The survival outcomes of localized low-risk prostate cancer, a population-based study using NCDB.

BACKGROUND: The optimal treatment approach for low-risk prostate cancer (LRPC) remains controversial. While active surveillance is an increasingly popular option, definitive local treatments, including radical prostatectomy (RP), external beam radiotherapy (EBRT), and prostate seed implantation (PSI), are also commonly used. This study aimed to evaluate the survival outcomes of patients with LRPC using a large patient population from the National Cancer Database (NCDB). METHODS: We analyzed data from 195,452 patients diagnosed with LRPC between 2004 and 2015 using the NCDB. Patients were classified based on their treatment modalities, including RP, EBRT, PSI, or no local treatment (NLT). Only patients with Charlson-Deyo comorbidity scores of 0 or 1 were included to ensure comparability. Propensity score analysis was used to balance the treatment groups, and the accelerated failure time model was used to analyze the survival rates of the treatment groups. RESULTS: After a median follow-up of 70.8 months, 24,545 deaths occurred, resulting in an all-cause mortality rate of 13%. RP demonstrated a survival benefit compared with NLT, particularly in patients younger than 74 years of age. In contrast, radiation treatments (EBRT and PSI) did not improve survival in the younger age groups, except for patients older than 70 years for EBRT and older than 65 years for PSI. Notably, EBRT in patients younger than 65 years was associated with inferior outcomes. CONCLUSION: This study highlights the differences in survival outcomes among LRPC treatment modalities. RP was associated with improved survival compared to NLT, especially in younger patients. In contrast, EBRT and PSI showed survival benefits primarily in the older age groups. NLT is a reasonable choice, particularly in younger patients when RP is not chosen. These findings emphasize the importance of individualized treatment decisions for LRPC management.

The eEF2 kinase coordinates the DNA damage response to cisplatin by supporting p53 activation.

Eukaryotic elongation factor 2 (eEF2) kinase (eEF2K) is a stress-responsive hub that inhibits the translation elongation factor eEF2, and consequently mRNA translation elongation, in response to hypoxia and nutrient deprivation. EEF2K is also involved in the response to DNA damage but its role in response to DNA crosslinks, as induced by cisplatin, is not known. Here we found that eEF2K is critical to mediate the cellular response to cisplatin. We uncovered that eEF2K deficient cells are more resistant to cisplatin treatment. Mechanistically, eEF2K deficiency blunts the activation of the DNA damage response associated ATM and ATR pathways, in turn preventing p53 activation and therefore compromising induction of cisplatin-induced apoptosis. We also report that loss of eEF2K delays the resolution of DNA damage triggered by cisplatin, suggesting that eEF2K contributes to DNA damage repair in response to cisplatin. In support of this, our data shows that eEF2K promotes the expression of the DNA repair protein ERCC1, critical for the repair of cisplatin-caused DNA damage. Finally, using Caenorhabditis elegans as an in vivo model, we find that deletion of efk-1, the worm eEF2K ortholog, mitigates the induction of germ cell death in response to cisplatin. Together, our data highlight that eEF2K represents an evolutionary conserved mediator of the DNA damage response to cisplatin which promotes p53 activation to induce cell death, or alternatively facilitates DNA repair, depending on the extent of DNA damage.

Urachal carcinoma: A novel staging system utilizing the National Cancer Database.

BACKGROUND: Urachal carcinoma (UrC) is a rare, aggressive cancer with a poor prognosis that is frequently diagnosed in advanced stages. Due to its rarity, the current staging systems, namely Sheldon, Mayo, and Ontario were established based on relatively small patient cohorts, necessitating further validation. We used a large patient population from the National Cancer Database to model a novel staging system based on the Tumor (T), Node(N), and Metastasis (M) (TNM) staging system and compared it to established staging systems. METHODS: We identified patients diagnosed with UrC between the years of 2004-2016. To determine median overall survival (OS), a Kaplan-Meier (KM) curve was generated using the Sheldon, Mayo, Ontario, and TNM staging system. A cox proportional-hazards regression model was developed to highlight predictors of overall survival. RESULTS: A total of 626 patients were included in the analysis. The OS for the entire cohort was 58.2 months (50.1-67.8) with survival rates at 12, 24, and 60 months of 83%, 70%, and 49%, respectively (p < 0.0001). As compared to the Sheldon, Mayo, and Ontario staging system, our TNM staging system had a more balanced sample and survival distribution per stage and no overlap among stages on KM survival curves. The Mayo, Ontario, and TNM staging systems were more accurate in terms of stage-survival correlation than the Sheldon staging system (p < 0.05 for all stages). CONCLUSIONS: The proposed novel TNM staging system for UrC has a more balanced sample distribution and a more accurate stage-survival correlation than the traditional Mayo, Sheldon, and Ontario staging systems. It is clinically applicable and enables better risk stratification, prognosis, and therapeutic decision-making.

Multi-omics data integration analysis identifies the spliceosome as a key regulator of DNA double-strand break repair.

DNA repair by homologous recombination (HR) is critical for the maintenance of genome stability. Germline and somatic mutations in HR genes have been associated with an increased risk of developing breast (BC) and ovarian cancers (OvC). However, the extent of factors and pathways that are functionally linked to HR with clinical relevance for BC and OvC remains unclear. To gain a broader understanding of this pathway, we used multi-omics datasets coupled with machine learning to identify genes that are associated with HR and to predict their sub-function. Specifically, we integrated our phylogenetic-based co-evolution approach (CladePP) with 23 distinct genetic and proteomic screens that monitored, directly or indirectly, DNA repair by HR. This omics data integration analysis yielded a new database (HRbase) that contains a list of 464 predictions, including 76 gold standard HR genes. Interestingly, the spliceosome machinery emerged as one major pathway with significant cross-platform interactions with the HR pathway. We functionally validated 6 spliceosome factors, including the RNA helicase SNRNP200 and its co-factor SNW1. Importantly, their RNA expression correlated with BC/OvC patient outcome. Altogether, we identified novel clinically relevant DNA repair factors and delineated their specific sub-function by machine learning. Our results, supported by evolutionary and multi-omics analyses, suggest that the spliceosome machinery plays an important role during the repair of DNA double-strand breaks (DSBs).

Visible near infrared reflectance molecular chemical imaging of human ex vivo carcinomas and murine in vivo carcinomas.

SIGNIFICANCE: A key risk faced by oncological surgeons continues to be complete removal of tumor. Currently, there is no intraoperative imaging device to detect kidney tumors during excision. AIM: We are evaluating molecular chemical imaging (MCI) as a technology for real-time tumor detection and margin assessment during tumor removal surgeries. APPROACH: In exploratory studies, we evaluate visible near infrared (Vis-NIR) MCI for differentiating tumor from adjacent tissue in ex vivo human kidney specimens, and in anaesthetized mice with breast or lung tumor xenografts. Differentiation of tumor from nontumor tissues is made possible with diffuse reflectance spectroscopic signatures and hyperspectral imaging technology. Tumor detection is achieved by score image generation to localize the tumor, followed by application of computer vision algorithms to define tumor border. RESULTS: Performance of a partial least squares discriminant analysis (PLS-DA) model for kidney tumor in a 22-patient study is 0.96 for area under the receiver operating characteristic curve. A PLS-DA model for in vivo breast and lung tumor xenografts performs with 100% sensitivity, 83% specificity, and 89% accuracy. CONCLUSION: Detection of cancer in surgically resected human kidney tissues is demonstrated ex vivo with Vis-NIR MCI, and in vivo on mice with breast or lung xenografts.

Mapping global and local coevolution across 600 species to identify novel homologous recombination repair genes.

The homologous recombination repair (HRR) pathway repairs DNA double-strand breaks in an error-free manner. Mutations in HRR genes can result in increased mutation rate and genomic rearrangements, and are associated with numerous genetic disorders and cancer. Despite intensive research, the HRR pathway is not yet fully mapped. Phylogenetic profiling analysis, which detects functional linkage between genes using coevolution, is a powerful approach to identify factors in many pathways. Nevertheless, phylogenetic profiling has limited predictive power when analyzing pathways with complex evolutionary dynamics such as the HRR. To map novel HRR genes systematically, we developed clade phylogenetic profiling (CladePP). CladePP detects local coevolution across hundreds of genomes and points to the evolutionary scale (e.g., mammals, vertebrates, animals, plants) at which coevolution occurred. We found that multiscale coevolution analysis is significantly more biologically relevant and sensitive to detect gene function. By using CladePP, we identified dozens of unrecognized genes that coevolved with the HRR pathway, either globally across all eukaryotes or locally in different clades. We validated eight genes in functional biological assays to have a role in DNA repair at both the cellular and organismal levels. These genes are expected to play a role in the HRR pathway and might lead to a better understanding of missing heredity in HRR-associated cancers (e.g., heredity breast and ovarian cancer). Our platform presents an innovative approach to predict gene function, identify novel factors related to different diseases and pathways, and characterize gene evolution.

SHLD2/FAM35A co-operates with REV7 to coordinate DNA double-strand break repair pathway choice.

DNA double-strand breaks (DSBs) can be repaired by two major pathways: non-homologous end-joining (NHEJ) and homologous recombination (HR). DNA repair pathway choice is governed by the opposing activities of 53BP1, in complex with its effectors RIF1 and REV7, and BRCA1. However, it remains unknown how the 53BP1/RIF1/REV7 complex stimulates NHEJ and restricts HR to the S/G2 phases of the cell cycle. Using a mass spectrometry (MS)-based approach, we identify 11 high-confidence REV7 interactors and elucidate the role of SHLD2 (previously annotated as FAM35A and RINN2) as an effector of REV7 in the NHEJ pathway. FAM35A depletion impairs NHEJ-mediated DNA repair and compromises antibody diversification by class switch recombination (CSR) in B cells. FAM35A accumulates at DSBs in a 53BP1-, RIF1-, and REV7-dependent manner and antagonizes HR by limiting DNA end resection. In fact, FAM35A is part of a larger complex composed of REV7 and SHLD1 (previously annotated as C20orf196 and RINN3), which promotes NHEJ and limits HR Together, these results establish SHLD2 as a novel effector of REV7 in controlling the decision-making process during DSB repair.