Citations

Abstract Background: Cyclin dependent 4/6 kinase inhibitors (CDK4/6i) and endocrine therapy (ET) have improved progression-free survival (PFS) and overall survival in HR+ MBC, but progression of disease ultimately occurs. Apart from HR+ status, there are no clinically available biomarkers that enable oncologists to determine prognosis and predict response to CDK4/6i. An emerging biomarker is serum thymidine kinase 1 (TK1), a secreted marker of proliferation that is prognostic in pts with HR+ HER2- MBC. High levels of TKa are associated with inferior PFS, whereas pts with low TKa levels pretreatment, or TKa levels that decrease on ET and a CDK4/6i, have superior PFS. Notably, TKa levels rebound ≥ 5 days off Pb, with resumption of cell cycling. PROMISE (NCT0281902) is a prospective study that enrolled women with HR+ MBC starting Pb + letrozole (L) in the 1st line [FL] or Pb + fulvestrant in the 2nd line [SL] setting. The trial includes a comprehensive “omic” assessment of blood, tumor, urine and the fecal microbiome to identify novel genomic variants and pathways associated with an early decline in TKa (measured after 2 months or end of cycle [C]2) and PFS. Here, we report the association between i) pre-treatment TKa (pre-TKa) levels and PFS (i.e. from registration to the 1st disease event) and ii) TKa levels at the end of C2 (C2-TKa) and PFS-2 (i.e. from the start of C3 to the 1st disease event).Methods: TKa testing was performed using the DiviTum assay (Biovica). TKa+ disease was defined as ≥ 200 Du/L and TKa- disease as below limit of detection to 200 Du/L. Log-rank test and univariate Cox modeling were used to assess the association between pre-TKa levels and PFS and between end of C2-TKa levels and PFS-2. The database was locked on June 28, 2021. Results: Of 68 pts enrolled, 4 were ineligible and pre-TKa data was unavailable for 4. Of the remaining 60 pts (45 FL, 15 SL), the percentage of pts with pre-TKa+ disease was 33.3% in FL (15/45, 95% CI: 20.0-49.0%), and 46.7% (7/15, 95% CI: 21.4-71.9%) in the SL. The median follow-up time for pts on study was 24 months (range: 2-42 months). There were 22 disease events (13 in FL, 9 in SL). In the FL setting, PFS was significantly shorter for preTKa+ pts compared to preTKa- pts (HR: 4.15, 95% CI:1.35-12.74; p=0.007), but not for SL pts (HR: 1.11, 95% CI: 0.30-4.18, p=0.875). End of C2 TKa data was obtained for pts while on Pb (n=5), or after stopping Pb as follows: 1-4 days (n=9), 5-8 days (n=28) and 9-36 days (n=11). PFS-2 was not associated with C2-TKa in the FL (p=0.834) or SL (p=0.454) settings. An analysis of TKa levels by metastatic site will be presented at the meeting.Conclusions: A secreted biomarker of proliferation (TK1) obtained prior to initiating CDK4/6i and ET for the treatment of HR+ MBC is associated with PFS in pts receiving 1st line Pb + L, but not in those receiving 2nd line Pb + fulvestrant. While the end of C2 TKa levels were not associated with PFS, the interpretability of these data are limited, given treatment delays (0-36 days) prior to starting C3 that may result in TKa rebound. Future studies evaluating the predictive nature of TKa and Pb response should focus on earlier timepoints while on drug. Citation Format: Ciara C O'Sullivan, Jun He, Jason Sinnwell, Vera J Suman, Krishna R Kalari, Peter T Vedell, Ann M Moyer, Xiaojia Tang, Kevin J Thompson, Abe Eyman Casey, Alvaro Moreno-Aspitia, Donald W Northfelt, Minetta C Liu, Tufia C Haddad, Saranya Chumsri, Brendan McMenomy, Prema Peethambaram, Kathryn J Ruddy, Karthik V Giridhar, Roberto A Leon-Ferre, Mattias Bergqvist, Adrian Nordmark, Richard M Weinshilboum, Liewei Wang, Matthew P Goetz. Serum thymidine kinase 1 activity (TKa) levels and progression-free survival (PFS) in patients (pts) with hormone receptor positive (HR+) HER2-negative metastatic breast cancer (MBC) on palbociclib (Pb) and endocrine therapy (ET) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-13-22.

Abstract Background: Hormone receptor-positive (HR+) breast cancer (BC) accounts for ~60-70% of all BC cases. CDK4/6i combined with endocrine therapy (ET) is the standard of care for first- and second-line therapy of patients with HR+ metastatic breast cancer (MBC) based on substantial improvements in progression free survival (PFS) and overall survival compared to ET alone. Unfortunately, most patients (pts) develop resistance to CDK4/6i. The mechanisms underlying CDK4/6i resistance have not been fully elucidated. Robust in vivo CDK4/6i resistant animal models from pts with de novo and acquired CDK 4/6i resistance are lacking. Patient-derived xenografts (PDXs) are important preclinical tools in oncology to advance our understanding of cancer biology and to evaluate drug response phenotypes. Unfortunately, the establishment of sustainable PDXs from pts with HR+ BC is much more difficult than from HR-negative BC. In order to obtain clinically relevant models that can be utilized to better understand mechanisms of primary and acquired resistance to ET and CDK4/6i, we report the development of PDXs from a prospective study in which percutaneous biopsies were obtained from women receiving palbociclib for the treatment of HR+ advanced or MBC (PROMISE; NCT03281902). Methods: PROMISE (Prospective Study to Evaluate the Role of Tumor Sequencing in Women Receiving Palbociclib for Advanced Hormone Receptor (HR)-Positive Breast Cancer) is a prospective trial which enrolled pts with HR+, HER2-negative MBC who planned to start treatment with palbociclib and letrozole (1st line [FL]) or palbociclib and fulvestrant (2nd line [SL]). For pts enrolled at Mayo Clinic Rochester (MCR), serial tumor biopsies were obtained prior to the start of treatment and at disease progression to establish PDXs. Because baseline take rate was low, we amended the protocol to attempt PDX generation after the 2nd cycle (C2) of therapy. Tissues were received within an hour of excision and were orthotopically implanted in the mammary fat pad of 6~8-week-old nonobese diabetic (NOD)/SCID/IL-2g-receptor null (NSG) mice. Tumor growth was defined as tumor volume ≥ 50 mm3. Tumor take rate was defined as percent of patients with development of at least one stably transplantable (passed at least for two generations) xenograft that was pathologically confirmed as BC. Results: Of the 50 pts enrolled at MCR, 37 were FL pts (2 ineligible) and 13 were SL pts (1 ineligible). Fresh tumor samples obtained pre-treatment from 43 eligible pts (32 FL), after C2 from 17 eligible pts (13 FL), and at disease progression from 10 eligible pts (5 FL) were implanted. Tumor growth was seen in at least one mouse from a pre-treatment specimen in 1 (3.1%) FL pt (confirmed BC) and 4 (36.4%) SL pts (2 confirmed BC); from end of C2 specimens in 2 (15.4%) FL pts and 2 (50%) SL pts (1 confirmed BC); and at progression in 1 (20%) FL pt and 2 (40%) SL pts (1 confirmed BC). The take rate from pre-treatment samples among FL pts was 1/32 (3.1%; 95% CI: 0.08-16.2%). Take rates in other groups are pending histological review. Discussion: In pts receiving palbociclib for HR+ MBC, the take rate using a pre-treatment percutaneous biopsy was low (3.1%) in the FL setting. However, higher growth rates were seen in the SL setting. The observation of higher growth rates at the end of C2 and at progression may relate to the activation of G1/S that occurs with withdrawal of palbociclib, and should be further studied. PDX remains a valuable tool for the evaluation of tumor biology and the development of new therapeutics, especially for those models established from pts with palbociclib and ET resistance. Proteogenomic and sequencing studies are ongoing to fully characterize these PDXs. Citation Format: Jia Yu, Vera J. Suman, Jun He, Jason P. Sinnwell, Ann M. Moyer, Bo Qin, Yayun Gu, Huan Zhang, Jodi M. Carter, Krishna R. Kalari, Brendan P. McMenomy, Minetta C. Liu, Tufia C. Haddad, Kathryn J. Ruddy, Fergus J. Couch, Alvaro Moreno-Aspitia, Donald W. Northfelt, Richard Weinshilboum, Ciara O'Sullivan, Matthew P. Goetz, Liewei Wang. Patient-derived xenografts (PDXs) generated from hormone receptor-positive breast cancer (BC) before and after cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) treatment: Initial findings from the PROMISE study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-01-07.

Abstract Background: Cyclin-dependent 4/6 kinase inhibitors (CDK4/6i) and endocrine therapy (ET) have improved progression-free survival (PFS) and overall survival in hormone-receptor-positive (HR+) metastatic breast cancer (MBC), but endocrine resistance is a major challenge. PROMISE [NCT0281902; n=63] is a multicenter study that enrolled women with HR+ HER2- MBC commencing palbociclib (Pb) with letrozole (1st line [1L]) or fulvestrant (2nd line [2L]), and was designed to perform a comprehensive “omic” assessment of prospectively collected biospecimens (pre-treatment (M1), at 2 months (M2), and at disease progression). The goal is to identify novel genomic variants and pathways associated with resistance to CDK4/6i and ET and PFS outcomes. Here we report the association between the proteomic, metabolomics, and lipidomics data generated from pre-Pb and 2-month serum samples and PFS. Methods: Untargeted mass spectrometry data was generated from Metabolon, assaying 1308 metabolites and 831 lipids. Additionally, 1436 proteins were assayed on the Olink platform. Cox proportional hazard models were used to evaluate the univariate hazard ratio (HR) for all features with respect to PFS. The analyses were performed on samples from 45 patients (N=33 1Lwith 9 progression events and 12 2L with 8 progression events), obtained from M1 and M2 timepoints on Pb + ET. Enrichment analysis p-values are calculated using Fisher’s exact test. Results: Proteomics: In the M1 timepoint, 93 and 43 proteins were associated with PFS in the 1L and 2L settings, respectively; inflammation genes were enriched among the 1L setting (p= 0.034); 33 proteins presented HRs ranging between 0.026 and 0.56. The FABP9 protein (HR of 1.98, 95% CI 1.02-3.83) was associated with worse PFS. Conversely, inflammation genes were not observed to be enriched in 2L. In the M2 timepoint, we observed 60 and 21 proteins significantly associated with PFS, but no biological function was enriched in 1L and 2L. Metabolites: In the M1 timepoint, metabolism of the sulfur-containing amino acids (methionine, cysteine, SAM and taurine) were enriched in the 1L setting (p= 0.035, HR range 0.15-0.33); and the branched-chain amino acids (leucine, isoleucine, and valine) were significantly associated with PFS in the 2L setting (p= 0.028, HR range 0.013-0.33). At the M2 timepoint, the amino acids were no longer enriched, but fatty acid metabolism was significantly enriched for both 1L and 2L (p= 0.048 and 0.067, respectively). Pathways involving lipids, amino acids, and xenobiotics were enriched in metabolites related to PFS (p <0.05) for both treatment lines at M1 and M2. Lipidomics: In the M1 timepoint, 10 and 19 lipids were associated with PFS for 1L and 2L, respectively. The most notable lipid associated with worse PFS in the 1L was an 18 carbon phosphatidylinositol, PI(18:1/18:2), (HR 7.34 (CI 1.27-42.50); 8 triglycerides were associated with improved PFS (HR range 0.39 and 0.55). In 2L, the 19 lipids associated with PFS included 12 phosphatidylcholines (enrichment p = 5.6X10-8). In the M2 timepoint, 15 and 8 lipids were significantly associated with PFS for 1L and 2L. An enrichment of phosphatidylinositols was observed in 1L (p= 1.2X10-5); none were observed in the 2L.Future Directions: Networks are being constructed using the proximity scores of the proteins, lipids, and metabolites associated with PFS in M1 and M2 for 1L and 2L. Network similarities and analyses will be conducted.Conclusion: Distinct multi-omic changes identified in serum samples obtained from PROMISE participants M1 and M2 on Pb correlate with disease progression in both 1L and 2L settings. Additionally, validation studies will determine the significance of these findings. Citation Format: Krishna R. Kalari, Kevin J. Thompson, Jason Sinnwell, Xiaojia Tang, Vera J. Suman, Jun He, Seul Kee Byeon, Akhilesh Pandey, Abe Eyman Casey, Peter T. Vedell, Ann M. Moyer, Alvaro Moreno-Aspitia, Donald W. Northfelt, Minetta C. Liu, Tufia C. Haddad, Saranya Chumsri, Prema Peethambaram, Kathryn J. Ruddy, Karthik V. Giridhar, Roberto A. Leon-Ferre, Richard M. Weinshilboum, Liewei Wang, Ciara C. O’ Sullivan, Matthew P. Goetz. Multiomics data reveal novel biomarkers for CDK4/6 resistance [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-01-03.

Abstract Introduction. The standard treatment for non-metastatic triple-negative breast cancer (TNBC) is neoadjuvant chemotherapy (NAC) and nearly 50% exhibit pathological complete response (pCR). However, patients with residual disease after NAC are at increased risk for recurrence and death. Prior studies examining the transcriptome of TNBC pre/post-NAC have examined a limited number of genes (<500) in heterogeneous subgroups of TNBC (e.g. LAR and non-LAR). We explored the transcriptome of androgen-receptor (AR) negative (non-LAR) TNBC subtype both pre/post NAC to identify pathways associated with NAC response. Methods. Tumors obtained pre/post NAC from TNBC patients enrolled in the Breast Cancer Genome Guided therapy study (BEAUTY) underwent RNA sequencing and reverse-phase protein array (RPPA). EdgeR was applied for differentially expressed (DE) analysis and regression methods for RPPA. Digital deconvolution method (CIBERSORTx) and TNBC single-cell data were used to obtain cell types. Pathway analysis was carried out using 2972 gene sets and gene set variation analysis (GSVA). Functional enrichment analysis was conducted with significant genes. Results. Of the 44 TNBC patients, 32 patients were excluded from the analysis cohort due to: LAR tumor (6 pts.), non-LAR tumor with pCR (23 pts.), and cell type issues with RNA-seq data (3 pt.). Paired RNA-Seq data were available for 12 TNBC patients (4 with progression <2 years [EP]) and 8 who were progression-free > 4 years [NP]) and paired RPPA data were available for 9 of these 12 patients. Differentially expressed genes, proteins and cell types between EP and NP in post-NAC. We identified 489 genes differentially expressed (DE) between EP and NP (logFC=|2|, FDR < 0.05). Analysis of cytobands from these 489 genes showed an enrichment of genes on chromosome 6p22.1-2 and 17q25.3 regions (enrichment ratio >5; p-value <10E-4). Critical genes identified in the AR- network (p-value < 10E-3) were IL1RN, SLAMF9, KRT81, BHLHE22, B3GALT5, PCP4, TREM1, AQP9, NRTN, and COL2A1.In addition, preliminary results from RPPA data of post-NAC tumors showed astrocytic phosphoprotein (PEA-15), involved in apoptosis, proliferation, glucose metabolism, as well as cell proliferation and Y box binding (YB1) proteins (involved in metastases), were more DE in EP than NP (p < 0.05). CIBERSORTx was applied to estimate the proportions of different cell types in post-NAC tumors. Cancer-associated fibroblasts iCAFs were low and myCAFs are high in EP vs NP. It is known that the cross-talk between CAFs and tumor cells may induce tumor resistance to chemotherapy. Differentially expressed pathways in post and pre-NAC EP tumors. Using genome-wide expression data from the paired 12 tumors and the GSVA method, we obtained individual pathway scores for 2972 pathways. One hundred ninety pathways were downregulated and 61 pathways were upregulated (p-value <= 0.05) in the post-NAC residual disease of EP relative to NP. We further examined these 190 pathways in the paired EPs and found 71% of those pathways were upregulated in the pre-NAC. These 190 downregulated pathways were enriched with FOXO, TGF-beta, PI3k, FGFR1, insulin and others. The 61 upregulated pathways in post-NAC EP tumors were enriched with mismatch repair, purine, tubulin, telomere, polymerase and gap-junction related pathways; 77% of those 61 pathways were downregulated in pre-NAC. Conclusions. Using a comprehensive “omics” approach, we have identified novel cancer and drug response pathways associated with recurrence in AR-TNBC disease. Further work to evaluate these as markers of outcome and potential drug targets is warranted. Citation Format: Krishna R Kalari, Vera J Suman, Xiaojia Tang, Jason P Sinnwell, Kevin J Thompson, Peter T Vedell, Jodi M Carter, Sarah A McLaughlin, Alvaro Moreno Aspitia, Donald W Northfelt, Richard J Gray, Richard Weinshilboum, Liewei Wang, Judy C Boughey, Matthew Goetz. Multi-omics data shows downregulation of mismatch repair, purin and tublin pathways in AR-negative triple-negative chemotherapy-resistant tumors [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-01-05.

Abstract Background: Although major advances have been made in the treatment of HER2+ metastatic breast cancer (MBC), the goal of care remains largely palliative, therefore better treatments are needed. Given encouraging preclinical and clinical data, the combination of cyclin dependent 4/6 kinase inhibitors and HER2-directed therapy is further being evaluated in this trial. Trial Design: In this phase I/II multicenter trial, we will determine the maximum tolerated dose (MTD) of abemaciclib (Abem) combined with T-DM1. Three Abem dose levels will be examined, 50 mg, 100 mg and 150 mg. The phase 2 portion of this trial will examine whether PFS is increased with addition of Abem to T-DM1 in two pt cohorts - those with ER+ HER2+ MBC and those with ER-HER2+ MBC. For phase 2, a pre-registration biopsy is required to confirm ER and HER2-status and to determine levels of tumor infiltrating lymphocytes; vimentin (an epithelial-mesenchymal transition marker); and CD8 and FOXP3 expression. Blood samples will be collected pretreatment , at 6 weeks, and at progression for all pts. Eligibility Criteria: Phase I&II: All pts must have HER2+ MBC per ASCO-CAP guidelines and prior treatment with a taxane, trastuzumab and pertuzumab. For the phase Iportion, pts can have measurable or non-measurable disease with no restriction on the number of prior lines of therapy. In the phase II portion, pts must have measurable disease with ≤1-2 prior lines of chemotherapy alone, ≤1 HER2-directed therapy alone, and/or chemotherapy with HER2-directed therapies. There is no limit on prior endocrine therapy. Specific Aims: The primary objective of the phase II trial is to assess whether addition of Abem to T-DM1 increases PFS in one or both patient cohorts. Secondary objectives include an assessment of toxicity, objective response rates and overall survival. Correlative studies will assess the association between baseline TIL levels, vimentin expression, and CD8/FOXP3 expression with PFS. Changes in peripheral blood mononuclear cells, CTCs, ctDNA and serum thymidine kinase 1 during the course of treatment will be examined to determine if there is a link with PFS outcomes overall and separately for each cohort. Pharmacogenomic studies will determine if pts with the FCGR3A-158 polymorphism derive less benefit from T-DM1 and have inferior PFS outcomes compared with pts who do not have this polymorphism. Statistical Methods:Phase I: Standard 3+3 design, with dose limiting toxicities as per protocol. Phase II: For each pt cohort, a stratified randomization scheme will be used to assign pts to treatment with liver mets as a stratification factor. For each pt cohort, a stratified log rank test will be used to assess whether PFS is increased with the addition of Abem to T-DM1. A non-binding futility analysis will be applied in each cohort after 58 events in the ER+ HER2+ MBC study cohort and 48 events in the ER- HER2+ MBC study cohort. Present Accrual: 0; target accrual: minimal 120 pts., maximal 140 pts CohortOne-sidedalphaPowerAccrual Period (accrual rate)Follow-up after close of enrollmentPFS with T-DM1PFS with abema and T-DM1Number of eligible patientsER+/HER2+0.100.912 months (5-6 pts per month)12 months12 weeks24 weeks64 (32 per arm)ER-/HER2+0.100.8512 months (3-4 pts per month)12 months6 weeks12 weeks50 (25 pts per arm) Citation Format: Ciara C O Sullivan, Jun He, Vera J Suman, Krishna R Kalari, Roberto A Leon-Ferre, Jose C Villasboas-Bisneto, Pratima Chalasani, Demet Gokalp Yasar, Daniel M Anderson, Philip J Stella, Anthony J Jaslowski, Susan H Tannenbaum, Angela Saverimuthu, Donald Northfelt, Alvaro Moreno-Aspitia, Jodi M Carter, Minetta C Liu, Liewei Wang, Zhenkun Lou, Matthew P Goetz. A phase I/II trial of abemaciclib and T-DM1 in women and men with HER2-positive advanced or metastatic breast cancer that has progressed on treatment with a taxane, trastuzumab and pertuzumab (THP) (ACCRU-BR-1801) [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr OT2-19-05.

Abstract Background. There is controversy regarding the impact of delayed graft function (DGF) on kidney transplant outcomes. We hypothesize that the duration of DGF, rather than DGF itself, is associated with long-term kidney graft function.Methods. We analyzed all deceased donor kidney transplants (DDKT) done at our center between 2008 to 2020 with DGF to determine factors associated with DGF duration as well as the impact of DGF duration on 1) acute rejection, BKV infection, progression of fibrosis on protocol biopsy, and death censored graft survival 2) resource utilization, including hospital length of stay and readmissions. DGF duration was assessed at three 14-day intervals: <14 DGF days, 14-27 DGF days, >28 DGF days.Results. There were 1714 DDKT were included, 59.4% (n=1018) had DGF. The median DGF duration was 10 days IQR (6,15). The majority of recipients (95%) had resolution of DGF within 28 days. Donor factors associated with DGF days were longer cold ischemia time, donor on inotropes, older age, donation after circulatory death, higher terminal creatinine, and hypertension. Recipient factors associated with increased DGF duration included male sex, length on dialysis before transplant, and higher body mass index. There were no differences in acute rejection events or interstitial fibrosis progression by 4 months when comparing DGF days. The median length of stay was 3 days. However, readmissions increased with increasing DGF duration. Death-censored graft survival was not associated with the length of DGF except when DGF lasted >28 days. Conclusions. Inferior graft survival was observed only in recipients of DDKT with DGF lasting beyond 28 days. DGF lasting <28 days had no impact on graft survival. Duration of DGF, rather than DGF itself, is associated with graft survival. Trial Registration. Retrospective study approved by Mayo Clinic IRB.

BackgroundThe objective of this randomized trial was to evaluate the short‐term effect of bilingual written and interpersonal education regarding mammographic breast density (MBD).MethodsLatinas aged 40 to 74 years who were presenting for screening mammography were recruited and randomized 1:1:1 to receive a letter with their mammogram and MBD results (usual care [UC]), a letter plus a brochure (enhanced care [ENH]), or a letter plus a brochure and telephonic promotora education (interpersonal care [INT]). Surveys were administered at enrollment (T0) and 2 weeks to 6 months after intervention delivery (T1). Differences were assessed with χ2, Kruskal‐Wallis, and McNemar tests and pairwise comparisons as appropriate. INT metrics and audio recordings were analyzed with descriptive statistics and qualitative content analysis.ResultsBetween October 2016 and October 2019, 943 of 1108 Latina participants (85%) completed both surveys. At T1, INT participants were more likely (P < .001) to report seeing their MBD results in the letter (70.2%) than UC (53.1%) or ENH participants (55.1%). The percentage of INT women who reported speaking with a provider about MBD (29.0%) was significantly greater (P < .001) than the percentage of UC (14.7%) or ENH participants (15.6%). All groups saw significant (P < .001) but nondifferential improvements in their knowledge of MBD as a masking and risk factor. In the INT group, the promotora delivered education to 77.1% of the 446 participants randomized to INT and answered questions at 28.3% of the encounters for an average of $4.70 per participant.ConclusionsAmong Latinas in a low‐resource setting, MBD knowledge may increase with written or interpersonal education, but with modest investment, interpersonal education may better improve MBD awareness and prompt patient‐provider discussions.

Abstract Introduction: The gut microbiome is a potentially modifiable factor in treatment related outcomes in allogeneic hematopoietic cell transplant (HCT). Prior studies have linked pre- or mid-treatment gut microbiome diversity with risk for treatment related morbidity and mortality. However, these studies have been limited by the inclusion of one or only a few institutions and the lack of longitudinal sampling with high quality metadata. These limitations complicate the interpretation of microbiome alterations over the course of HCT. Methods: To overcome these, we devised and implemented a large-scale biospecimen collection protocol in conjunction with BMT CTN 1703, a randomized, multicenter, Phase III trial of tacrolimus/methotrexate vs. post-transplant cyclophosphamide/tacrolimus/mycophenolate mofetil in reduced intensity conditioning (RIC) allogeneic HCT (NCT03959241). Patients enrolled on 1703 were optionally co-enrolled in the companion immune and microbiome profiling study, 1801 (MI-IMMUNE). This involved blood, urine and stool sampling before conditioning (PCON), then weekly starting on day 0 through day 77 (through day 84 for blood), and on days 98, 180, 270, 365 and 730. For all enrolled participants where the donor consented, residual donor cells were saved from the empty hematopoietic stem cell product bag for later analysis. Additionally, the protocol included one-time blood, urine and stool sample collection from consented matched related donors (MRDs) prior to stem cell collection. Starting with protocol version 4.0 on February 1, 2021, participation in 1801 stool collection was required for the first six out of eighteen sample collection timepoints. Participation in later stool and urine timepoint collections remained optional. Here we review the feasibility of creating a multi-institutional biobank. Additionally, we assess the success of our strategies by calculating sample collection compliance and standard deviation in compliance across centers for each timepoint. Results: On June 18, 2021, BMT CTN 1703/1801 closed to accrual with 431 patients enrolled on 1703; 323 patients from 36 centers were co-enrolled on 1801. 304 (94%) provided study samples, making this the largest prospective microbiome and immune profiling study in HCT patients to date. As of July 6, 2021, 3,683 blood, 2,668 urine, and 2,098 stool samples had been collected. Across the first 6 timepoints for all participating centers, blood, urine and stool sample collection averaged 93%, 82%, and 74% compliance, respectively. Of the 99 (30%) patients enrolled on 1801 with a MRD, 34 (34%) donors consented to sample collection. Sample collection compliance was lower for MRDs than for patients on the study with 76%, 74%, and 62% of expected blood, urine and stool samples collected, respectively, from this group. For stool collection exclusively, a median of 5 samples were collected per patient across the first 6 timepoints (median of 6 across all timepoints) with 93 (31%) of patients completing a full sample set through Day 28. 139 (46%) patients provided at least one sample after day 28; these represented 37% of the total samples collected to date. The PCON sample, which provides an important measure of pre-treatment gut microbiome diversity, had the third highest compliance with 74% of patients providing a sample. Surprisingly, Day 28 had the lowest compliance (66%) and highest standard deviation (37%) possibly because this timepoint often falls around the time of hospital discharge. Between PCON and day 28, the standard deviation between sites in the average collection compliance (24%) and number of samples collected per patient (1.1) was small indicating the successful adoption of stool collection across institutions. Table 1 summarizes sample collection statistics. Conclusion: Overall this study has resulted in a large, novel biobank of blood, urine and stool samples from patients undergoing RIC allogeneic HCT at 36 centers across the US. This will serve as a valuable resource for investigating the role of the gut microbiome in long term health outcomes following HCT. Although the results of 1801 are forthcoming given ongoing sample collection, the size and composition of the biobank to date clearly demonstrate the feasibility of implementing multi-institutional stool collection. This study represents a critical step towards the large-scale adoption of microbiome sampling as a diagnostic tool. Figure 1 Figure 1. Disclosures Chhabra: GSK: Honoraria. Clark: Kadmon: Consultancy. Horowitz: Mesoblast: Research Funding; Shire: Research Funding; Vertex: Research Funding; Stemcyte: Research Funding; Vor Biopharma: Research Funding; Janssen: Research Funding; Miltenyi Biotech: Research Funding; Kiadis: Research Funding; Sobi: Research Funding; Kite/Gilead: Research Funding; Pfizer, Inc: Research Funding; Jazz Pharmaceuticals: Research Funding; Magenta: Consultancy, Research Funding; Medac: Research Funding; Novartis: Research Funding; GlaxoSmithKline: Research Funding; Daiicho Sankyo: Research Funding; Xenikos: Research Funding; Omeros: Research Funding; Orca Biosystems: Research Funding; Pharmacyclics: Research Funding; Regeneron: Research Funding; Tscan: Research Funding; Takeda: Research Funding; CSL Behring: Research Funding; Genentech: Research Funding; Gamida Cell: Research Funding; Chimerix: Research Funding; Bristol-Myers Squibb: Research Funding; bluebird bio: Research Funding; Astellas: Research Funding; Amgen: Research Funding; Allovir: Consultancy; Actinium: Research Funding; Sanofi: Research Funding; Seattle Genetics: Research Funding. Jenq: Microbiome DX: Consultancy; Merck: Consultancy; Prolacta: Consultancy, Membership on an entity's Board of Directors or advisory committees; Kaleido: Consultancy, Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Research Funding; Seres: Consultancy, Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; LisCure: Consultancy, Membership on an entity's Board of Directors or advisory committees; MaaT Pharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Karius: Consultancy. Levine: Equillium Bio: Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Research Funding; Kamada: Research Funding; Biogen: Research Funding; Omeros: Membership on an entity's Board of Directors or advisory committees; Symbio: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Talaris Therapeutics: Membership on an entity's Board of Directors or advisory committees; Viracor: Patents & Royalties: GVHD biomarker patent with royalties from Viracor; Mesoblast: Consultancy, Research Funding; X4 Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Murthy: CRISPR Therapeutics: Research Funding. Riches: ATARA Biotherapeutics: Other: Payment; BioIntelect: Membership on an entity's Board of Directors or advisory committees; Jazz Pharmaceuticals: Other: Payment. Sung: Merck: Research Funding; Novartis: Research Funding; Enterome: Research Funding; Seres: Research Funding; AVROBIO: Consultancy; Abbott Nutrition: Honoraria; Clasado: Other: Research Product; DSM: Other: Research Product. Al Malki: Neximmune: Consultancy; Jazz Pharmaceuticals, Inc.: Consultancy; Rigel Pharma: Consultancy; Hansa Biopharma: Consultancy; CareDx: Consultancy. Rezvani: Kaleido: Other: One-time scientific advisory board; Nohla Therapeutics: Other: One-time scientific advisory board; Pharmacyclics-Abbvie: Research Funding; US Department of Justice: Consultancy. Bolaños-Meade: Incyte Corp: Consultancy. Holtan: Incyte: Consultancy, Research Funding; Generon: Consultancy. Saber: Govt. COI: Other. Hamadani: Sanofi, Genzyme, AstraZeneca, BeiGene: Speakers Bureau; Janssen, Incyte, ADC Therapeutics, Omeros, Morphosys, Kite: Consultancy; Takeda, Spectrum Pharmaceuticals and Astellas Pharma: Research Funding. Kean: Bluebird Bio: Research Funding; Bristol Myers Squibb: Patents & Royalties: From clinical trial data, Research Funding; Vertex: Consultancy; Novartis: Consultancy; Gilead: Research Funding; Regeneron: Research Funding; EMD Serono: Consultancy. Perales: Cidara: Honoraria; Servier: Honoraria; Incyte: Honoraria, Other; Equilium: Honoraria; Takeda: Honoraria; Novartis: Honoraria, Other; Nektar Therapeutics: Honoraria, Other; NexImmune: Honoraria; MorphoSys: Honoraria; Omeros: Honoraria; Karyopharm: Honoraria; Sellas Life Sciences: Honoraria; Merck: Honoraria; Miltenyi Biotec: Honoraria, Other; Medigene: Honoraria; Bristol-Myers Squibb: Honoraria; Kite/Gilead: Honoraria, Other; Celgene: Honoraria.

Abstract Multiple myeloma (MM) is the second-most common hematological malignancy in the US. MM is an incurable, age-dependent plasma cell neoplasm with a 5-year survival rate of less than 50%. Extensive inter-individual variation in response to standard-of-care drugs like proteasome inhibitors (PIs) and immunomodulatory drugs (IMiDs), drug resistance, and dose-limiting toxicities are critical problems for the treatment of MM. Clinical success in anti-myeloma treatment, therefore, warrants continuous development of novel combination therapy strategies with the explicit goal to improve the therapeutic efficacy by concomitantly targeting multiple signaling pathways. Previously, we have reported the development of an in-house computational pipeline called secDrug that applies greedy algorithm-based set-covering computational optimization method followed by a regularization technique to predict secondary drugs that can be repurposed as novel synergistic partners of standard-of-care drugs for the management of refractory/ resistant MM. Top among these secondary drugs (secDrugs) were the HSP90 inhibitor 17-AAG. In this study, we used 17-AAG as a proof of principle to establish a pipeline that integrates our in silico predictions with in vitro and ex vivo validation as well as multi-omics technologies to identify, validate, and characterize therapeutic agents that could be used either alone or in combination with standard-of-care drugs for the treatment of R/R MM patients (Figure 1). To screen and validate our in silico prediction results, we performed in vitro cytotoxicity assays using 17-AAG on a panel of human myeloma cell lines (HMCLs; in vitro model systems) that captures a wide range of biological and genetic heterogeneity representing the complexities encountered in clinical settings. These cell lines include HMCLs representing innate sensitive/resistance, &gt;10 pairs of parental and clonally-derived PI- and IMiD-resistant pairs (P vs VR or LenR; representing acquired/emerging resistance/relapse), NRAS mutants which leads to the constitutive activation of oncogenic Ras signaling, and CRISPR-edited HSP90 knockdown cell line. Our results showed that 17-AAG has high synergistic activity in combination with PI in inducing apoptosis even in innate and acquired PI-resistant HMCLs and significantly reduces the effective dose of PI required to achieve IC 50 (Chou-Talalay's Dose Reduction Index or DRI 7±1.4). Moreover, 17-AAG+IMiD showed synergistic cell killing activity in clonally-derived IMiD resistant HMCL. Further, 17-AAG induced cell death was comparable with Hsp90 knockdown as evident from the cytotoxicity assay using PI and 17-AAG in combination in RPMI8226-wild type and RPMI-HSP90AA1 knocked down cell line. Notably, 17-AAG was strikingly effective against the NRAS-mutant cell line indicating an additional niche (NRas mutant myeloma) where 17-AAG could be most effective. Next, we performed RNA sequencing to elucidate the molecular mechanisms behind 17-AAG drug action, drug synergy, 17-AAG-induced cell death. Our gene expression profiling (GEP) followed by Ingenuity Pathway Analysis (IPA) analysis revealed protein ubiquitination, aryl hydrocarbon receptor signalling pathway as the top canonical pathways. 17-AAG induced apoptosis via mitochondrial mediated pathway in myeloma. 17-AAG exerts its cytotoxic effect by activating intrinsic pathway of apoptosis which we further confirmed through the increase in reactive oxygen species generation and decrease in mitochondrial membrane potential. 17-AAG was also effective in reducing the expression of hallmarks of MM such as p65/NF-kB, IRF4, c-Myc. Finally, we performed mass cytometry (CyTOF; Cytometry by time of flight) on primary bone-marrow cells (PMCs) from myeloma patients for further validation of proteomic signatures at the single-cell level. CyTOF analysis confirmed 17-AAG-induced cell death and key changes in MM-specific proteomic markers. 17-AAG treated PMCs showed elevated cleaved caspase levels and down-regulation of IRF4 and phospho-STAT3. GEP and CyTOF results were confirmed using immunoblotting assays. Together, our study demonstrates a unique pipeline for drug repositioning that has the potential to revolutionize clinical decision-making by minimizing the number of drugs required for discovering successful combination chemotherapy regimens against drug-resistant myeloma. Figure 1 Figure 1. Disclosures Kumar: BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Beigene: Consultancy; Oncopeptides: Consultancy; Antengene: Consultancy, Honoraria; Carsgen: Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding.