O-122 Gene expression signatures for prognosis in NSCLC, coupled with signatures of oncogenic pathway deregulation, provide a novel approach for selection of molecular targets

Lung Cancer ◽  
2005 ◽  
Vol 49 ◽  
pp. S42-S43
Author(s):  
R. Petersen ◽  
A. Bild ◽  
H. Dressman ◽  
M. Joshi ◽  
D. Conlon ◽  
...  
Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4550-4550
Author(s):  
Merav Bar ◽  
Alice Woo ◽  
Mohammed Toufiq ◽  
Sabri Boughorbel ◽  
Darawan Rinchai ◽  
...  

Introduction Allogeneic Hematopoietic Cell Transplantation (allo HCT) is currently the only curative therapy for high-risk hematologic malignancies due to the immune response of the donor cells against the malignant cells (graft versus tumor effect; GVT), but with the cost of Graft Versus Host Disease (GVHD). Despite extensive research, very few predictors of GVHD and GVT have been identified to date. Additionally, clinical GVHD diagnosis can be challenging due to chemotherapy-related or infection-related organ toxicity manifestations, which further complicate prediction and treatment stratification algorithms. In order to study the mechanisms of GVHD and GVT and to identify potential GVHD markers we apply a novel approach, called Transcriptome Fingerprint Assay (TFA), relying on high frequency sampling and blood transcript profiling. The TFA is a multiplex microfluidics q-PCR based assay linked with a computational model for modular functional transcriptome analyses, uniquely tailored to answer complex questions on immune perturbations through frequent profiling of gene expression signatures from < 1 ml of blood (Chaussabel and Baldwin. Nat Rev Immunol 2014, Speake et al. Clin Exp Immunol 2017). This approach has been successfully applied to stratify patients' prognosis in autoimmune and infectious diseases (Banchereau R et al. Cell 2016, Dunning et al. Nat Immunol 2018). In our study we use the TFA to capture longitudinal immune signatures as dynamic "snapshots" of the patient's immune system after HCT. Hypotheses Fluctuations over-time in gene expression of allo HCT patients' immune system reflect the pathologic/disease control programs (GVHD/GVT) and may be used to identify diagnostic and predictive biomarkers. GVHD/GVT control immune programs depend on the "inner" interface between the donor immune-system and the recipient, and are influenced by external variables, as infections or drugs. These variables can affect the immune system-related gene expression and can be measured. Objectives To systematically measure gene expression signatures in immune perturbations post-allo HCT, in order to: Identify GVHD-related immune signatures consistent with clinical diagnosis of GVHD.Predict and stratify therapy-resistant GVHD and severe chronic GVHD, according to immune signatures.Identify links (causative and consequential) between GVHD, GVT, relapse, and other post-transplant immune perturbations (e.g. infections). Methods Enroll 250 allo HCT patients to populate a "GVHD cohort" and a "non-GVHD cohort" of 50 patients each, and 50 donors (healthy controls cohort) . Patients donate micro-quantities of blood (50 to 600 microliters), weekly until day 100 post-transplant and every 2 weeks thereafter until 2 years after transplant. Detailed clinical, laboratory and therapy annotations are captured during the follow-up. Gene expression of 264 immune-related genes for each sample are measured through Fluidigm BioMark high throughput qPCR system, and normalized to the geometric mean Ct of 8 housekeeping genes. Data interpretation is performed through TFA modular analyses and correlated with the clinical annotations. Results Results of three series of patients' samples are shown to exemplify the potential of TFA as a method to study the mechanisms of GVHD and GVT. All three patients underwent myeloablative peripheral blood stem cell transplant from an HLA identical sibling donor. Two patients developed steroid responsive-acute GVHD (patient #1: GVHD stage I was diagnosed on day 38 post HCT, patient #4: GVHD stage III was diagnosed on day 21 post HCT). One patient (Patient #6) did not develop clinical GVHD, but routine skin biopsy on day 80 revealed apoptotic cells consistent with subclinical skin GVHD. Principal Component Analysis (PCA) of the three patients' series is shown in Figure 1, the dynamic transcriptomes according to TFA modules of patients #1 and #6 are shown in Figure 2, and representative TFA modular fingerprints are shown in Figure 3. Conclusion We anticipate that using the TFA approach will help to fill knowledge gaps instrumental to solve clinical dilemmas related to allo HCT complications, and to improve the clinical outcomes of allo HCT patients. Disclosures No relevant conflicts of interest to declare.


2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e23142-e23142 ◽  
Author(s):  
Anton Buzdin ◽  
Maxim Sorokin ◽  
Alexander Glusker ◽  
Andrew Garazha ◽  
Elena Poddubskaya ◽  
...  

e23142 Background: Anticancer target drugs (ATDs) specifically bind and inhibit molecular targets that play important roles in tumorigenesis. More than 150 different ATDs have been approved for clinical use worldwide, and the clinicians are faced with the problem of choosing the best therapeutic solution for each patient. The problem of efficient ATD selection remains largely unsolved and personalized approaches are needed to select the best ATD candidates for individual patients. Methods: We propose a new approach termed OncoFinder. It is based on digesting gene expression profiles for the analysis of activation of intracellular signalling pathways as a marker for the selection of target therapies. The original bioinformatic algorithms were integrated with the databases featuring molecular drug targets, compositions of signalling pathways, including the functional role of each gene product, for more than 1700 pathways (Buzdin, Front.Genet 2014; Ozerov, Nature Communications 2016). Results: We showed that pathway activation strengths are more stable and reliable biomarkers of cancer than the expressions of individual genes. OncoFinder allows to detect changes at the level of pathway activation and to predict the effectiveness of drugs based on the knowledge of their molecular targets. We applied it to find new biomarkers of clinical response to the ATD cetuximab; for modelling the combined chemotherapy of acute myeloid leukemia and combined anti-VEGF/BRAF therapy of melanoma. For two unrelated datasets obtained for colon cancer patients before treatment with the ATD bevacizumab, we were able to distinguish between those who responded to treatment and not (p < 0.01). We next assayed biopsies for kidney cancer patients with known responses to the ATD sorafenib. The responders and non-responders showed a significant difference (p = 0.02). Finally, the OncoFinder platform was prospectively used for decision making support to patients with advanced metastatic solid tumors (n = 23). The efficiency of the ATD treatment was 61% (complete + partial response, RECIST). Conclusions: OncoFinder method may be effective for predicting response to ATD based on high throughput gene expression profiles.


2002 ◽  
Vol 35 (3) ◽  
pp. 160-170 ◽  
Author(s):  
Pierre R. Bushel ◽  
Hisham K. Hamadeh ◽  
Lee Bennett ◽  
James Green ◽  
Alan Ableson ◽  
...  

2008 ◽  
Vol 134 (4) ◽  
pp. A-66
Author(s):  
Katherine S. Garman ◽  
Marian Grade ◽  
Chaitanya Acharya ◽  
Kelli S. Walters ◽  
Shivani Sud ◽  
...  

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