Unbiased data mining identifies cell cycle transcripts that predict non-indolent Gleason score 7 prostate cancer

Development of a multigenomic liquid biopsy (PROSTest) for prostate cancer in whole blood

INTRODUCTION

We describe the development of a molecular assay from publicly available tumor tissue mRNA databases using machine learning and present preliminary evidence of functionality as a diagnostic and monitoring tool for prostate cancer (PCa) in whole blood.

MATERIALS AND METHODS

We assessed 1055 PCas (public microarray data sets) to identify putative mRNA biomarkers. Specificity was confirmed against 32 different solid and hematological cancers from The Cancer Genome Atlas (n = 10,990). This defined a 27-gene panel which was validated by qPCR in 50 histologically confirmed PCa surgical specimens and matched blood. An ensemble classifier (Random Forest, Support Vector Machines, XGBoost) was trained in age-matched PCas (n = 294), and in 72 controls and 64 BPH. Classifier performance was validated in two independent sets (n = 263 PCas; n = 99 controls). We assessed the panel as a postoperative disease monitor in a radical prostatectomy cohort (RPC: n = 47).

RESULTS

A PCa-specific 27-gene panel was identified. Matched blood and tumor gene expression levels were concordant (r = 0.72, p < 0.0001). The ensemble classifier ("PROSTest") was scaled 0%-100% and the industry-standard operating point of ≥50% used to define a PCa. Using this, the PROSTest exhibited an 85% sensitivity and 95% specificity for PCa versus controls. In two independent sets, the metrics were 92%-95% sensitivity and 100% specificity. In the RPCs (n = 47), PROSTest scores decreased from 72% ± 7% to 33% ± 16% (p < 0.0001, Mann-Whitney test). PROSTest was 26% ± 8% in 37 with normal postoperative PSA levels (<0.1 ng/mL). In 10 with elevated postoperative PSA, PROSTest was 60% ± 4%.

CONCLUSION

A 27-gene whole blood signature for PCa is concordant with tissue mRNA levels. Measuring blood expression provides a minimally invasive genomic tool that may facilitate prostate cancer management.

The Prognostic Value of Liquid Biopsies for Benefit of Salvage Radiotherapy in Relapsed Oligometastatic Prostate Cancer

Simple Summary

Around 30% of patients with oligometastatic prostate cancer relapse will benefit from local PET/CT-guided ablative radiotherapy (RT) with improved progression-free and ADT (Androgene Deprivation Therapy)-free survivals. Therefore, there is an urgent need for predictive testing for therapeutic benefits prior to initiation. Various tests have already been established on tumor specimens for the prediction of prostate cancer’s behavior or therapy outcome. However, in imaging-proven relapse tumor tissue from the local recurrence or metastases is often not available. Hence, there is a need for a liquid biopsy-based testing. We aimed to assess the prognostic value of CTCs- associated mRNA and blood-derived RNA for the benefit of PSMA PET-guided salvage RT in oligometastatic prostate cancer relapses. Significant correlations were found between the relative transcript levels of several investigated genes and clinicopathological parameters. Furthermore, distinct “transcriptional signatures” were found in patients with temporary and long-term benefits from RT.

Abstract

To assess the prognostic value of “liquid biopsies” for the benefit of salvage RT in oligometastatic prostate cancer relapse, we enrolled 44 patients in the study between the years 2016 and 2020. All the patients were diagnosed as having an oligometastatic prostate cancer relapse on prostate-specific membrane antigen (PSMA)-targeted PET-CT and underwent irradiation at the Department of Radiotherapy at the Hannover Medical School. Tumor cells and total RNA, enriched from the liquid biopsies of patients, were processed for the subsequent quantification analysis of relative transcript levels in real-time PCR. In total, 54 gene transcripts known or suggested to be associated with prostate cancer or treatment outcome were prioritized for analysis. We found significant correlations between the relative transcript levels of several investigated genes and the Gleason score, PSA (prostate-specific antigen) value, or UICC stage (tumor node metastasis -TNM classification of malignant tumors from Union for International Cancer Control). Furthermore, a significant association of MTCO2, FOXM1, SREBF1, HOXB7, FDXR, and MTRNR transcript profiles was found with a temporary and/or long-term benefit from RT. Further studies on larger patients cohorts are necessary to prove our preliminary findings for establishing liquid biopsy tests as a predictive examination method prior to salvage RT.

Identification of novel prostate cancer genes in patients stratified by Gleason classification: role of antitumoral genes

Prostate cancer (PCa) is a tumor with a great heterogeneity, both at a molecular and clinical level. Despite its global good prognosis, cases can vary from indolent to lethal metastatic and scientific efforts are aimed to discern those with worse outcomes. Current prognostic markers, as Gleason score, fall short when it comes to distinguishing these cases. Identification of new early biomarkers to enable a better PCa distinction and classification remains a challenge. In order to identify new genes implicated in PCa progression we conducted several differential gene expression analyses over paired samples comparing primary PCa tissue against healthy prostatic tissue of PCa patients. The results obtained show that this approach is a serious alternative to overcome patient heterogeneity. We were able to identify 250 genes whose expression varies along with tissue differentiation—healthy to tumor tissue, 161 of these genes are described here for the first time to be related to PCa. The further manual curation of these genes allowed to annotate 39 genes with antitumoral activity, 22 of them described for the first time to be related to PCa proliferation and metastasis. These findings could be replicated in different cohorts for most genes. Results obtained considering paired differential expression, functional annotation and replication results point to: CGREF1, UNC5A, C16orf74, LGR6, IGSF1, QPRT and CA14 as possible new early markers in PCa. These genes may prevent the progression of the disease and their expression should be studied in patients with different outcomes.

An advanced network pharmacology study to explore the novel molecular mechanism of Compound Kushen Injection for treating hepatocellular carcinoma by bioinformatics and experimental verification

Background

Compound Kushen Injection (CKI) is a Chinese patent drug that exerts curative effects in the clinical treatment of hepatocellular carcinoma (HCC). This study aimed to explore the targets and potential pharmacological mechanisms of CKI in the treatment of HCC.

Methods

In this study, network pharmacology was used in combination with molecular biology experiments to predict and verify the molecular mechanism of CKI in the treatment of HCC. The constituents of CKI were identified by UHPLC-MS/MS and literature search. The targets corresponding to these compounds and the targets related to HCC were collected based on public databases. To screen out the potential hub targets of CKI in the treatment of HCC, a compound-HCC target network was constructed. The underlying pharmacological mechanism was explored through the subsequent enrichment analysis. Interactive Gene Expression Profiling Analysis and Kaplan-Meier plotter were used to examine the expression and prognostic value of hub genes. Furthermore, the effects of CKI on HCC were verified through molecular docking simulations and cell experiments in vitro.

Results

Network analysis revealed that BCHE, SRD5A2, EPHX2, ADH1C, ADH1A and CDK1 were the key targets of CKI in the treatment of HCC. Among them, only CDK1 was highly expressed in HCC tissues, while the other 5 targets were lowly expressed. Furthermore, the six hub genes were all closely related to the prognosis of HCC patients in survival analysis. Molecular docking revealed that there was an efficient binding potential between the constituents of CKI and BCHE. Experiments in vitro proved that CKI inhibited the proliferation of HepG2 cells and up-regulated SRD5A2 and ADH1A, while down-regulated CDK1 and EPHX2.

Conclusions

This study revealed and verified the targets of CKI on HCC based on network pharmacology and experiments and provided a scientific reference for further mechanism research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03530-3.

The CAPRA-S score versus subtypes of minimal residual disease to predict biochemical failure after radical prostatectomy

Objective

The objective of this study was to compare the CAPRA-S score (based on clinicopathological findings) and the subtypes of minimal residual disease (MRD) (based on the biological properties of cancer cells) to predict biochemical failure (BF) after prostatectomy radical.

Patients and methods

This was a prospective single-centre study of men who underwent radical prostatectomy. One month after surgery, the blood and bone marrow were taken for circulating prostate cell (CPC) and micrometastasis detection, identified using anti-PSA immunocytochemistry and defined as positive or negative. Patients were classified as Group A: CPC and micrometastasis negative, Group B: micrometastasis positive and CPC negative and Group C: CPC positive. CAPRA-S scores were classified as low, intermediate and high risk. Kaplan–Meier curves for biochemical failure-free survival (BFFS) and restricted mean survival time (RMST) to biochemical failure were determined and compared for up to 10 years.

Results

347 men participated with a median follow-up of 7 years, BFFS decreased proportionally with increasing CAPRA-S score and HR 1.13 and 1.65 for intermediate and high risk, respectively. After 10 years, the BFFS and RMST were 68%, 47% and 16% and 9, 7 and 6 years, respectively. The BFFS curves for MRD were not proportional; Group A and B BFFSs were similar up to 5 years, and then, there was an increasing failure in Group B patients After 10 years, the BFFS and RMST were 95%, 57% and 27% and 10, 9 and 6 years respectively. The CAPRA-S score failed to distinguish between Groups A and B, and one-third of high-risk Group C had low-risk CAPRA-S scores. MRD hazard ratios were Group B 1.76 and Group C 4.03.

Conclusions

The MRD prognostic classification was superior to the CAPRA-S score in predicting BFFS and differentiated between early and late BF. The results need to be confirmed in larger studies.

Association Between Contrast-Enhanced Ultrasound Indicators and Prostate Cancer Biochemical Recurrence After Treatment

Background

Some patients with prostate cancer (PCa) will experience biochemical recurrence (BCR) after treatment. Current researches have identified the influencing factors of BCR, but these factors are difficult to quantify and hence unable to accurately predict the BCR in PCa patients.

Objective

To explore the value of contrast-enhanced ultrasound (CEUS) indicators in predicting the BCR after treatment by evaluating the association between them.

Patients and Methods

In a retrospective cohort study, 157 PCa patients were recruited and received prostate specific antigen (PSA) measurement, CEUS, pathological classification, and immunohistochemistry after puncture biopsy. PCa patients with BCR were included in the recurrence group, while the remaining patients were included in the non-recurrence group after a 5-year follow-up. The clinical characteristics and CEUS indicators were compared between the two groups, and the multivariable COX regression was used for screening the influencing factors of BCR. Receiver operating characteristic (ROC) curves were used to analyze the value of potential factors in predicting BCR. The effect of the combined prediction model was explored to improve the accuracy of the prediction.

Results

Twelve patients are lost during the follow-up period and the final analysis included 145 patients. The 5-year BCR rate of PCa patients was 27%, with 43 patients in the recurrence group and 102 patients in the non-recurrence group. Multivariate analysis showed that lymph node metastasis (P<0.001), distant metastasis (P<0.001), Gleason score (P<0.001), pretreatment PSA (P<0.001), treatment method (P<0.001), peak intensity (PI) (P=0.001), and time to peak (TTP) (P=0.003) were independent influencing factors for BCR after treatment. ROC analysis showed that the AUCs of all indicators in predicting BCR were not high (all <0.9). The combination of lymph node metastasis, Gleason score, pretreatment PSA, and treatment method can improve the predictive accuracy (AUC = 0.85), but the AUC was still under 0.9. The combined prediction model including CEUS time-intensity curve (TIC) indicators (PI and TTP) could accurately predict the BCR after treatment (AUC=0.953). The sensitivity and specificity were 93.02% and 88.24%, respectively.

Conclusion

The prediction model including TIC indicators and common influencing factors can more accurately predict the BCR in PCa patients.

The CAPRA score versus sub-types of minimal residual disease to predict biochemical failure after external beam radiotherapy

Introduction

External beam radiotherapy is a treatment option for clinically localised prostate cancer; however, some 15% of patients will undergo treatment failure within 5 years. The objective was to compare the Cancer of the Prostate Risk Assessment (CAPRA) score (based on the clinical-pathological findings) and the sub-types of minimal residual disease (MRD) (based on the biological properties of the cancer cells) risk classifications to predict biochemical failure (BF) after external beam radiotherapy.

Methods and Patients

Clinical-pathological findings were obtained from the prostate biopsy to determine the CAPRA score and used to define low-, intermediate- and high-risk patients. Blood and bone marrow were obtained 3 months after radiotherapy; circulating prostate cells (CPCs) and micro-metastasis were detected using immunocytochemistry with anti-prostate specific antigen. CPCs and micro-metastasis were classified as positive if at least one cell was detected in the sample. Three subgroups were formed Group A (MRD negative), Group B (micro-metastasis positive, CPC negative) and Group C (CPC positive)Patients were followed up for 10 years or until biochemical failure. Biochemical failure free survival (BFFS) curves were constructed using Kaplan-Meier (observed), a flexible parameter model (predicted survival) and the restricted mean survival time (RMST) was calculated for each sub-group.

Results

309 men participated with a median follow-up of 8 years. The risk of biochemical failure increased proportionally with increasing CAPRA score, hazard ratio 1.18 for intermediate and 1.69 for high risk patients. After 10 years, the percentage BFFS and RMST to failure were 74%, 49%, 16% and 9, 7 and 6 years, respectively. The agreement between observed and predicted BFFS was acceptable (Harrell´s C 0.62). The BFFS curves for MRD were different and not proportional, survival curves for men MRD negative and only micro-metastasis were similar up to 5 years, and then there was increasing failure in the micro-metastasis only group. After 10 years, the percentage BFFS and RMST to failure were 95%, 59%, 28% and 10, 9 and 6 years, respectively. The CAPRA score failed to distinguish between Groups A and B, one third of high risk Group C had low risk CAPRA scores. The agreement between observed and predicted BFFS was very good (Harrell´s C 0.92). Minimal residual disease hazard ratios were Group B 1.84 and Group C 4.51.

Conclusions

The MRD prognostic classification is based on the biological characteristics of the tumour cell-microenvironment interaction, to give three groups, MRD negative, only bone marrow micro-metastasis and CPC positive prostate cancer. Differing from the CAPRA score classification the risk of treatment failure changes with time, differentiating between early and late treatment failures and incorporates the concept of dormancy. It proved to be superior to the CAPRA score in predicting biochemical failure and the results need to be confirmed in larger studies.

The expression of matrix-metalloproteinase-2 in bone marrow micro-metastasis is associated with the presence of circulating prostate cells and a worse prognosis in men treated with radical prostatectomy for prostate cancer

OBJECTIVE

The expression of matrix-metalloproteinase-2 (MMP-2) in the primary tumor is associated with a worse prognosis but little is known at this time regarding the expression in micro-metastasis, the association with circulating prostate cells (CPCs), and outcome.

MATERIAL AND METHODS

This was a prospective study of men undergoing radical prostatectomy. Bone marrow and blood samples were taken at one month after surgery. Micro-metastasis and CPCs were identified using immunocytochemistry with anti-prostate specific-antigen and MMP-2 expression determined with anti-MMP-2. Pathological stage, Gleason score, and time to biochemical failure were recorded; meanwhile, Kaplan-Meier biochemical failure-free survival and restricted mean biochemical failure-free survival times for 10 years were determined.

RESULTS

A total of 282 men participated, 54 (19%) of whom had micro-metastasis but not CPCs (group B) and 88 (31%) of whom had micro-metastasis and CPCs (group C). Men in group C had a higher frequency of MMP-2 expressing micro-metastasis at 63% versus 12% (p<0.001), and MMP-2 expression in bone marrow micro-metastasis was associated with a higher Gleason score (p<0.05) as well as a higher frequency of and shorter time to treatment failure. Also, a 10-year Kaplan-Meier biochemical failure-free survival rate of 0% versus 7.7% (MMP-2 positive versus negative) and a mean time to biochemical failure of 2.6 versus 4.0 years were recorded.

CONCLUSION

The expression of MMP-2 in bone marrow micro-metastasis is associated with a higher Gleason score, the presence of CPCs, and a higher frequency of and shorter time to failure and could be clinically useful for identifying men at high risk of treatment failure.

A nomogram based on a gene signature for predicting the prognosis of patients with head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignant tumors. The purpose of this study was to establish and validate a gene-expression-based prognostic signature in non-metastatic patients with HNSCC.

MATERIALS AND METHODS

All the patients were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We randomly divided the GSE65858 samples into 70% (training cohort, n = 190) and 30% (internal validation cohort, n = 72). A total of 36 samples collected from the TCGA HNSCC databases were selected as an independent external validation cohort. The oligo package in R was used to normalize the raw data before analysis. Data characteristics were extracted, and a gene signature was built via the least absolute shrinkage and selection operator regression model. The predictive model was developed by multivariable Cox regression analysis. T stage, N stage, human papilloma virus status, and the gene signature were incorporated in this predictive model, which was shown as a nomogram. Calibration and discrimination were performed to assess the performance of the nomogram. The clinical utility of this nomogram was assessed by the decision curve analysis.

RESULTS

Overall, 2001 significant messenger RNAs in HNSCC samples were identified compared with normal samples. The gene signature contained seven genes and significantly correlated with overall survival. The gene signature was also significant in subgroup analysis of the primary cohort. The calibration was plotted in the external cohort (C-index 0.90, 95% CI 0.85, 0.95) compared with the training (C-index 0.76, 95% CI 0.73, 0.79) and internal (C-index 0.71, 95% CI 0.66, 0.77) cohorts. In clinic, a decision curve analysis demonstrated that the model including the prognostic gene signature score status was better than that without it.

CONCLUSION

This study developed and validated a predictive model, which can promote the individualized prediction of overall survival in non-metastatic patients with HNSCC.