Sense-antisense gene pairs for patient stratification, prognosis, and therapeutic biomarkers identification

A computerized method according to any one of the preceding claims, wherein identifying the prognostic subset of SAGPs comprises:

• generation of a statistical partition model (SPM) for each of each SAGPs using said subject data;
• obtaining data characterizing the statistical significance of the SPMs;
• and
• identifying of a subset of said SAGPs using the data characterizing the statistical significance.

A computerized method of clinical outcome prognosis in a subject having a medical condition, the method comprising:

• receiving data representing parameters of one or more statistical partition models (SPMs) said SPMs being configured to stratify a cohort of subjects having the medical condition into subgroups, said parameters representing, for each gene pair of one or more sense-antisense gene pairs (SAGPs), a pair of lines in a two-dimensional space spanned by respective expression level values of respective genes i, j in the gene pair, the pair of lines being formed using two cut-off values ci and cj, and each of the lines having a non-zero angle α to each of two axis directions in the space indicating increasing values of a corresponding one of the expression level values;
• receiving expression level data representing expression levels in the subject of genes of one or more selected SAGPs;
• and
• for each SAGP of the selected SAGPs, comparing the expression levels to the pair of lines for the SAGP to obtain comparison data indicating on which side of the pair of lines the expression values for the subject lie, thereby obtaining a prediction of a subgroup to which the subject belongs.

A kit for predicting clinical outcome in a subject having a medical condition, the kit comprising:

• a plurality of polynucleotide sequences, ones of the plurality of polynucleotide sequences being capable of specifically hybridizing to and/or detecting a gene of a plurality of genes and/or an expression product of the gene to obtain respective gene expression values, wherein the plurality of genes comprises one or more of the sense-antisense gene pairs (SAGPs) listed in Table 1A, and written instructions for comparing, and/or a tangible computer-readable medium having stored thereon machine-readable instructions for causing a computer processor to compare, the respective gene expression values to optimal gene expression cut-off values, wherein the plurality of genes comprises no more than 100 genes;
• and wherein the optimal gene expression cut-off values are determined for each SAGP by:
• (i) defining a plurality of trial values for each of two cut-off values ci and cj;
• (ii) for each of a plurality of angles α, for each subject, and for each of the trial cut-off values ci and cj:
• (a) comparing the expression values to a respective pair of lines in a two-dimensional space spanned by the expression values to obtain comparison data indicating on which side of the pair of lines the expression values for the corresponding subject lie, the pair of lines being formed using the cut-off values ci and cj, each of the lines having angle α to a direction in the space indicating increasing values of a corresponding one of the expression values;
• and
• (b) generating at least one SPM based on the comparison data;
• and
• (iii) selecting the one of the SPMs (‘the maximally predictive SPM’) which has the maximal statistical value in predicting the survival times of the subjects,
• whereby the cut-off values ci and cj for the maximally predictive SPM are the optimal gene expression cut-off values.

A computerized method of composite survival prediction combining the output values from a plurality of SPMs associated with prognosis of a potentially fatal medical condition in each subject k of a set of K subjects suffering from the medical condition, each SPM being a model of the statistical significance of the expression level values of a corresponding set of one or more genes or gene pairs, the method employing test data which for each gene i of the pair of genes indicates a corresponding gene expression value yi,k of subject k;

• the method including:
• for each subject obtaining for each of the SPMs a respective risk level value indicative of a risk level for the subject;
• forming a weighted average of the risk level values using a set of respective weights, the weights being indicative of the relative quality of patient separation according to the given SPM versus others of the respective models in context of statistical significance of the relative risk statistics of the medical condition;
• comparing the weighted average with a cut-off value to obtain a prognosis value.