Methods of determining the prognosis of an adenocarcinoma
Inventors
Harris, Curtis C. • Seike, Masahiro • Wang, Xin Wei
Assignees
United States, AS REPRESENTED BY SECRETARY Dhhs • US Department of Health and Human Services
Publication Number
US-9464324-B2
Publication Date
2016-10-11
Expiration Date
2027-07-16
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Abstract
Methods are disclosed for determining the prognosis of a subject with an adenocarcinoma in an organ, such as the lung. The methods can include quantitating expression of a plurality of cytokines of interest, such as IL-1a, IL-1b, IL-2, IL-8, IL-10, IL-12, IL-15, IFN-γ and TNF-a in the adenocarcinoma and in non-cancerous tissue in the organ. Altered expression of IL-1a, IL-1b, IL-2, IL-8, IL-10, IL-12, IL-15, IFN-γ and TNF-a in the adenocarcinoma as compared to a control and in non-cancerous tissue in the organ as compared to a control determines the prognosis for the subject. Methods for determining if a therapeutic agent is effective as an anti-cancer agent are also disclosed.
Core Innovation
Methods are disclosed for determining the prognosis of a subject with an adenocarcinoma in an organ, such as the lung, by quantitating expression of a plurality of cytokines including IL-1a, IL-1b, IL-2, IL-6, IL-8, IL-10, IL-12, IL-15, CSF-1, IFN-γ and TNF-a in both the adenocarcinoma and in non-cancerous tissue in the organ. Altered expression of these cytokines compared to controls determines the prognosis for the subject. The inventors identified a cytokine gene signature called CLASS-11 that accurately classifies patients according to risk of death from adenocarcinoma, including stage I disease. The cytokine gene signature from noncancerous lung tissue primarily reflects lymph node status, while the tumor tissue signature associates with prognosis independent of lymph node status.
The problem being solved is the need for markers to determine prognosis and whether non-small cell lung cancer (NSCLC) will metastasize, especially given that lung cancer remains a leading cause of death with poor outcomes despite current therapies. There is a need for methods that can identify subjects with adenocarcinoma who have poor or good prognosis to guide treatment strategies, including selection of aggressive versus less aggressive therapeutic regimens.
Claims Coverage
The patent includes independent claims directed to methods for treating subjects with lung adenocarcinoma using measurement of cytokine expression, and methods for classifying prognosis and metastasis based on cytokine mRNA expression.
Method for treating lung adenocarcinoma by measuring increased cytokine expression
A method of treating a subject with stage I, IB, or II lung adenocarcinoma comprising contacting adenocarcinoma samples with nucleic acid probes or primers specific for cytokines IL-1a, IL-1b, IL-2, IL-6, IL-8, IL-10, IL-12, IL-15, CSF-1, IFN-γ, and TNF-a; measuring increased nucleic acid expression of either (a) IL-1a, IL-8, and TNF-a or (b) IL-1a, IL-1b, IL-2, IL-6, IL-8, IL-10, IL-12, IL-15, TNF-a, CSF-1 and IFN-γ compared to control values from a cancer-free subject; and administering chemotherapy or radiation following surgery.
Use of centroid values from known subject cytokine expression as control for prognosis determination
Employing control centroid values of cytokine expression from cancer-free subjects' lung tissue to compare with patient cytokine expression, to aid in determining prognosis and treatment.
Using statistical and computational methods like shrunken centroid calculation and PAM for cytokine expression analysis
Applying statistical classifiers such as shrunken centroid calculations and prediction analysis of microarrays (PAM) to generate centroids from known cytokine expression data and classify the prognosis and metastasis status of patient samples by comparison to centroids.
Method for predicting prognosis by comparing cytokine expression in tumor and non-cancerous tissue
Measuring cytokine expressions in lung adenocarcinoma and non-cancerous tissue, generating centroids from known cases, and classifying new samples by determining nearest centroid values to predict metastasis and prognosis.
The claims cover methods of treating lung adenocarcinoma based on quantitating specific cytokine expressions, employing statistical classifiers such as PAM, and using control values from cancer-free subjects to determine prognosis and guide therapy post-surgery.
Stated Advantages
The methods provide a significant clinical benefit by enabling classification of adenocarcinoma patients into high or low risk of death groups.
They allow identification of early-stage lung cancer patients (including stage I) who have a poor prognosis and may benefit from more aggressive treatment.
The cytokine gene signature CLASS-11 is an independent prognostic factor and robust predictor of disease progression.
The methods support selection of tailored therapeutic regimens, such as the decision to apply adjuvant chemotherapy or radiation post-surgery.
Documented Applications
Determining prognosis of subjects with adenocarcinoma, including likelihood of survival and metastasis, particularly lung adenocarcinoma.
Guiding selection of therapeutic regimens, including identifying stage I and II lung adenocarcinoma patients who may benefit from aggressive adjuvant therapy.
Evaluating effectiveness of anti-cancer agents by comparing cytokine expression before and after treatment.
Use of cytokine-specific arrays and kits for detecting mRNA or protein expression to classify prognosis and select treatments for adenocarcinoma patients.
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