support sponsorship and recovery: 1) assessing dyadic compatibility, 2) managing sponsorship with or without technology, 3) establishing boundaries, 4) building a peer support network, and 5) managing anonymity. We identify social computing and digitally-mediated design opportunities and implications.
578 Background: TNBC patients with RD after neoadjuvant systemic therapy (NAST) have high risk of recurrence. Biomarkers to risk-stratify patients with RD could individualize adjuvant therapy and inform adjuvant therapy trials. We aim to investigate the impact of circulating extracellular vesicle (EV)-derived non-coding RNAs (exo-ncRNAs) on outcomes in TNBC patients with RD. Methods: The study population included 79 TNBC patients with RD post-NAST and available end-of- treatment plasma samples enrolled in an IRB-approved multisite prospective registry. EVs and their associated exo-ncRNAs were isolated by membrane affinity spin columns (Qiagen exoRNeasy). Exo-ncRNA was subjected to next-generation sequencing (Qiagen QIAseq miRNA library kit). N=47 served as a discovery cohort and N=32 served as validation cohort. With inclusion of transcripts expressed in ≥ 80% of samples, there were 1,123 normalized reads/sample. Hazard ratios and C-statistics for event-free survival (EFS) were computed for each exo-ncRNA. We report exo-ncRNAs that were significantly associated with EFS in both the discovery and validation cohorts. Results: Patient and tumor characteristics were balanced in discovery and validation cohorts. Three exo-ncRNAs were associated with increased recurrence risk in both the discovery dataset ( miR-200a-3p, HR=1.39, 95%CI 1.01-1.89, P=0.04, C-stat=0.55; miR-203a-3p, HR=1.77, 95%CI 1.15-2.73, P=0.01, C-stat=0.59; and miR-7845-5p, HR=1.53, 95%CI 1.15-2.05, P=0.004, C-stat=0.62) and the validation dataset ( miR-200a-3p, HR=1.83, 95%CI 1.24-2.72, P=0.003, C-stat=0.76; miR-203a-3p, HR=1.78, 95%CI 1.10-2.87, P=0.02, C-stat=0.67; and miR-7845-5p, HR=2.06, 95%CI 1.06-4.01, P=0.03, C-stat=0.52). Using the miRNA Target Prediction Database (miRDB), we identified 1,088, 1,352, and 387 predicted targets for miR-200a-3p, miR-203a-3p, and miR-7845-5p, respectively. Amongst 2,827 prediction events there were 2,526 unique target mRNAs. 2,235 mRNAs were targets for one candidate miRNAs, 281 mRNAs were predicted targets for two candidate miRNAs, and 10 mRNAs were predicted as targets for all three candidate miRNAs. Conclusions: The expression of miR-200a-3p, miR-203a-3p, and miR-7845-5p in plasma-derived EVs in TNBC patients with RD after NAST is associated with increased risk of recurrence. We identified ten mRNAs that are predicted targets of all three of these miRNAs. If validated in additional cohorts these exo-ncRNAs could be used in a liquid-biopsy assay to identify high-risk patients with RD who could benefit from adjuvant treatment intensification. [Table: see text]
507 Background: TNBCs with enrichment of stromal tumor-infiltrating lymphocytes (sTILs) and/or immune gene expression are more sensitive to neoadjuvant systemic therapy (NAST) and exhibit higher rates of pathologic complete response (pCR). Other biomarkers, including proliferation, are also prognostic in TNBC patients treated with NAST. We aim to investigate the impact of proliferation gene expression on efficacy of NAST in sTIL-high and sTIL-low TNBC. Methods: 110 TNBC patients treated with neoadjuvant chemoimmunotherapy (Carboplatin+Docetaxel+Pembrolizumab) on the phase II NeoPACT trial (NCT03639948) with available whole exome RNA sequencing were included. sTILs were scored in 5% increments by H&E. Tumors were defined as sTIL-high (≥ 20% sTILs) or sTIL-low ( < 20% sTILs). The ImSig Proliferation Signature score (ProlifSig) was computed from RNA sequencing data and samples were classified as ProlifSig-high (≥ median) or ProlifSig-low ( < median). ProlifSig was tested for prediction of pCR in sTIL-high and sTIL-low groups. Logistic regression was used to examine the independent prognostic utility of sTILs and ProlifSig on pCR. Results: 63/110 (57%) patients achieved a pCR. 56/110 (51%) patients were classified as sTIL-high, and 54/110 (49%) classified as sTIL-low. sTILs and ProlifSig as continuous variables were each predictive of pCR (OR = 1.022, 95%CI = 1.009-1.035, P= 0.001 for sTILs; OR = 2.682, 95%CI = 1.23-5.85, P= 0.01 for ProlifSig). In the sTIL-high group, ProlifSig was not associated with pCR either as a continuous score (AUC = 0.56) or when assessed as high/low categories (pCR 78% vs. 67% in ProlifSig-high and ProlifSig-low groups, respectively; OR = 1.79, 95%CI = 0.54-5.89, P= 0.34). In contrast, in the sTIL-low group, ProlifSig was significantly associated with pCR both as continuous score (AUC = 0.74) and when assessed as high/low categories (pCR 57% vs. 29% in ProlifSig-high and ProlifSig-low groups, respectively; OR = 3.18, 95%CI = 1.03-9.86, P= 0.045). On multivariate analysis, sTILs and ProlifSig were independent predictors of pCR (OR = 1.02, 95%CI = 1.01-1.03, P= 0.004 for sTILs; OR = 3.13, 95%CI = 1.44-6.83, P= 0.004 for ProlifSig). Conclusions: In TNBC patients treated with chemoimmunotherapy sTILs and ProlifSig provide complimentary information for prediction of pCR. ProlifSig is positively associated with pCR in sTIL-low tumors but not in sTIL-high tumors. We hypothesize that the therapeutic response in sTIL-high tumors is dominated by lymphocyte-dependent cytotoxic mechanisms, while in sTIL-low tumors, the response may be dominated by proliferation-dependent responses. ProlifSig could identify a subgroup of immune low TNBCs that can achieve substantial rates of pCR with neoadjuvant chemoimmunotherapy.
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