Olaparib Combined with Abiraterone versus Olaparib Monotherapy for Patients with Metastatic Castration-resistant Prostate Cancer Progressing after Abiraterone and Harboring DNA Damage Repair Deficiency: A Multicenter Real-world Study.

BACKGROUND AND OBJECTIVE: Olaparib + abiraterone has a combined antitumor effect in metastatic castration-resistant prostate cancer (mCRPC), but the efficacy of this combination in patients with DNA damage repair (DDR)-deficient mCRPC progressing after abiraterone is unknown. Our aim was to compare the efficacy of olaparib + abiraterone versus olaparib monotherapy for patients with DDR-deficient mCRPC progressing after abiraterone. METHODS: The study included 86 consecutive patients with DDR-deficient mCRPC progressing after abiraterone: 34 received olaparib + abiraterone, and 52 received olaparib monotherapy. DDR-deficient status was defined as the presence of a DDR gene with a pathogenic or likely pathogenic variant (DDR-PV), or with a variant of unknown significance (DDR-VUS). We assessed progression-free survival (PFS) and overall survival (OS) using the Kaplan-Meier method. Potential factors influencing PFS and OS were compared between the treatment arms using Cox proportional-hazards models. The prostate-specific antigen (PSA) response, the treatment effect across subgroups, and adverse events (AEs) were also evaluated. KEY FINDINGS AND LIMITATIONS: Median follow-up was 9 mo. In the overall cohort, median PFS and OS were significantly longer in the combination arm than in the monotherapy arm (PFS: 6.0 vs 3.0 mo; hazard ratio [HR] 0.41, 95% confidence interval [CI] 0.25-0.67; p < 0.01; OS: 25.0 vs 12.0 mo; HR 0.30, 95% CI 0.14-0.67; p < 0.01). PSA responses were significantly higher following combination therapy versus monotherapy. Combination therapy had significantly better efficacy in the DDR-PV and DDR-VUS subgroups, and was an independent predictor of better PFS and OS. AE rates were acceptable. The retrospective nature, small sample size, and short follow-up are limitations. CONCLUSIONS: Olaparib + abiraterone resulted in better PFS and OS than olaparib alone for patients with DDR-deficient mCRPC progressing after abiraterone. These results need to be confirmed by a large-scale prospective randomized controlled trial. PATIENT SUMMARY: Our study shows that the drug combination of olaparib plus abiraterone improved survival over abiraterone alone for patients who have mutations in genes affecting DNA repair and metastatic prostate cancer resistant to hormone therapy. The results provide evidence of a synergistic effect of the two drugs in these patients.

Concordance and Clinical Significance of Genomic Alterations in Progressive Tumor Tissue and Matched Circulating Tumor DNA in Aggressive-variant Prostate Cancer.

Sequencing of circulating tumor DNA (ctDNA) is a minimally invasive approach to reveal the genomic alterations of cancer; however, its comparison with sequencing of tumor tissue has not been well documented in real-world patients with aggressive-variant prostate cancer (AVPC). Concordance of genomic alterations was assessed between progressive tumor tissue and matched ctDNA by next-generation sequencing for 63 patients with AVPC. Associations of genomic alterations with progression-free survival (PFS) and overall survival (OS) were investigated using Kaplan-Meier and Cox regression analyses. A total of 161 somatic mutations (SMs) and 84 copy-number variants (CNVs) were detected in tumors, of which 97 were also found in ctDNA, giving concordance of 39.6% (97/245) across all SMs and CNVs, 49.7% for SMs only and 20.2% for CNVs only. Across all patients with AVPC, chemotherapy was associated with significantly longer median PFS (6 vs. 0.75 months, P = 0.001) and OS (11 vs. 8 months, P < 0.001) than next-generation hormonal therapy (NHT). Among types of chemotherapy, additional platinum-based chemotherapy was associated with significantly longer median PFS and OS than docetaxel only in patients with TP53, RB1, or PTEN alterations, and in those with ctDNA% ≥ 13.5%. The concordance analysis first provides evidence for combining the sequencing of ctDNA and tumor tissue in real-world patients with AVPC. Chemotherapy is associated with significantly better survival than NHT, and the benefit of additional platinum-based chemotherapy may depend on the presence of alterations in TP53, RB1, or PTEN and on a sufficiently high proportion of ctDNA in patients with AVPC. SIGNIFICANCE: AVPC is a highly malignant and heterogeneous disease. Sequencing of ctDNA is a minimally invasive approach to reveal genomic alterations. On the basis of the current real-world study, we found ctDNA does not fully recapitulate the landscape of genomic alterations from progressive tumor tissue in AVPC. We also revealed AVPC can benefit from chemotherapy, especially platinum-based regimens. TP53/RB1/PTEN alterations in ctDNA or tumor tissue could be biomarkers for platinum-based chemotherapy in this setting.

Sustained complete response to first-line immunochemotherapy for highly aggressive TP53/MDM2-mutated upper tract urothelial carcinoma with ERBB2 mutations, luminal immune-infiltrated contexture, and non-mesenchymal state: a case report and literature review.

Background: Upper tract urothelial carcinoma (UTUC) is a rare malignancy. The management of metastatic or unresectable UTUC is mainly based on evidence extrapolated from histologically homologous bladder cancer, including platinum-based chemotherapy and immune checkpoint inhibitor alone, whereas UTUC exhibits more invasiveness, worse prognosis, and comparatively inferior response to treatments. First-line immunochemotherapy regimens have been attempted in clinical trials for unselected naïve-treated cases, but their efficacies relative to standard chemo- or immuno-monotherapy still remain controversial. Here, we present a case of highly aggressive UTUC for whom comprehensive genetic and phenotypic signatures predicted sustained complete response to first-line immunochemotherapy. Case presentation: A 50-year-old man received retroperitoneoscopic nephroureterectomy and regional lymphadenectomy for high-risk locally advanced UTUC. Postoperatively, he developed rapid progression of residual unresectable metastatic lymph nodes. Pathologic analysis and next-generation sequencing classified the tumor as highly aggressive TP53/MDM2-mutated subtype with features more than expression of programmed death ligand-1, including ERBB2 mutations, luminal immune-infiltrated contexture, and non-mesenchymal state. Immunochemotherapy combining gemcitabine, carboplatin, and off-label programmed death-1 inhibitor sintilimab was initiated, and sintilimab monotherapy was maintained up to 1 year. Retroperitoneal lymphatic metastases gradually regressed to complete response. Blood-based analyses were performed longitudinally for serum tumor markers, inflammatory parameters, peripheral immune cells, and circulating tumor DNA (ctDNA) profiling. The ctDNA kinetics of tumor mutation burden and mean variant allele frequency accurately predicted postoperative progression and sustained response to the following immunochemotherapy, which were mirrored by dynamic changes in abundances of ctDNA mutations from UTUC-typical variant genes. The patient remained free of recurrence or metastasis as of this publishing, over 2 years after the initial surgical treatment. Conclusion: Immunochemotherapy may be a promising first-line option for advanced or metastatic UTUC selected with specific genomic or phenotypic signatures, and blood-based analyses incorporating ctDNA profiling provide precise longitudinal monitoring.

Identification of a combined lncRNA prognostic signature and knockdown of lncRNA MANCR to inhibit progression of clear cell renal cell carcinoma by bioinformatics analysis.

Background: Long non-coding RNAs (lncRNAs) have become potential therapeutic targets or promising prognostic biomarkers in cancers. However, individual gene does not show sufficient prognostic value for clear cell renal cell carcinoma (ccRCC). Therefore, this study aims to develop a combined prognostic lncRNA signature to the prognosis of ccRCC. Methods: The transcriptome profiling data for confirmed ccRCC cases were obtained from The Cancer Genome Atlas (TCGA; https://portal.gdc.cancer.gov/). The prognostic significance, survival time and diagnostic effectiveness of the lncRNAs in ccRCC was evaluated using Kaplan-Meier method, the log-rank test and receiver operating characteristic (ROC) curves, respectively. The area under the ROC curve (AUC) of the 4 lncRNAs was also performed. The expression of mitotically-associated lncRNA (MANCR) was measured in ccRCC cells or tissues by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Both Colony formation assays and Cell Counting Kit-8 (CCK-8) assay was conducted to detect the proliferation of both 786-O and SN12C cells. For apoptosis detection, flow cytometry in both 786-O and SN12C cells was performed. For migration of 786-O and SN12C cells detection, wound healing and transwell assays were performed. Results: A total of 1,567 differentially expressed lncRNAs in ccRCC were discerned with 1,340 upregulation and 227 downregulation. Furthermore, a 4-lncRNA signature (FIRRE, MANCR, AC103706.1, and AC018648.1) model was obtained that showed good performance in the prognosis of ccRCC. Gene Ontology (GO) analysis showed that these protein-coding genes (PCGs) were mainly enriched in ATPase activity, catalytic activity, and acting on RNA protein serine/threonine kinase activity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that PCGs were mainly involved in endocytosis, oocyte meiosis and spliceosome. In addition, we revealed that MANCR was highly expressed in ccRCC cells and tissues and downregulation of MANCR inhibited cell proliferation and migration. In contrast, apoptosis of 786-O and SN12C cells was promoted with MANCR suppression. Conclusions: A 4-lncRNA prognostic model that presented good performance for prognosis of ccRCC patients was established. Knockdown of MANCR inhibited cell proliferation and migration, and promoted apoptosis of 786-O and SN12C cells, suggesting that a 4-lncRNA signature model might be an essential for ccRCC prognosis.

The diagnostic and prognostic value of miR-92a in gastric cancer: A systematic review and meta-analysis.

BACKGROUND: miR-92a is believed to have a significant role in the diagnosis and prognosis of different types of tumors, but the potential impact of its expression is still controversial due to the sample size. We conducted the meta-analysis to figure out whether miR-92a could be used as a detecting tool for assessing the prognosis of gastric cancer. METHOD: A literature search was conducted by retrieving the Web of Science, PubMed, EMBASE, Chinese National Knowledge Infrastructure, VIP (Technology of Chongqing databases), and Wanfang databases (last updated by February 2020). The sensitivity (SEN), specificity (SPE), positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and area under the ROC curve (AUC) were pooled to explore the diagnostic performance of miR-92a. The pooled hazard ratios (HRs) and 95% CIs of miR-92a for overall survival (OS) were calculated to explore the prognostic performance of miR-92a. RESULTS: Nine articles containing 11 studies were included. The pooled SEN and SPE were 0.76 and 0.79. Besides, the pooled PLR and NLR were 3.7 and 0.30, and the pooled DOR was 12. AUC was 0.84, indicating a significant value of miR-92a in gastric cancer detection. For the prognostic analysis of miR-92a in gastric cancer, the univariate and multivariate data's poor OS were 1.37 and 2.01. CONCLUSION: The present meta-analysis demonstrated that miR-92a could be a potential biomarker for the detection of gastric cancer. miR-92a could also be used as a valuable indicator for predicting the prognosis of gastric cancer patients.

Identification of crucial genes and pathways associated with prostate cancer in multiple databases.

OBJECTIVE: Prostate cancer (PCa) is a malignant neoplasm of the urinary system. This study aimed to use bioinformatics to screen for core genes and biological pathways related to PCa. METHODS: The GSE5957 gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were constructed by R language. Furthermore, protein-protein interaction (PPI) networks were generated to predict core genes. The expression levels of core genes were examined in the Tumor Immune Estimation Resource (TIMER) and Oncomine databases. The cBioPortal tool was used to study the co-expression and prognostic factors of the core genes. Finally, the core genes of signaling pathways were determined using gene set enrichment analysis (GSEA). RESULTS: Overall, 874 DEGs were identified. Hierarchical clustering analysis revealed that these 24 core genes have significant association with carcinogenesis and development. LONRF1, CDK1, RPS18, GNB2L1 (RACK1), RPL30, and SEC61A1 directly related to the recurrence and prognosis of PCa. CONCLUSIONS: This study identified the core genes and pathways in PCa and provides candidate targets for diagnosis, prognosis, and treatment.

Based on biomedical index data: Risk prediction model for prostate cancer.

ABSTRACT: To explore the influencing factors of prostate cancer occurrence, set up risk prediction model, require reference for the preliminary diagnosis of clinical doctors, this model searched database through the data of prostate cancer patients and prostate hyperplasia patients National Clinical Medical Science Data Center.With the help of Stata SE 12.0 and SPSS 25.0 software, the biases between groups were balanced by propensity score matching. Based on the matched data, the relevant factors were further screened by stepwise logistic regression analysis, the key variable and artificial neural network model are established. The prediction accuracy of the model is evaluated by combining the probability of test set with the area under receiver operating characteristic curve (ROC).After 1:2 PSM, 339 pairs were matched successfully. There are 159 cases in testing groups and 407 cases in training groups. And the regression model was P = 1 / (1 + e (0.122 ∗ age + 0.083 ∗ Apo lipoprotein C3 + 0.371 ∗ total prostate specific antigen (tPSA) -0.227 ∗ Apo lipoprotein C2-6.093 ∗ free calcium (iCa) + 0.428 ∗ Apo lipoprotein E-1.246 ∗ triglyceride-1.919 ∗ HDL cholesterol + 0.083 ∗ creatine kinase isoenzyme [CKMB])). The logistic regression model performed very well (ROC, 0.963; 95% confidence interval, 0.951 to 0.978) and artificial neural network model (ROC, 0.983; 95% confidence interval, 0.964 to 0.997). High degree of Apo lipoprotein E (Apo E) (Odds Ratio, [OR], 1.535) in blood test is a risk factor and high triglyceride (TG) (OR, 0.288) is a protective factor.It takes the biochemical examination of the case as variables to establish a risk prediction model, which can initially reflect the risk of prostate cancer and bring some references for diagnosis and treatment.