Gastric cancer (GC) is the fifth cancer type by associated mortality. Proportion of early diagnosis is low, and most patients are diagnosed at the advanced stages. First line therapy standardly includes fluoropyrimidines and platinum compounds with trastuzumab for HER2positive cases. For the recurrent disease there are several alternative options including ramucirumab, a monoclonal therapeutic antibody that inhibits VEGF-mediated tumor angiogenesis by binding with VEGFR2, alone or in combination with other cancer drugs. However, overall response rate rate following ramucirumab or its combinations is 30-80% of the patients, suggesting that personalization of drug prescription is needed to increase efficacy of treatment. We report here original tumor RNA sequencing profiles for 15 advanced GC patients linked with data on clinical response to ramucirumab or its combinations. Three genes showed differential expression in the tumors-responders vs non-responders: CHRM3, LRFN1 and TEX15. Of them, CHRM3 was upregulated in the responders. Using bioinformatic platform Oncobox we simulated ramucirumab efficiency and compared output model results with actual tumor response data. An agreement was observed between predicted and real clinical outcomes (AUC ≥ 0.7). These results suggest that RNA sequencing may be used to personalize prescription of ramucirumab for GC and indicate on potential molecular mechanisms underlying ramucirumab resistance. The RNA sequencing profiles obtained here are fully compatible with the previously published Oncobox Atlas of Normal Tissue Expression (ANTE) data.
BackgroundCholangiocarcinoma is an aggressive tumor with poor prognosis. Most of the cases are not available for surgery at the stage of the diagnosis and the best clinical practice chemotherapy results in about 12-month median survival. Several tyrosine kinase inhibitors (TKIs) are currently under investigation as an alternative treatment option for cholangiocarcinoma. Thus, the report of personalized selection of effective inhibitor and case outcome are of clinical interest.Case presentationHere we report a case of aggressive metastatic cholangiocarcinoma (MCC) in 72-year-old man, sequentially treated with two targeted chemotherapies. Initially disease quickly progressed during best clinical practice care (gemcitabine in combination with cisplatin or capecitabine), which was accompanied by significant decrease of life quality. Monotherapy with TKI sorafenib was prescribed to the patient, which resulted in stabilization of tumor growth and elimination of pain. The choice of the inhibitor was made based on high-throughput screening of gene expression in the patient’s tumor biopsy, utilized by Oncobox platform to build a personalized rating of potentially effective target therapies. However, time to progression after start of sorafenib administration did not exceed 6 months and the regimen was changed to monotherapy with Pazopanib, another TKI predicted to be effective for this patient according to the same molecular test. It resulted in disease progression according to RECIST with simultaneous elimination of sorafenib side effects such as rash and hand-foot syndrome. After 2 years from the diagnosis of MCC the patient was alive and physically active, which is substantially longer than median survival for standard therapy.ConclusionThis case evidences that sequential personalized prescription of different TKIs may show promising efficacy in terms of survival and quality of life in MCC.Electronic supplementary materialThe online version of this article (10.1186/s40164-018-0113-x) contains supplementary material, which is available to authorized users.
Ovarian cancer is the fifth leading cause of cancer-related female mortality and the most lethal gynecological cancer. In this report, we present a rare case of recurrent granulosa cell tumor (GCT) of the ovary. We describe the case of a 26-yr-old woman with progressive GCT of the right ovary despite multiple lines of therapy who underwent salvage therapy selection based on a novel bioinformatical decision support tool (Oncobox). This analysis generated a list of potentially actionable compounds, which when used clinically lead to partial response and later long-term stabilization of the patient's disease.
Non-small cell lung carcinoma (NSCLC) is the major cause of cancer-associated mortality. Identification of rearrangements in anaplastic lymphoma kinase (ALK) gene is an effective instrument for more effective targeted therapy of NSCLC using ALK inhibitors dramatically raising progression-free survival in the ALK-mutated group of patients. However, the tumors frequently develop resistance to ALK inhibitors. We describe here a case of 48 y.o. male patient with ALK-positive NSCLC who was clinically managed for 6.5 years from the diagnosis. The tumor was surgically resected, but 8 months later multiple brain metastases were discovered. The patient started receiving platinum-based chemotherapy and then was enrolled in a clinical trial of second-generation ALK inhibitor ceritinib, which resulted in a 21 months stabilization. Following disease relapse, the patient was successfully managed for 33 months with different lines of chemo- and local ablative therapies. Chemotherapy regimens, including off-label combination of crizotinib + bevacizumab + docetaxel, were selected using the cancer transcriptome data-guided bioinformatical decision support system Oncobox. These therapies led to additional stabilization for 22 months. Survival of our patient after developing resistance to ALK inhibitor was longer for 16 months than previously reported average survival for such cases. This case shows that transcriptomic-guided sequential personalized prescription of targeted therapies can be effective in terms of survival and quality of life in ALK-mutated NSCLC.
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