Precision oncology is currently based on pairing molecularly targeted agents (MTA) to predefined single driver genes or biomarkers. Each tumor harbors a combination of a large number of potential genetic alterations of multiple driver genes in a complex system that limits the potential of this approach. We have developed an artificial intelligence (AI)-assisted computational method, the digital drug-assignment (DDA) system, to prioritize potential MTAs for each cancer patient based on the complex individual molecular profile of their tumor. We analyzed the clinical benefit of the DDA system on the molecular and clinical outcome data of patients treated in the SHIVA01 precision oncology clinical trial with MTAs matched to individual genetic alterations or biomarkers of their tumor. We found that the DDA score assigned to MTAs was significantly higher in patients experiencing disease control than in patients with progressive disease (1523 versus 580, P = 0.037). The median PFS was also significantly longer in patients receiving MTAs with high (1000+ <) than with low (<0) DDA scores (3.95 versus 1.95 months, P = 0.044). Our results indicate that AI-based systems, like DDA, are promising new tools for oncologists to improve the clinical benefit of precision oncology.

Since the prognosis of advanced cholangiocarcinoma (CCA) remains poor with traditional chemotherapy, attention has shifted to molecularly targeted agents. Results of available clinical studies reveal little or no benefit of using targeted agents in advanced CCA. Limitations of these trials could be the lack of comprehensive molecular and genetic characterization of CCA samples in order to identify potential drug targets. Here we report a case of a 59-year-old female with chemotherapy-refractor, metastatic extrahepatic cholangiocarcinoma (EHCCA). After failure of first-line chemotherapy with cisplatin plus gemcitabine, next generation sequencing (NGS) based tumor molecular profiling was performed on aspiration cytological sample, that revealed BRAF V600E mutation. Multidisciplinary team decided on the initiation of combined treatment with BRAF and MEK inhibitors. Dabrafenib was started orally 150 mg twice a day, adding trametinib 2 mg once a day. Right from the initiation of targeted therapy, significant clinical improvement had been observed. Even though the first restaging computed tomography (CT) scan at 8 weeks revealed spectacular decrease in all metastatic sites, a new hepatic mass of 67 mm × 40 mm was identified and interpreted as new metastatic lesion. As the clinical and radiological response was contradictory, CT-guided biopsy was taken from the hepatic lesion while the therapy was continued on. Histopathologic evaluation excluded the hepatic lesion from being a metastasis, instead described it as a fibrotic, inflammatory lesion.At 12 week, PET CT confirmed further tumor regression with complete regression of the multiple cerebral metastases. The therapy has been extremely well tolerated by the patient. According to our knowledge, this is the first reported case on a successful treatment of EHCCA with the combination of dabrafenib and trametinib. Our case highlights the importance of molecular profiling in CCA, in order to find potential actionable driver mutations for personalised treatment.

Objective A patient/family-centered conference was conducted at an underserved community hospital to address Latinas’ post-genetic cancer risk assessment (GCRA) medical information and psychosocial support needs, and determine the utility of the action research format. Methods Latinas seen for GCRA were recruited to a half-day conference conducted in Spanish. Content was partly determined from follow-up survey feedback. Written surveys, interactive discussions, and Audience Response System (ARS) queries facilitated the participant-healthcare professional action research process. Analyses included descriptive statistics and thematic analysis. Results The 71 attendees (41 patients and 27 relatives/friends) were primarily non-U.S. born Spanish-speaking females, mean age 43 years. Among patients, 73% had a breast cancer history; 85% had BRCA testing (49% BRCA+). Nearly all (96%) attendees completed the conference surveys and ARS queries; ≥48% participated in interactive discussions. Most (95%) agreed that the format met their personal interests and expectations and provided useful information and resources. Gaps/challenges identified in the GCRA process included pre-consult anxiety, uncertainty about reason for referral and expected outcomes, and psychosocial needs post-GCRA, such as absorbing and disseminating risk information to relatives and concurrently coping with a recent cancer diagnosis. Conclusions The combined action research and educational conference format was innovative and effective for responding to continued patient information needs and addressing an important data gap about support needs of Latina patients and family members following genetic cancer risk assessment. Findings informed GCRA process improvements and provide a basis for theory-driven cancer control research.

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