Prostark: prostate cancer recurrence risk calculator

Abstract

The present invention refers to a mathematical calculation with the technical purpose of predicting the risk of recurrence / progression of prostate cancer through automated computer-aided processing. The said mathematical calculation provides the specific formula that better predicts patient prognosis, specifically the risk of biochemical recurrence (BCR). The said formula, herein termed ProstARK, integrates measurement of the tissue expression of a biomarker, along with clinical variables such as age, tumor stage, and Prostate Specific Antigen (PSA) serum levels. The herein disclosed mathematical processing may be handled on a local or remote computer or a device developing computing the said formula from inputted biomarker measurement and clinical variables. ProstARK may be advantageously integrated into the clinics for accurate risk assessment and improvement of patient management. A specifically defined cut-off may be employed to define high and low-risk patients. High-risk patients might benefit from active treatment instead of active surveillance. Moreover, the low-risk patients that do not meet this criterion have a favorable prognosis and could avoid unnecessary interventions.

Description

[0001] DESCRIPTION

[0002] PROSTARK: PROSTATE CANCER RECURRENCE RISK CALCULATOR

[0003] Technical field of the invention

[0004] The present invention relates to the technical field of mathematical calculation with a technical purpose p e r f o rme d through a computer-aided process and integrating measurements of biomarkers and clinical variables .

[0005] Thiophene containing compounds are well known to exhibit various biological ef fects . Heterocycles containing the thienopyrimidine moiety Thiophene containing compounds are well known to exhibit various biological ef fects . Heterocycles containing the thienopyrimidine moiety

[0006] State of the art

[0007] Prostate cancer ( PCa ) remains a highly prevalent disease in men worldwide ( 1 , 21 ) . Characteristically, this disease develops gradually and is frequently diagnosed in older individuals ( 1 , 21 ) . The high incidence of this disease is mostly attributed to the widespread PSA screening, which results in nearly 90% of PCa diagnosed as organ-confined disease ( 26 ) . When initially diagnosed, defining the optimal primary treatment for PCa is articulated with the risk o f biochemical recurrence (BCR) . Thi s risk assessment considers factors like PSA serum levels , clinical stage , and tumor grade , with the International Society of Urological Pathology ( ISUP) grade system playing a central role ( 17 , 50 , 51 ) . For high-risk patients ( PSA>20ng / mL and ISUP grade greater than 4 or cT2b ) , therapeutic procedures commonly involved neoadj uvant or concurrent androgen deprivation therapy (ADT ) plus radiotherapy ( 50 , 54 ) . Nonetheless , the approach for low- and intermediate-risk PCa patients remains challenging . Currently, it is di f ficult to predict which patients may benefit most from an active intervention-based approach or, on the other hand, might be better placed under active surveillance . Indeed, a subset of patients undergoing active surveillance eventually progress , with 11 to 32% of men ultimately receiving active treatment (50, 95) . However, it remains difficult to accurately predict which patients will have poor outcomes and require treatment. The lack of reliable biomarkers of PCa aggressiveness with prognostic value is a major drawback. Nevertheless, efforts to address this issue have been accomplished with the emergence of new strategies based on genomic tests, such as the Decipher® score, Prolaris® cell cycle progression test, and Oncotype DX® Prostate Score. However, the results are not always clinically informative (12, 50, 56-60) . These tests, which rely on whole transcriptomic data, offer valuable prognostic insights, especially by predicting the risk of metastasis, the probability of tumor regrowth, and the risk of death (12, 50, 56-60) . Despite the advantages of these newly "cancer prognostic tests", they are very expensive, with a price ranging from 3.900 to 5.150 dollars per patient, being difficult to implement in clinical practice. Consequently, there is an urgent need to explore alternative strategies that can leverage more cost- effective and convenient tools, such as immunohistochemistry (IHC) or PCR, to make this risk assessment simpler in clinical practice (56) . For instance, developing a more precise and reliable method may be pivotal to defining the most appropriate therapeutic choice, particularly when dealing with a subset of patients with low- and intermediate-risk tumors, since they can be candidates for active surveillance .

[0008] Summary of the Invention

[0009] In the present invention, a risk stratification calculator is disclosed. This tool is based on relevant clinicopathologic characteristics and biomarkers, employing techniques that can be easily integrated into routine clinical practice, namely Ki67 immunoexpression .

[0010] Remarkably, the present invention underscores the significance of Ki67 immunoexpression as a valuable prognostic indicator, making it a strong candidate for assessing the risk of PCa progression and / or recurrence, offering a straightforward and useful approach for clinical implementation, particularly in the context of low- and intermediate-risk PCa.

[0011] As such, the present invention refers to a computer-aided mathematical calculation for the prediction of the risk of biochemical recurrence of PCa, characterized by the equation: BCR Risk= -4.5509

[0012] 0.1447*AGEcat+l .6921* Ki 67 + 0.5982*Tstage+0.9164* PSA, wherein:

[0013] BCR refers to risk of biochemical recurrence, AGEcat refers to patient' s age at diagnosis

[0014] Ki67 refers to the score of Ki67 immunoexpression

[0015] Tstage refers to Tumour Stage

[0016] PSA refers to the serum levels of Prostate Specific Antigen, according to claim 1.

[0017] Another embodiment of the present invention refers to a method to stratify patients according to the risk of biochemical recurrence of PCa, characterized by the steps of: a) using a computing device to calculate the risk of progression through the formula: BCR Risk= -4.5509

[0018] 0.1447*AGEcat+l .6921* Ki 67 + 0.5982*Tstage+0.9164* PSA, wherein:

[0019] BCR refers to the risk of biochemical recurrence,

[0020] AGEcat refers to patient's age at diagnosis (0: <55, 1: 55-65, 2: >65 years ) , and

[0021] Ki67 refers to the score of Ki67 immunoexpression (0: <5%, 1: 5- 10%, 2: >10% of positive staining)

[0022] Tstage refers to Tumour clinical Stage

[0023] PSA refers to the Prostate Specific Antigen serum levels (1: <10ng / mL, 2: >10ng / mL) . b) classifying patients into low and high-risk based on a cut-off of 0.31, wherein: low-risk patients have a risk of progression lower than 0.31, high-risk patients have a risk of progression equal to or higher than 0.31. Detailed description of the Invention

[0024] Prostate cancer (PCa) specimens were obtained from formalin-fixed paraffin-embedded (FFPE) tissue samples collected from patients with localized prostate adenocarcinoma submitted to radical prostatectomy without any previous treatment. Moreover, Grade Group 1 and 2 patients (GG1 / 2) were segregated as Discovery Cohort GG1 / 2. The clinical data of the patients is summarized in Table 1. Additionally, a validation series of PCa biopsies (Table 4) was used to validate ProstARK performance.

[0025] Interestingly, PCa patients diagnosed with stage 3 disease displayed a significantly higher proportion of cases with high Ki67 immunoexpression (>10%) (p-value<0.01 , Figure 1A) . Significant differences among Gleason Grade (GG) groups were found for Ki67 immunoexpression (Figure IB) . Specifically, high-grade tumors (GG 3, 4, and 5) displayed a higher Ki67 immunoscore than low-grade tumors (GG 1 and 2) .

[0026] Remarkably, Ki67 positive staining independently predicts PCa patients' prognosis. Patients displaying moderate (5-10% of positive staining) and strong (>10% of positive staining) Ki67 immunoexpression face significantly reduced biochemical recurrence (BCR) -free survival in the Discovery Cohort and Discovery cohort GG1 / 2 (p-value=0.0002 and p-value=0.0121, respectively) (Figure 2 A and B) .

[0027] Table 1- Detailed clinicopathological data of PCa patients

[0028]

[0029] Abbreviations: N / A- Non applicable

[0030] Based on the Ki67 expression and clinical variables, models were developed and tested to find the one which better predicts patients' prognosis. The purpose of both calculators was to provide accurate risk assessment at diagnosis, particularly focusing on low-grade patients who are candidates for active surveillance. Thus, the ProstARK calculator included clinicopathologic variables: age at diagnosis, clinical stage, and PSA serum levels. This model was applied for the discovery cohort GG1 / 2.

[0031] Given that Ki67 high immunoexpression is significantly associated with the risk of BCR (p-value=0.0057 , 95% CI: 1.6377 - 18.0077) , this marker is selectively included in models aiming at predicting the risk of BCR.

[0032] As a result, a risk calculator model for BCR-free survival, herein termed ProstARK can be generated and represented by the equation: BCR Risk= -4.5509-

[0033] 0.1447*AGEcat+l .6921* Ki 67 + 0.5982*Tstage+0.9164* PSA, wherein:

[0034] BCR refers to the risk of biochemical recurrence,

[0035] AGEcat refers to the patient's age at diagnosis (0: <55, 1: 55- 65, 2: >65 years) , clinical stage, and PSA serum levels. Ki67 refers to the Ki67 immunoscore (0: <5%, 1: 5-10%, 2: >10% of positive staining)

[0036] Tstage refers to Tumour Clinical Stage

[0037] PSA refers to Prostate Specific Antigen serum levels (1: <10ng / mL, 2: >10ng / mL) .

[0038] For this model (Figure 3 A and B) , the area under the curve (AUG) was greater than 0.75(95% CI: 0.615-0.888) . The logistic regression model representative of the Risk of BCR calculator is summarized in Table 2.

[0039] Table 2- Summary of the logistic models' representative ProstARK calculator, in the Discovery Cohort GG1 / 2

[0040] Abbreviations: S.E.- Standard Error; OR - Odds Ratio; CI- Confidence Interval.

[0041] ProstARK calculator significantly discriminated low- vs. high-risk BCR patients for GG1 / 2 patients (Figure 4A) . Notably, ProstARK performance was encouraging: 79.17% specificity, 66.67% sensitivity, 55% positive predictive value (PPV) , 86% negative predictive value (NPV) , and 75.76% accuracy (Table 3) .

[0042] Then, ProstARK performance was validated in an independent series of diagnostic prostate biopsies (Table 4) , simulating a risk assessment realistic scenario. When considering the GG1 / 2 tumors, the area under the curve obtained was 0.723 (95% CI: 0.571-0.875) (Figure 4B and C) , meaning there is a 72% chance of our model correctly predicting the patients' outcome. Table 3- Indicators of the calculators' performance

[0043] Abbreviations: SE- Sensitivity; CI- Confidence Interval; SP- Specificity; PPV- Positive

[0044] Predictive Value; NPV- Negative Predictive Value; AC- Accuracy; AUC- Area under the curve

[0045] Table 4- Detailed clinicopathological data of a series of prostate cancer biopsies.

[0046] Abbreviations: N / A- Non applicable

[0047] ProstARK was formulated to be integrated into the clinics for accurate risk assessment and improved patient management. Specifically, a cut-off of -0.82 for the Linear predictor, translated into a recurrence / progression rate of 0.31, entailing that patients diagnosed with low GG PCa but displaying a risk of progression exceeding 0.31 are classified as high-risk patients. These high-risk patients might benefit from active treatment instead of active surveillance. Moreover, the other low GG PCa patients who do not meet this criterion will probably benefit from an active surveillance approach.

[0048] Hence, this calculator enables a more precise risk stratification among low-grade PCa patients, optimizing clinical decisions on the most appropriate therapeutic strategy. Furthermore, assessing prognostic variables may further refine follow-up strategies, allowing for timely adjustments in treatment plans and providing a more attentive monitoring of patients at higher risk for recurrence / progression . The combination of each patient's clinicopathologic features and Ki67 immunoexpression levels provides a risk calculator easy to implement for PCa prognostication .

[0049] Brief description of the Figures

[0050] Figure 1- Association Ki67 immunoexpression with clinicopathological features.

[0051] Ki67 immunoexpression was compared between stage IT and stage ITT tumors (A) and between different Gleason grade (GG) groups, GG1- GG5 (B) . Median ranks between two groups were compared using the Mann-Whitney test and the comparisons between grade groups were performed using the Kruskal-Wallis test. *, **, *** and **** represent a p-value lower than 0.05, 0.01, 0.001 and 0.0001, respectively .

[0052] One hundred and three PCa specimens (Discovery Cohort) were obtained from the archives of IPO Porto Biobank. These formalin- fixed paraffin-embedded (FFPE) tissue samples were collected from patients with localized prostate adenocarcinoma submitted to radical prostatectomy at IPO Porto between 2004 and 2008, without any previous treatment. Moreover, the Discovery Cohort was stratified to form the Discovery GG1 / 2, which includes exclusively patients with Grade Groups 1 and 2, according to the ISUP classification system. The clinical data of the patients is summarized in Table 3. Additionally, a validation series of PCa biopsies (Supplementary Table 1) , previously reported by other colleagues, was used to validate the risk predictor calculators discovered in cohort 1 and cohort 1.1 (83) . This study was approved by the Institutional Review Board of the Portuguese Oncology Institute of Porto (CES86 / 2022) .

[0053] For TISSUE MICROARRAY (TMA) CONSTRUCTION, firstly, using a rubber cast of 60 cores (T-SueTM Microarray Mold 60 cores W / plunger 2mm Red, Simport Scientific, Canada) , the TMA recipient blocks were made in a paraffin inclusion device (Modular Tissue Embedding Center EC 500) . Here, the liquid paraffin (at 61°C) was placed in the mold, and then it rested for about 30 minutes in the cold part of the device to solidify.

[0054] After the TMA recipient blocks were done, a puncher (T-SueTM punch needle plunger Simport Scientific, Canada) was used to remove 2mm diameter of tumor tissue (core) from donor blocks that were transferred to the recipient block. For each case, 3 cores were needed to ensure tumors' representativeness. A liver tissue core was used as a technical TMA guide. Furthermore, breast, colon, stomach, and tumor-adjacent prostate samples were used as controls .

[0055] Finally, after TMA constructions, 3pm of thick sections were cut using a Rotary Microtome to further immunohistochemistry (IHC) evaluation .

[0056] Immunostaining was performed using the NovoLink TM Max Polymer Detection System (Leica Biosystems, Germany) . The antibodies against CK8 / 18, NKX3.1, CK5 / 6, CK14, CD49f (section 1) , and Ki-67 (section 2) were used at properly optimized conditions (Supplementary Table 2) .

[0057] Briefly, after 15 minutes in the oven at 60°C, the slides were deparaffinized in xylol and hydrated in a decreasing series of alcohols. Then, the slides were washed in current water and distilled water for 3 minutes each. The antigen retrieval was realized using the retrieval buffer indicated for each antibody (Supplementary Table 2) . Then, the endogenous peroxidases were neutralized using 3% hydrogen peroxide for 10 minutes in a humidified chamber at room temperature. The slides were washed again with water, followed by two washes in TBST for 3 minutes. Subsequently, the horse serum was incubated at a dilution of 1:50 for 20 minutes, at room temperature. After this, the primary antibody was incubated with the appropriate time and dilution (Supplementary Table 2) .

[0058] Afterward, the slides were incubated with post-primary and polymer solutions for 30 minutes each at room temperature. Then, 3,3’- Diaminobenzidine (DAB) was incubated for 10 minutes at a dilution of 1:10 at room temperature. Hematoxylin was used as a counterstained solution.

[0059] Finally, the slides were dehydrated with an increased series of alcohols followed by diaphanization with xylol. The assembly of the slides was made using an automatic slide assembler (Leica CV5030, Germany) .

[0060] The slides were analyzed by an experienced pathologist according to a semiquantitative method. The IHC analysis considers the intensity, the localization, and the percentage of positive staining cells. Specifically, for Ki-67, cases were categorized according to the following score: 0: <5% of positive cells, 1: 5- 10% of positive cells, and 2: >10% of positive cells.

[0061] Figure 2. Figure 2- Kaplan-Meier curves for the biochemicalrecurrence free survival based on the expression of Ki67, in discovery cohort (A) and when stratified for GG1 / 2 (B) . The Log- Rank test was used to evaluate the differences in overall survival and BCR-free survival, where * and *** represent p- values lower than 0.05 and 0.001, respectively.

[0062] Figure 3. Figure 3- Graphical computation of a mathematical function integrating conventionally defined clinicopathological variables with Ki67.

[0063] Nomogram representative risk of biochemical-recurrence - ProstARK

[0064] (A) calculators, for the Discovery Cohort GG1 / 2, with the relevant clinicopathological variables for risk stratification: age at diagnosis (0: <55, 1: 55-65, 2: >65 years) , clinical stage and PSA serum levels (1: <10ng / mL, 2: >10ng / mL) . B- Roc curves to evaluate the performance of the nomogram model. Ki67 immunoexpression categorization- 0: <5%, 1: 5-10%, 2: >10% of positive staining.

[0065] For risk calculator computation, nomograms were constructed based on multivariable logistic regression analysis, using Rstudio from R software (version 4.3.1) . Receiver operator characteristic (ROC) curves were used to evaluate the performance of our models, based on the calculation of the area under the curve (AUG) . The rms, caTools, epicalc, and pROC packages were installed for these analyses. Youden' s J index (value combining highest sensitivity and specificity) was used for the categorization of results and subsequent assessment of the performance of our model in predicting BCR risk, dividing the cohort into two groups (high-risk and low- risk) according to the cut-off established for the Linear predictor value at the nomogram. For each analysis, the p-values lower than 0.05 were considered statistically significant. Specifically, *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001, ns: non-signif leant .

[0066] Figure 4. Figure 4- Risk Calculators evaluation in the Discovery and Validation Cohorts GG1 / 2. A- Kaplan-Meier curves for the biochemical-recurrence free survival based on the ProstARK calculator, in Discovery Cohort GG1 / 2. A -0.82 cut-off for the linear predictor translates into recurrence / progression risk of 0.31. B- Kaplan-Meier curve for the biochemical-recurrence free survival based on the ProstARK calculator, in Validation Cohort GG1 / 2 patients. A -0.82 cut-off for the linear predictor translates into recurrence / progression risk of 0.31. C- ROC curve to evaluate the performance of the ProstARK, in Validation Cohort GG1 / 2 patients .

[0067] References

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Claims

CLAIMS1. Computer-aided mathematical calculation for prediction of the risk of biochemical recurrence of prostate cancer (PCa) , characterized by the equation: BCR Risk= -4.5509 -0.1447*AGEcat+l .6921* Ki 67 + 0.5982*Tstage+0.9164* PSA, wherein:BCR refers to risk of biochemical recurrence,AGEcat refers to patient's age at diagnosisKi67 refers to the score of Ki67 immunoexpressionTstage refers to Tumour Clinical StagePSA refers to the serum levels of Prostate Specific Antigen .

2. Method to stratify patients according to risk of biochemical recurrence of PCa, characterized by the steps of: a) using a computing device to calculate the risk of progression through the formula: BCR Risk= -4.5509 - 0.1447 *AGEcat+ 1.6921*Ki67+0.5982*Tstage+0.9164* PSA, wherein :BCR refers to risk of biochemical recurrence,AGEcat refers to patient's age (0: <55, 1: 55-65, 2: >65 years) , clinical stage and PSA serum levels (1: <10ng / mL, 2 : >10ng / mL) .Ki67 refers to the score of Ki67 immunoexpression (0: <5%, 1: 5-10%, 2: >10% of positive staining)Tstage refers to Tumour Clinical StagePSA refers to the serum levels of Prostate Specific Antigen . b) classifying patients into low and high risk based on a cut-off of 0.31, wherein: low risk patients have a risk of progression lower than 0.31, high risk patients have a risk of progression equal or higher than 0.31.

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