Li, Kai shang

Abstract Chemotherapy regimens for triple-negative breast cancer (TNBC) combine agents without knowing which agents drive response. Consequently, predictors derived from multi-agent regimens cannot be assumed to generalize to individual drugs or other regimens, motivating development of treatment-matched predictors. Here, we used TNBC patient-derived xenografts (PDXs) treated with carboplatin, docetaxel, or the combination to deconvolute drug-specific responses and identify associated molecular features. Combination treatment rarely improved upon the best single agent, with enhanced responses in only 13% of PDXs and antagonism in a comparable fraction. Proteogenomic analyses identified high cytokeratin-5 (KRT5) as a general marker of chemotherapy responsiveness and KRT5 immunohistochemistry discriminated responsive PDXs (AUROC, 0.83). To train treatment-specific predictors, we integrated these data with independent PDX and clinical cohorts with responses assessed after anthracycline-free platinum, taxane, or platinum-taxane therapy, ensuring response corresponded to the modeled treatment. Four feature selection strategies yielded largely nonoverlapping biomarker panels converging on treatment-relevant pathways. On independent test data, RNA-based predictors of complete response (CR) to platinum-based (carboplatin or cisplatin) and taxane-based (docetaxel or paclitaxel) chemotherapy achieved AUROCs of 0.80 and 0.86, respectively. For platinum-taxane regimens (carboplatin plus docetaxel or paclitaxel), proteomic-guided feature selection generated a 10-biomarker, protein- informed RNA predictor of pathologic complete response (pCR) that outperformed RNA-only feature selection and achieved an AUROC of 0.85 in an independent clinical cohort, while retaining practicality as an RNA-based assay. Treatment-matched integration of multi-omic PDX and clinical datasets provides a framework for chemotherapy-specific predictors with clinically relevant performance, supporting biomarker-guided precision selection and treatment optimization for patients with TNBC. Statement of significance Integration of multi-omic data from patient-derived xenografts with treatment-matched clinical cohorts yielded three retrospectively validated predictors of platinum, taxane, and platinum+taxane response, enabling biomarker-guided chemotherapy selection for patients with triple-negative breast cancer.

2016 Background: Among the primary aims of new therapies for glioblastoma (GBM) are the reduction of morbidity and restoration or preservation of quality of life (QoL). Selinexor (SEL) is a first-in class, oral, selective inhibitor of nuclear export which blocks exportin 1 (XPO1), forcing the nuclear retention and reactivation of tumor suppressor proteins, ultimately causing cell death in cancer cells. SEL is approved for the treatment of previously treated multiple myeloma and DLBCL. XPORT-GBM-029 (NCT04421378) is a phase 1 dose finding study followed by an open-label randomized phase 2, 3-arm trial to evaluate SEL in combination with standard therapies for newly diagnosed and recurrent GBM: Arm A (ndGBM, uMGMT) – radiation +/- SEL; Arm B (ndGBM, mMGMT) – radiation and temozolomide +/- SEL; Arm C (rGBM) – lomustine +/- SEL at first relapse. We look to identify sensitive, reliable, and clinically meaningful digital assessments of the functional status of ndGBM and rGBM patients via a patient-centric approach. Methods: XPORT-GBM-029 incorporates standard clinical and imaging evaluations of GBM progression with novel digital tools that objectively measure motor and cognitive function. The study is conducted at 50 sites globally with the aim of enrolling 350 patients with newly diagnosed and recurrent GBM. Following discussions with KOLs and patient advocacy partners at EndbrainCancer, we surveyed GBM patients and their caregivers to identify disease manifestations critical to patients’ QoL. The survey revealed four key areas impacting patients’ QoL that can be affected by GBM therapies and can be objectively monitored: cognitive function, lateralization, fatigue, and sleep. In this trial we use objective measurements to evaluate SEL’s effects on GBM patients’ QoL. Patients wear inertial sensors to measure their activity and sleep and complete a cognitive battery at baseline and before each MRI. Results: Associations between objective digital measures of activity, gait, fatigue, sleep, and cognition will be examined with respect to clinical assessments including physical examinations, modified Response Assessment in Neuro-Oncology (mRANO), Neurologic Assessment in Neuro-Oncology (NANO), Karnofsky Performance Score (KPS) and Patient Reported Outcome (PRO) QoL questionnaires. Descriptive summary statistics and plots are employed in exploratory data analysis, and other advanced data mining methods may also be considered. Conclusions: XPORT-GBM-029 trial is probably the first large, prospective, longitudinal study in GBM patients employing digital markers and may provide useful information regarding the utility of wearable and mobile devices for measuring functional outcomes in clinical trials. Clinical trial information: NCT04421378.