Validation of the Concept of a Common Typical Time of Disease Duration for Hepatocellular Carcinoma Patients Using the Fisher Information Processing of Tumor Imaging Results Combined With Network Phenotyping Strategy Quantification of Individual Patient Clinical Profile Patterns.

A primary goal of current clinical cancer research is the identification of prognostic tumor subtypes. It is increasingly clear that tumor growth depends on both internal tumor factors, and factors that are external to the tumor, such as microenvironment. We recently showed that parameter values alone are less important than the patterns of all patient parameters together for the identification of prognostic subtypes and have identified a network phenotyping strategy method to quantitatively describe the dependency of the tumor on the environment, to characterize hepatocellular carcinoma (HCC) subtypes. We have also shown that information about tumor mass together with patterns of other prognostic factors is related to survival. We now use a different patient cohort to validate this prognostic approach. A main finding is our identification of a common time of total disease duration (TDD) for every HCC patient. Clinical prognosis at the time of baseline patient evaluation is then calculable as the difference between TDD and the time from disease onset to diagnosis (T(onset)). We show that the total pattern of all parameter values and the differences in the relationships between this pattern and a reference pattern that, together with the tumor mass, best reflects the patient's prognosis at baseline. Our approach led us to identify 15 different composite HCC subtypes. Our results highlight the nearly identical TDD in all patients, which must therefore be a characteristic of the HCC disease, as opposed to the variable quantity of T(onset), which is impacted by multiple macro- and micro-environmental factors.

Evaluation of total hepatocellular cancer lifespan, including both clinically evident and preclinical development, using combined network phenotyping strategy and fisher information analysis.

We previously showed that for hepatocellular cancer (HCC) prognostication, disease parameters need to be considered within a total personal clinical context. This requires preserving the coherence of data values, observed simultaneously for each patient during baseline diagnostic evaluation. Application of the Network Phenotyping Strategy (NPS) provided quantitative descriptors of these patient coherences. Combination of these descriptors with Fisher information about the patient tumor mass and the histogram of the tumor masses in the whole cohort permitted estimation of the time from disease onset until clinical diagnosis (t(baseline)). We found faster growth of smaller tumors having total masses<70 (80% of cohort) which involved about three times more interacting cellular processes than were observed for slower growing larger tumors (20% of cohort) with total masses>70. Combining the clinical survival and t(baseline) normalized all HCC patients to a common 1,045 days of mean total disease duration (t(baseline) plus post diagnosis survival). We also found a simple relationship between the baseline clinical status, t(baseline), and survival. Every difference between individual patient baseline clinical profiles and special coherent clinical status (HL1) reduced the above common overall survival (OVS) by 65 days. In summary, we showed that HCC patients with any given tumor can best have their tumor biology understood, when account is taken of the total clinical and liver contexts, and with knowing the point in the tumor history when an HCC diagnosis is made. This ability to compute the t(baseline) from standard clinical data brings us closer to calculating survival from diagnosis of individual HCC patients.

Identification of two clinical hepatocellular carcinoma patient phenotypes from results of standard screening parameters.

Previous work has shown that two general processes contribute to hepatocellular cancer (HCC) prognosis: liver damage, monitored by indices such as blood bilirubin, prothrombin time (PT), and aspartate aminostransferase (AST); and tumor biology, monitored by indices such as tumor size, tumor number, presence of portal vein thrombosis (PVT) and blood alpha-fetoprotein (AFP) levels. These processes may affect one another, with prognostically significant interactions between multiple tumor and host parameters. These interactions form a context that provide personalization of the prognostic meaning of these factors for every patient. Thus, a given level of bilirubin or tumor diameter might have a different significance in different personal contexts. We previously applied network phenotyping strategy (NPS) to characterize interactions between liver function indices of Asian HCC patients and recognized two clinical phenotypes, S and L, differing in tumor size and tumor nodule numbers. Our aim was to validate the applicability of the NPS-based HCC S/L classification on an independent European HCC cohort, for which survival information was additionally available. Four sets of peripheral blood parameters, including AFP-platelets, derived from routine blood parameter levels and tumor indices from the ITA.LI.CA database, were analyzed using NPS, a graph-theory-based approach that compares personal patterns of complete relationships between clinical data values to reference patterns with significant association to disease outcomes. Without reference to the actual tumor sizes, patients were classified by NPS into two subgroups with S and L phenotypes. These two phenotypes were recognized using solely the HCC screening test results, consisting of eight common blood parameters, paired by their significant correlations, including an AFP-platelets relationship. These trends were combined with patient age, gender, and self-reported alcoholism into NPS personal patient profiles. We subsequently validated (using actual scan data) that patients in L phenotype group had 1.5× larger mean tumor masses relative to S, P = 6 × 10(-16). Importantly, with the new data, liver test pattern-identified S-phenotype patients had typically 1.7× longer survival compared to L-phenotype patients. NPS integrated the liver, tumor, and basic demographic factors. Cirrhosis-associated thrombocytopenia was typical for smaller S tumors. In L tumor phenotype, typical platelet levels increased with the tumor mass. Hepatic inflammation and tumor factors contributed to more aggressive L tumors, with parenchymal destruction and shorter survival. NPS provides integrative interpretation for HCC behavior, identifying two tumor and survival phenotypes by clinical parameter patterns. The NPS classifier is provided as an Excel tool. The NPS system shows the importance of considering each tumor marker and parameter in the total context of all the other parameters of an individual patient.

Macro- and micro-environmental factors in clinical hepatocellular cancer.

We previously developed a network phenotyping strategy (NPS), a graph theory-based transformation of clinical practice data, for recognition of two primary subgroups of hepatocellular cancer (HCC), called S and L, which differed significantly in their tumor masses. In the current study, we have independently validated this result on 641 HCC patients from another continent. We identified the same HCC subgroups with mean tumor masses 9 cm x n (S) and 22 cm x n (L), P<10(-14). The means of survival distribution (not available previously) for this new cohort were also significantly different (S was 12 months, L was 7 months, P<10(-5)). We characterized nine unique reference patterns of interactions between tumor and clinical environment factors, identifying four subtypes for S and five subtypes for L phenotypes, respectively. In L phenotype, all reference patterns were portal vein thrombosis (PVT)-positive, all platelet/alpha fetoprotein (AFP) levels were high, and all were chronic alcohol consumers. L had phenotype landmarks with worst survival. S phenotype interaction patterns were PVT-negative, with low platelet/AFP levels. We demonstrated that tumor-clinical environment interaction patterns explained how a given parameter level can have a different significance within a different overall context. Thus, baseline bilirubin is low in S1 and S4, but high in S2 and S3, yet all are S subtype patterns, with better prognosis than in L. Gender and age, representing macro-environmental factors, and bilirubin, prothrombin time, and AST levels representing micro-environmental factors, had a major impact on subtype characterization. Clinically important HCC phenotypes are therefore represented by complete parameter relationship patterns and cannot be replaced by individual parameter levels.

A new mathematical model for the interpretation of translational research evaluating six CTLA-4 polymorphisms in high-risk melanoma patients receiving adjuvant interferon.

Adjuvant therapy of stage IIB/III melanoma with interferon reduces relapse and mortality by up to 33% but is accompanied by toxicity-related complications. Polymorphisms of the CTLA-4 gene associated with autoimmune diseases could help in identifying interferon treatment benefits. We previously genotyped 286 melanoma patients and 288 healthy (unrelated) individuals for six CTLA-4 polymorphisms (SNP). Previous analyses found no significant differences between the distributions of CTLA-4 polymorphisms in the melanoma population vs. controls, no significant difference in relapse free and overall survivals among patients and no correlation between autoimmunity and specific alleles. We report new analysis of these CTLA-4 genetic profiles, using Network Phenotyping Strategy (NPS). It is graph-theory based method, analyzing the SNP patterns. Application of NPS on CTLA-4 polymorphism captures allele relationship pattern for every patient into 6-partite mathematical graph P. Graphs P are combined into weighted 6-partite graph S, which subsequently decomposed into reference relationship profiles (RRP). Finally, every individual CTLA-4 genotype pattern is characterized by the graph distances of P from eight identified RRP's. RRP's are subgraphs of S, collecting equally frequent binary allele co-occurrences in all studied loci. If S topology represents the genetic "dominant model", the RRP's and their characteristic frequencies are identical to expectation-maximization derived haplotypes and maximal likelihood estimates of their frequencies. The graph-representation allows showing that patient CTLA-4 haplotypes are uniquely different from the controls by absence of specific SNP combinations. New function-related insight is derived when the 6-partite graph reflects allelic state of CTLA-4. We found that we can use differences between individual P and specific RRPs to identify patient subpopulations with clearly different polymorphic patterns relatively to controls as well as to identify patients with significantly different survival.

Phenotypic Categorization and Profiles of Small and Large Hepatocellular Carcinomas.

We used a database of 4139 Taiwanese HCC patients to take a new approach (Network Phenotyping Strategy) to HCC subset identification. Individual parameters for liver function tests, complete blood count, portal vein thrombosis, AFP levels and clinical demographics of age, gender, hepatitis or alcohol consumption, were considered within the whole context of complete relationships, being networked with all other parameter levels in the entire cohort. We identified 4 multi-parameter patterns for one tumor phenotype of patients and a separate 5 multi-parameter patterns to characterize another tumor phenotype of patterns. The 2 subgroups were quite different in their clinical profiles. The means of the tumor mass distributions in these phenotype subgroups were significantly different, one being associated with larger (L) and the other with smaller (S) tumor masses. These significant differences were seen systematically throughout the tumor mass distributions. Essential and common clinical components of L-phenotype patterns included simultaneously high blood levels of AFP and platelets plus presence of portal vein thrombosis. S included higher levels of liver inflammatory parameters. The 2 different parameter patterns of L and S subgroups suggest different mechanisms; L, possibly involving tumor-driven processes and S more associated with liver inflammatory processes.

Small hepatocellular carcinomas and thrombocytopenia.

BACKGROUND: Clinical phenotypes of small and large hepatocellular carcinomas (HCCs) are not well characterized. AIM: To evaluate the characteristics of small HCCs diagnosed by screening. METHOD: A cohort of 430 small HCCs that were diagnosed through screening, were dichotomized according to a size of ≤ 3 cm or >3 cm maximum tumor diameter and compared for radiological and blood-test parameters. RESULTS: There were 330 males and 100 females. A higher percent of females had smaller tumors. The majority of patients had single tumors, but 15% of those with larger tumors had portal vein thrombosis (PVT) compared to 5% of those with smaller tumors. Significant differences between the tumor-size groups included alpha-fetoprotein (AFP) values and platelet counts, with thrombocytopenia and elevated bilirubin levels being associated with smaller tumors. In comparing PVT-positive and PVT-negative patients, AFP levels and platelet counts were also significantly different between the 2 groups. A mean multinomial multiple logistic regression model was developed for maximum tumor diameter plus PVT. CONCLUSIONS: The finding of larger tumors being associated with normal platelets and bilirubin levels in comparison to smaller tumors having thrombocytopenia reveals 2 different patterns of HCC presentation.

Thrombocytopenia in relation to tumor size in patients with hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) size at diagnosis is important in management. Without screening programs, tumor size at diagnosis is heterogeneous. AIMS: To examine the clinical parameters related to tumor size. METHODS: Using prospectively collected data from a 1,100-patient biopsy-proven HCC cohort presenting in the absence of screening, tumor sizes were ordered and trichotomized and the resulting terciles were compared for tumor and blood parameters. RESULTS: The terciles were significantly different with respect to portal hypertension and thrombocytopenia, which were present in a higher percent of tercile I patients with smaller tumors. Tercile III patients with larger HCCs had the highest serum α-fetoprotein (AFP), γ-glutamyl transpeptidase (GGTP), and alkaline phosphatase (ALKP) levels and the most portal vein (PV) thrombosis. Subclassification of tercile I patients by AFP showed that patients with high serum AFP had increased numbers of tumor nodules, more PV thrombosis, higher bilirubin, ALKP, and GGTP levels, and shorter survival. CONCLUSIONS: Smaller-tumor tercile I patients had more advanced portal hypertension with thrombocytopenia than did larger-tumor patients. Tercile I patients with higher AFP levels had more frequent PV thrombosis and worse survival than those with lower AFP levels. Elevated serum GGTP and ALKP levels appear to be associated with a more aggressive HCC phenotype. These differing patterns suggest more than one HCC pathway.

Small hepatocellular carcinoma in Chinese patients.

BACKGROUND/AIMS: Physicians aim to either prevent HCC by treating the underlying cause or to diagnose it at its earliest, clinically-observable stages by surveillance, for maximal treatment benefit. Surveillance depends predominantly on radiological screening and less satisfactorily on AFP blood tests. We previously examined a large cohort of unresectable HCC patients and found some useful, statistically-significant, prognostic factors. METHODOLOGY: We evaluated 325 Chinese HCC patients with hepatitis and were diagnosed with small HCCs by surveillance in Taiwan and we examined their clinical characteristics at time of HCC diagnosis, after ordering the patients according to their tumor mass and then analyzing trends in the data. RESULTS: We found that gender is associated with tumor mass and the patterns are different in patients with HBV or HCV. Male gender and young age were typical for smaller tumor mass phenotypes, but there was no gender bias for larger or multiple tumor phenotypes. Typical serum GGTP and ALKP levels increased linearly with tumor mass, but the AFP patterns were more complex. The relationship of serum AFP to GGTP and of albumin to bilirubin, help identify tumor mass phenotypes. CONCLUSIONS: Hepatitis-associated small HCCs that were diagnosed by surveillance demonstrate several phenotypic subsets, with serum GGTP increasing and albumin decreasing in many patients as tumor mass increased. In a patient at risk of HCC, elevated serum GGTP, AFP or ALKP, regardless of bilirubin level, might be a stimulus for appropriate radiology for early HCC diagnosis.

Small HCCs identified by screening.

BACKGROUND: Survival in HCC depends on diagnosis at early tumor stage, best achieved through surveillance radiology. There is also a need for complementary serum tests. METHODS: We evaluated baseline liver function parameters from a cohort of 231 HCC patients who were diagnosed by surveillance. They were ordered according to their tumor mass and trends in the data were analyzed. RESULTS: Trends in serum GGTP levels increased linearly with increases in small tumor mass, but the patterns for AFP levels were more complex and elevated only with larger tumor mass. ALKP levels were elevated in association with small tumors and further increased with increasing tumor mass. The relationships of serum AFP to GGTP, of albumin to bilirubin and of ALKP to bilirubin, helped identify tumor mass phenotypes. There was an especially important relationship between serum bilirubin and AFP, suggesting that HCC growth and liver factors were interdependent. CONCLUSIONS: Small HCCs demonstrated several phenotypic sub-groups, with serum GGTP and ALKP increasing and albumin decreasing in many patients with increasing tumor mass.

Significance of increased serum GGTP levels in HCC patients.

A large dataset of patients with biopsy-proven and unresectable HCC who were prospectively followed from diagnosis till death, was examined for the prognostic significance of serum GGTP levels. Their survival-ordered baseline clinical parameter data was examined. Two cohorts of patients with both low AFP and bilirubin levels were identified, who had serum GGTP levels with an increasing trend with increasing AFP levels. The survival of these patients also decreased as their GGTP levels trended up, as did their tumor masses. By contrast, in patients with elevated serum AFP levels, the GGTP trends were less informative, although patients with the highest AFP levels had a worse prognosis if their GGTP levels were simultaneously elevated. The results suggest that following trends in serum GGTP levels, in the context of specific ranges of AFP and bilirubin levels, might be useful in diagnosis of small HCCs.

HCC in young adults.

A large cohort of unresectable and untransplantable biopsy-proven HCC patients was rank-ordered for survival. Non-random clustering by age was noted, with 3 sub-cohorts of younger patients with survival in the range of 90-360 days. One sub-cohort had a predominance of females. Tumor numbers were well monitored by serum AFP, but tumor mass was better monitored by serum GGTP. In contrast to the older patients, the probability of hepatitis appeared to have a major impact on their survival and these patients tended to have larger numbers of smaller tumors, consistent with the idea of a hepatitis-mediated carcinogenic field defect.

Low alpha-fetoprotein hepatocellular carcinoma.

BACKGROUND AND AIM: A large proportion of hepatocellular carcinoma (HCC) patients do not secrete elevated levels of the tumor marker alpha-fetoprotein (AFP). There is little published guide to prognostic features of this patient subset. METHODS: We interrogated a large HCC database in which all patients had been followed until death, to examine which features might be prognostically useful. RESULTS: We found 413 biopsy-proven unresectable HCC patients with low serum AFP values. Serum gamma glutamyl transpeptidase (GGTP) levels were one of the most significant factors for survival. This dichotomization into low and high GGTP levels separated the patients into distinctive survival ranges. Patients with GGTP levels < 110 U/100 mL and small tumors had longest survival > 795 days. Patients with GGTP > or = 110 U/mL and large tumors with the presence of portal vein thrombosis had the shortest survival range of 300-560 days. CONCLUSIONS: Serum levels of the onco-fetal protein GGTP represent a useful prognostic parameter in HCC patients with low AFP levels.

Network-based analysis of survival for unresectable hepatocellular carcinoma.

Primary hepatocellular cancer (HCC) classification systems are based on histopathology and radiology, yet clinical intuition and experience suggest that natural history and disease progression have distinctive clinical features, consistent with a cluster of homogeneous entities within a heterogeneous cohort. We built a rigorous, sequenced, graph-based strategy of network phenotyping analysis (NPA) to combine data smoothing to minimize stochasticity, multivariate analysis to identify ambiguity and prioritize key variables, and k-partite graphs to visualize coherence. In 890 unresectable HCC patients, we selected 13 baseline clinical variables. After rank ordering by survival, we found data structure that exhibited coherence between variables, implying heterogeneity in which survival varied depending on the associated variable profile. The NPA data compression identified five distinctive clinical phenotypes, based only on gender, age, and levels of serum bilirubin, serum alpha-fetoprotein (AFP), and serum gamma glutamyl transpeptidase (GGTP). The phenotypic profiles for gender and age were substantially different. Young, male patients had a low survival, while elderly women had a long survival. Novel clusters included young men, with high AFP levels for their level of bilirubin, as well as women of all ages, with high GGTP values for their level of AFP. The identification of phenotypic groups of HCC may be of value in studies designed to understand their underlying pathophysiology. We conclude that NPA offers a new useful tool in the reclassification of HCC.

HCC in older patients.

BACKGROUND: Hepatocellular carcinoma (HCC) is a heterogeneous disease, with many poorly-defined prognostic patient subsets. Identification of discrete subsets will aid rational patient and treatment selection. METHODS: A database with 778 biopsy-proven, unresectable and untransplantable HCC patients who were followed from diagnosis till death was interrogated. Using a moving average algorithm, patients were ordered by survival and then survival cohorts were analyzed according to standard liver function and CT characteristic parameters. RESULTS: We found characteristic age clustering groupings by survival. In the older age patients, two survival sub-groups were identified, with 45-80 days in one and 330-1,250 days survival in the other group. The longer surviving group had the lowest serum bilirubin and AFP levels and the lowest tumor mass. Remarkably, the trends for both AFP and bilirubin were similar, suggesting that they were not independent variables. This idea was supported by the similar correlation of typical AFP with GGTP, ALKP and SGOT levels. CONCLUSIONS: A large HCC cohort showed significant age clustering characteristics for survival, especially in older patients. AFP, bilirubin and age were found to be inter-related factors for HCC severity and survival.

Feasibility of adolescents to conduct community-based participatory research on obesity and diabetes in rural Appalachia.

Community-Based Participatory Research (CBPR) has been advocated to translate advances in health care sciences to the community. We describe a novel approach applied to obesity management and diabetes prevention. This takes advantage of a network of science clubs organized by the Health Sciences and Technology Academy (HSTA) for extracurricular activity of disadvantaged high school students in rural Appalachia. Physician scientists and educators provided an intensive summer course on CBPR, ethics, and study design on obesity management and diabetes prevention. Ethical certification for CBPR investigation was obtained for 210 students and 18 mentors for a study on the prevalence of obesity and Type II diabetes within their community. Over a 6-month period, 989 had a collection of complete analyzable data, of which 103 had diabetes. The proportion with obesity (BMI > or = 30) was over 50%. The frequency of diabetes was related to increasing BMI. When BMI > or = 40, the frequency approached 50%, and exhibited a clear familial distribution. We conclude that trained adolescents can effectively conduct CBPR, and obesity and diabetes are more prevalent than previously reported in this community. This experience provides encouragement to conduct future studies to infl uence weight management from high-risk populations in this medically disadvantaged community.

Family networks of obesity and type 2 diabetes in rural Appalachia.

The prevalence of obesity and diabetes has been studied in adolescent and adult populations in poor, medically underserved rural Appalachia of West Virginia. A web-based questionnaire about obesity and diabetes was obtained in 989 family members of 210 Community Based Clinical Research (CBPR) trained adolescent members of a network of 18 science clubs, incorporating 142 families. After age-correction in < 20 years old, 50% of both adolescents and adults were obese. The frequency distribution of obesity was trimodal. In the overall population 10.4% had type 2 diabetes, while 24% of adult, obese subjects had type 2 diabetes. A new metric, the family diabetes risk potential, identified a trimodal distribution of risk potential. In the lowest most common distribution 43% of families had a diabetic family member. In the intermediate distribution, 69% had a diabetic family member, and in the distribution with highest scores all the families had a diabetic member. In conclusion, the poorest counties of rural Appalachia are at crisis level with the prevalence of obesity and diabetes. The distribution of age-corrected obesity and family diabetes risk potential are not normally distributed. We suggest that targeting individual family units at greatest risk offers the most efficient strategy for ameliorating this epidemic.

Tumor and liver determinants of prognosis in unresectable hepatocellular carcinoma: a large case cohort study.

OBJECTIVES: 967 patients with unresectable and untransplantable, biopsy-proven hepatocellular carcinoma (HCC) were prospectively evaluated at baseline and followed up till death. Survival was the end point. RESULTS: We found that male gender, ascites, cirrhosis, portal vein thrombosis (PVT), elevated AFP or bilirubin, or alkaline phosphatase, were each statistically significant adverse prognostic factors. Patients with normal AFP survived longer than those with elevated AFP, even in the presence of PVT, large or bilobar tumors or cirrhosis. We used a bivariate analysis to separate patient sub groups based on liver function and tumor characteristics and found clear discrimination in survival between subsets; in addition both cirrhosis and presence of PVT were significant factors. We also used a purely mathematical approach to derive subgroups and a prognostic model for individual patients. Interestingly, the two approaches gave similar predictive information, which opens the possibility of a more detailed mathematical analysis in the future. The results of this large dataset show that amongst non-surgical HCC patients, there are clear subsets with longer survival. CONCLUSION: The data supports the concept of heterogeneity of HCC. The three factors, bilirubin, AFP, and PVT predominate in prognosis.

Tumor and liver determinants of prognosis in unresectable hepatocellular carcinoma: a case cohort study.

BACKGROUND AND AIMS: A total of 967 patients with unresectable and untransplantable, biopsy-proven hepatocellular carcinoma (HCC) were prospectively evaluated at baseline and followed up till death. METHODS: Survival was the end-point for all analyses. RESULTS: We found in our overall analysis, that male gender, ascites, cirrhosis, portal vein thrombosis (PVT), elevated alpha-fetoprotein (AFP) or bilirubin or alkaline phosphatases were each statistically significant adverse prognostic factors. Patients with normal AFP survived longer than those with elevated AFP, in the presence of PVT, large or bilobar tumors or cirrhosis. We used a bivariate analysis to separate patient subgroups based on poor liver function and aggressive tumor characteristics. In subgroup analysis based on these subsets, there was clear discrimination in survival between subsets; in addition both cirrhosis and presence of PVT were significant, independent but modest risk factors. The results of this large dataset show that amongst nonsurgical HCC patients, there are clear subsets with longer survival than other subsets. CONCLUSIONS: This data also supports the concept of heterogeneity of HCC.

Patterns of p73 N-terminal isoform expression and p53 status have prognostic value in gynecological cancers.

The goal of this study was to determine whether patterns of expression profiles of p73 isoforms and of p53 mutational status are useful combinatorial biomarkers for predicting outcome in a gynecological cancer cohort. This is the first such study using matched tumor/normal tissue pairs from each patient. The median follow-up was over two years. The expression of all 5 N-terminal isoforms (TAp73, DeltaNp73, DeltaN'p73, Ex2p73 and Ex2/3p73) was measured by real-time RT-PCR and p53 status was analyzed by immunohistochemistry. TAp73, DeltaNp73 and DeltaN'p73 were significantly upregulated in tumors. Surprisingly, their range of overexpression was age-dependent, with the highest differences delta (tumor-normal) in the youngest age group. Correction of this age effect was important in further survival correlations. We used all 6 variables (five p73 isoform levels plus p53 status) as input into a principal component analysis with Varimax rotation (VrPCA) to filter out noise from non-disease related individual variability of p73 levels. Rationally selected and individually weighted principal components from each patient were then used to train a support vector machine (SVM) algorithm to predict clinical outcome. This SVM algorithm was able to predict correct outcome in 30 of the 35 patients. We use here a mathematical tool for pattern recognition that has been commonly used in e.g. microarray data mining and apply it for the first time in a prognostic model. We find that PCA/SVM is able to test a clinical hypothesis with robust statistics and show that p73 expression profiles and p53 status are useful prognostic biomarkers that differentiate patients with good vs. poor prognosis with gynecological cancers.