Personalized prescription of imatinib in recurrent granulosa cell tumor of the ovary: case report

Poddubskaya, Elena; Baranova, Madina; Allina, Daria; Sekacheva, Marina; Makovskaia, Lyudmila; Камашев, Д.; Suntsova, Maria; Barbara, Viktoria; Kochergina-Nikitskaya, Irina N.; Aleshin, Alexey

doi:10.1101/mcs.a003434

Cited by 31 publications

(26 citation statements)

References 22 publications

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“…Based on pathway activation analysis and expressions of drug target genes, an approach was proposed that makes it possible to personalize the ranking of anticancer target drugs (ATDs) for an individual tumor [27,32,33]. This approach was recently successfully applied for several cases of off-label prescriptions of ATDs to patients with advanced or metastatic solid tumors [27,[34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Intratumoral Heterogeneity and Longitudinal Changes in Gene Expression Predict Differential Drug Sensitivity in Newly Diagnosed and Recurrent Glioblastoma

Kim

Sorokin

Kantelhardt

et al. 2020

Cancers

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Background: Inevitable recurrence after radiochemotherapy is the major problem in the treatment of glioblastoma, the most prevalent type of adult brain malignancy. Glioblastomas are notorious for a high degree of intratumor heterogeneity manifest through a diversity of cell types and molecular patterns. The current paradigm of understanding glioblastoma recurrence is that cytotoxic therapy fails to target effectively glioma stem cells. Recent advances indicate that therapy-driven molecular evolution is a fundamental trait associated with glioblastoma recurrence. There is a growing body of evidence indicating that intratumor heterogeneity, longitudinal changes in molecular biomarkers and specific impacts of glioma stem cells need to be taken into consideration in order to increase the accuracy of molecular diagnostics still relying on readouts obtained from a single tumor specimen. Methods: This study integrates a multisampling strategy, longitudinal approach and complementary transcriptomic investigations in order to identify transcriptomic traits of recurrent glioblastoma in whole-tissue specimens of glioblastoma or glioblastoma stem cells. In this study, 128 tissue samples of 44 tumors including 23 first diagnosed, 19 recurrent and 2 secondary recurrent glioblastomas were analyzed along with 27 primary cultures of glioblastoma stem cells by RNA sequencing. A novel algorithm was used to quantify longitudinal changes in pathway activities and model efficacy of anti-cancer drugs based on gene expression data. Results: Our study reveals that intratumor heterogeneity of gene expression patterns is a fundamental characteristic of not only newly diagnosed but also recurrent glioblastomas. Evidence is provided that glioblastoma stem cells recapitulate intratumor heterogeneity, longitudinal transcriptomic changes and drug sensitivity patterns associated with the state of recurrence. Conclusions: Our results provide a transcriptional rationale for the lack of significant therapeutic benefit from temozolomide in patients with recurrent glioblastoma. Our findings imply that the spectrum of potentially effective drugs is likely to differ between newly diagnosed and recurrent glioblastomas and underscore the merits of glioblastoma stem cells as prognostic models for identifying alternative drugs and predicting drug response in recurrent glioblastoma. With the majority of recurrent glioblastomas being inoperable, glioblastoma stem cell models provide the means of compensating for the limited availability of recurrent glioblastoma specimens.

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Section: Introductionmentioning

confidence: 99%

Intratumoral Heterogeneity and Longitudinal Changes in Gene Expression Predict Differential Drug Sensitivity in Newly Diagnosed and Recurrent Glioblastoma

Kim

Sorokin

Kantelhardt

et al. 2020

Cancers

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“…Oncobox algorithm builds a personalized rating of target drugs for individual cancer patients. It is based on a simultaneous analysis of gene expression and molecular pathway activation in the patient's tumor and was shown to be effective in a retrospective cohort of gastric cancer patients [22], in several prospective advanced cancers cases [23][24][25], and in an ongoing prospective clinical investigation [26]. Gene expression profiling and whole exome sequencing was approved by institutional Review Board (IRB) at Clinical Center Vitamed, Moscow, Russia, protocol date 17 October 2016.…”

Section: Case Presentationmentioning

confidence: 99%

“…We identified significantly upregulated expression of MMP7, MMP9, BIRC5, and PD-L1. To investigate functional interplay of the discovered driver gene mutations with the gene expression profiles, we analyzed differentially regulated molecular pathways using Oncobox pathway analysis software [23,24]. For every pathway, a pathway activation level (PAL) value was calculated [49] corresponding to degree of a pathway activation or downregulation in a tumor sample (biopsy, stomach, and esophageal localizations) in comparison to the normal stomach sample.…”

Section: Analysis Of Molecular Pathway Activationmentioning

confidence: 99%

Transcriptomic and Genomic Testing to Guide Individualized Treatment in Chemoresistant Gastric Cancer Case

et al. 2020

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Gastric cancer is globally the fifth leading cause of cancer death. We present a case report describing the unique genomic characteristics of an Epstein–Barr virus-negative gastric cancer with esophageal invasion and regional lymph node metastasis. Genomic tests were performed first with the stomach biopsy using platforms FoundationOne, OncoDNA, and Oncopanel at Dana Farber Institute. Following neoadjuvant chemotherapy, residual tumor was resected and the stomach and esophageal residual tumor samples were compared with the initial biopsy by whole exome sequencing and molecular pathway analysis platform Oncobox. Copy number variation profiling perfectly matched the whole exome sequencing results. A moderate agreement was seen between the diagnostic platforms in finding mutations in the initial biopsy. Final data indicate somatic activating mutation Q546K in PIK3CA gene, somatic frameshifts in PIH1D1 and FBXW7 genes, stop-gain in TP53BP1, and a few somatic mutations of unknown significance. RNA sequencing analysis revealed upregulated expressions of MMP7, MMP9, BIRC5, and PD-L1 genes and strongly differential regulation of several molecular pathways linked with the mutations identified. According to test results, the patient received immunotherapy with anti-PD1 therapy and is now free of disease for 2 years. Our data suggest that matched tumor and normal tissue analyses have a considerable advantage over tumor biopsy-only genomic tests in stomach cancer.

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“…In turn, RNA sequencing is currently accepted as the gold standard analytic approach for high throughput screening of gene expression (SEQC/MAQC-III Consortium 2014). Comparison of tumor gene expression profiles with the normal tissues is crucial for understanding individual mechanisms of cancer development, progression and response to the targeted therapies (Rodon et al 2019;Buzdin et al 2019c).…”

Section: Introductionmentioning

confidence: 99%

RNA sequencing profiles and diagnostic signatures linked with response to ramucirumab in gastric cancer

Sorokin

Poddubskaya

Baranova

et al. 2020

Cold Spring Harb Mol Case Stud

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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.

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Personalized prescription of imatinib in recurrent granulosa cell tumor of the ovary: case report

Cited by 31 publications

References 22 publications

Intratumoral Heterogeneity and Longitudinal Changes in Gene Expression Predict Differential Drug Sensitivity in Newly Diagnosed and Recurrent Glioblastoma

Intratumoral Heterogeneity and Longitudinal Changes in Gene Expression Predict Differential Drug Sensitivity in Newly Diagnosed and Recurrent Glioblastoma

Transcriptomic and Genomic Testing to Guide Individualized Treatment in Chemoresistant Gastric Cancer Case

RNA sequencing profiles and diagnostic signatures linked with response to ramucirumab in gastric cancer

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