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The cancer cell proteome and transcriptome predicts sensitivity to targeted and cytotoxic drugs.

ABSTRACT: Tumors of different molecular subtypes can show strongly deviating responses to drug treatment, making stratification of patients based on molecular markers an important part of cancer therapy. Pharmacogenomic studies have led to the discovery of selected genomic markers (e.g., BRAFV600E), whereas transcriptomic and proteomic markers so far have been largely absent in clinical use, thus constituting a potentially valuable resource for further substratification of patients. To systematically assess the explanatory power of different -omics data types, we assembled a panel of 49 melanoma cell lines, including genomic, transcriptomic, proteomic, and pharmacological data, showing that drug sensitivity models trained on transcriptomic or proteomic data outperform genomic-based models for most drugs. These results were confirmed in eight additional tumor types using published datasets. Furthermore, we show that drug sensitivity models can be transferred between tumor types, although after correcting for training sample size, transferred models perform worse than within-tumor-type predictions. Our results suggest that transcriptomic/proteomic signals may be alternative biomarker candidates for the stratification of patients without known genomic markers.

SUBMITTER: Rydenfelt M

PROVIDER: S-EPMC6600015 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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The cancer cell proteome and transcriptome predicts sensitivity to targeted and cytotoxic drugs.

Rydenfelt Mattias M Wongchenko Matthew M Klinger Bertram B Yan Yibing Y Blüthgen Nils N

Life science alliance 20190628 4

Tumors of different molecular subtypes can show strongly deviating responses to drug treatment, making stratification of patients based on molecular markers an important part of cancer therapy. Pharmacogenomic studies have led to the discovery of selected genomic markers (e.g., BRAF<sup>V600E</sup>), whereas transcriptomic and proteomic markers so far have been largely absent in clinical use, thus constituting a potentially valuable resource for further substratification of patients. To systemat ...[more]

PMID: 31253656

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Project description:BackgroundNeutrophil-to-lymphocyte ratio (NLR) has recently attracted attention as a prognostic predictor in patients with non-small cell lung cancer (NSCLC) who receive immune checkpoint inhibitors (ICIs). However, the utility of NLR in relation to cytotoxic anticancer drugs or molecular targeted drugs remains unclear. We determined if NLR could predict the treatment efficacy and prognosis in NSCLC patients who receive cytotoxic anticancer drugs or molecular targeted drugs, as well as ICIs, in a cross-sectional manner.MethodsOf 658 patients with advanced NSCLC who received first-line systemic treatment in our hospital between 2008 and 2019, 312 who met the analytical criteria were included in the study. We retrospectively analyzed the ability of NLR with a cut-off value of 5 to predict time to treatment failure (TTF) and overall survival (OS) in patients who received the following treatments: first-line treatment with molecular targeted drugs (mt group, n=100); first-line treatment with cytotoxic anticancer drugs (wt group, n=212); and first-line treatment with cytotoxic anticancer drugs followed by ICIs (ICI group, n=58).ResultsIn the high- and low-NLR mt subgroups, median TTFs were 6.7 and 14.9 months (P<0.01), respectively, and median survival times (MSTs) were 17.8 and 39.1 months (P<0.01), respectively. In the high- and low-NLR wt subgroups, median TTFs were 1.5 and 5.8 months (P<0.01), and MSTs were 6.3 and 20.7 months (P<0.01), respectively. In the high- and low-NLR ICI subgroups, median TTFs were 1.3 and 6.8 months (P<0.01), and MSTs were 9.2 and 25.8 months (P<0.01), respectively. Multivariate analysis identified NLR as a significant independent predictor of TTF [hazard ratio (HR) 1.89, P=0.01; HR 2.51, P<0.01; and HR 5.06, P<0.01 in the mt, wt, and ICI groups, respectively) and OS (HR 3.81, P<0.01; HR 2.59, P<0.01; and HR 2.48, P<0.01, respectively).ConclusionsThis study showed that NLR might be a predictor of treatment efficacy and prognosis in advanced NSCLC patients who receive various systemic treatments. This finding of consistent applicability of NLR to a wide variety of systemic treatments is of great significance.

Project description:A major impediment to the effective treatment of patients with PDAC (Pancreatic Ductal Adenocarcinoma) is the molecular heterogeneity of the disease, which is reflected in an equally diverse pattern of clinical responses to therapy. We developed an efficient strategy in which PDAC samples from 17 consecutively patients were obtained by EUS-FNA or surgery, their cells maintained as a primary culture and tumors as breathing tumors by xenografting in immunosuppressed mice. For these patients a clinical follow up was obtained. On the breathing tumors we studied the RNA expression profile by an Affymetrix approach. We observed a significant heterogeneity in their RNA expression profile, however, the transcriptome was able to discriminate patients with long- or short-time survival which correspond to moderately- or poorly-differentiated PDAC tumors respectively. Cells allowed us the possibility to analyze their relative sensitivity to several anticancer drugs in vitro by developing a chimiogram, like an antibiogram for microorganisms, with several anticancer drugs for obtaining an individual profile of drug sensitivity and as expected, the response was patient-dependent. Interestingly, using this approach, we also found that the transcriptome analysis could predict the sensitivity to some anticancer drugs of patients with a PDAC. In conclusion, using this approach, we found that the transcriptome analysis could predict the sensitivity to some anticancer drugs and the clinical outcome of patients with a PDAC. PDAC samples from 17 consecutively patients were obtained by Endoscopic Ultrasound-Guided Fine-Needle Aspiration (EUS-FNA) or surgery. Consents of informed patients were collected, and the ethics review board of the three centers approved the study. All samples were anonymized and obtained in accordance with institutional review boards. EUS-FNA cells were maintained as a primary culture and tumors as breathing tumors by xenografting in immunosuppressed mice. We characterized 17 PDAC-derived xenografts by duplicate. Total RNA was extracted and hybridized on Human Gene 2.0 (Genechip, Affymetrix) as described previously (Hamidi et al. JCI 122: 2092-2103, 2012).

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The cancer cell proteome and transcriptome predicts sensitivity to targeted and cytotoxic drugs.

Publications

The cancer cell proteome and transcriptome predicts sensitivity to targeted and cytotoxic drugs.

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