Exome sequencing identified six copy number variations as a prediction model for recurrence of primary prostate cancers with distinctive prognosis

Reticular Myxoid Odontogenic Neoplasm with Novel STRN::ALK Fusion: Report of 2 Cases in 3-Year-Old Males

Odontogenic tumors represent a collection of entities ranging from hamartomas to destructive benign and malignant neoplasms. Occasionally, pathologists encounter gnathic lesions which clearly exhibit an odontogenic origin but do not fit within the confines of established diagnoses. Here, we describe two such odontogenic tumors, both affecting 3-year-old males. Each case presented as a destructive, radiolucent mandibular lesion composed of mesenchymal cells, some with unique multi-lobed nuclei, frequently arranged in a reticular pattern and supported by a myxoid stroma with focal laminations. Production of odontogenic hard tissues was also seen. Because of their unique microscopic features, both cases were investigated by next-generation sequencing and found to harbor the same STRN::ALK oncogene fusion. To our knowledge, these cases represent the first report of an odontogenic tumor with a STRN::ALK gene rearrangement. We propose the possibility that this neoplasm could be separate from other known odontogenic tumors. Both patients were treated with surgical resection and reconstruction. The prognosis of patients with this entity is currently uncertain but shall become more apparent over time as more cases are identified and followed.

Multi-omics approach for identifying CNV-associated lncRNA signatures with prognostic value in prostate cancer

BACKGROUND

Prostate cancer, the second most prevalent malignancy among men, poses a significant threat to affected patients' well-being due to its poor prognosis. Novel biomarkers are required to enhance clinical outcomes and tailor personalized treatments. Herein, we describe our research to explore the prognostic value of long non-coding RNAs (lncRNAs) deregulated by copy number variations (CNVs) in prostate cancer.

METHODS

The study employed an integrative multi-omics data analysis of the prostate cancer transcriptomic, CNV and methylation datasets to identify prognosis-related subtypes. Subtype-specific expression profiles of protein-coding genes (PCGs) and lncRNAs were determined. We analysed CNV patterns of lncRNAs across the genome to identify subtype-specific lncRNAs with CNV changes. LncRNAs exhibiting significant amplification or deletion and a positive correlation were designated CNV-deregulated lncRNAs. A prognostic risk score model was subsequently developed using these CNV-driven lncRNAs.

RESULTS

Six molecular subtypes of prostate cancer were identified, demonstrating significant differences in prognosis (P = 0.034). The CNV profiles of subtype-specific lncRNAs were examined, revealing their correlation with CNV amplification or deletion. Six lncRNAs (CCAT2, LINC01593, LINC00276, GACAT2, LINC00457, LINC01343) were selected based on significant CNV amplifications or deletions using a rigorous univariate Cox proportional risk regression model. A robust risk score model was developed, stratifying patients into high-risk and low-risk categories. Notably, our prognostic model based on these six lncRNAs exhibited exceptional predictive capabilities for recurrence-free survival (RFS) in prostate cancer patients (P = 0.024).

CONCLUSIONS

Our study successfully identified a prognostic risk score model comprising six CNV-driven lncRNAs that could potentially be prognostic biomarkers for prostate cancer. These lncRNA signatures are closely associated with RFS, providing promising prospects for improved patient prognostication and personalized therapeutic strategies for novel prostate cancer treatment.

Whole-exome sequencing of Indian prostate cancer reveals a novel therapeutic target: POLQ

PURPOSE

Prostate cancer is the second most common cancer diagnosed worldwide and the third most common cancer among men in India. This study's objective was to characterise the mutational landscape of Indian prostate cancer using whole-exome sequencing to identify population-specific polymorphisms.

METHODS

Whole-exome sequencing was performed of 58 treatment-naive primary prostate tumors of Indian origin. Multiple computational and statistical analyses were used to profile the known common mutations, other deleterious mutations, driver genes, prognostic biomarkers, and gene signatures unique to each clinical parameter. Cox analysis was performed to validate survival-associated genes. McNemar test identified genes significant to recurrence and receiver-operating characteristic (ROC) analysis was conducted to determine its accuracy. OncodriveCLUSTL algorithm was used to deduce driver genes. The druggable target identified was modeled with its known inhibitor using Autodock.

RESULTS

TP53 was the most commonly mutated gene in our cohort. Three novel deleterious variants unique to the Indian prostate cancer subtype were identified: POLQ, FTHL17, and OR8G1. COX regression analysis identified ACSM5, a mitochondrial gene responsible for survival. CYLC1 gene, which encodes for sperm head cytoskeletal protein, was identified as an unfavorable prognostic biomarker indicative of recurrence. The novel POLQ mutant, also identified as a driver gene, was evaluated as the druggable target in this study. POLQ, a DNA repair enzyme implicated in various cancer types, is overexpressed and is associated with a poor prognosis. The mutant POLQ was subjected to structural analysis and modeled with its known inhibitor novobiocin resulting in decreased binding efficiency necessitating the development of a better drug.

CONCLUSION

In this pilot study, the molecular profiling using multiple computational and statistical analyses revealed distinct polymorphisms in the Indian prostate cancer cohort. The mutational signatures identified provide a valuable resource for prognostic stratification and targeted treatment strategies for Indian prostate cancer patients. The DNA repair enzyme, POLQ, was identified as the druggable target in this study.

Mutational Signature and Integrative Genomic Analysis of Human Papillomavirus-Associated Penile Squamous Cell Carcinomas from Latin American Patients

High-throughput DNA sequencing has allowed for the identification of genomic alterations and their impact on tumor development, progression, and therapeutic responses. In PSCC, for which the incidence has progressively increased worldwide, there are still limited data on the molecular mechanisms involved in the disease pathogenesis. In this study, we characterized the mutational signature of 30 human papillomavirus (HPV)-associated PSCC cases from Latin Americans, using whole-exome sequencing. Copy number variations (CNVs) were also identified and compared to previous array-generated data. Enrichment analyses were performed to reveal disrupted pathways and to identify alterations mapped to HPV integration sites (HPVis) and miRNA-mRNA hybridization regions. Among the most frequently mutated genes were NOTCH1, TERT, TTN, FAT1, TP53, CDKN2A, RYR2, CASP8, FBXW7, HMCN2, and ITGA8. Of note, 92% of these altered genes were localized at HPVis. We also found mutations in ten novel genes (KMT2C, SMARCA4, PTPRB, AJUBA, CR1, KMT2D, NBEA, FAM135B, GTF2I, and CIC), thus increasing our understanding of the potential HPV-disrupted pathways. Therefore, our study reveals innovative targets with potential therapeutic benefits for HPV-associated PSCCs. The CNV analysis by sequencing (CNV-seq) revealed five cancer-associated genes as the most frequent with gains (NOTCH1, MYC, NUMA1, PLAG1, and RAD21), while 30% of the tumors showed SMARCA4 with loss. Additionally, four cancer-associated genes (CARD11, CSMD3, KDR, and TLX3) carried untranslated regions (UTRs) variants, which may impact gene regulation by affecting the miRNAs hybridization regions. Altogether, these data contribute to the characterization of the mutational spectrum and its impact on cellular signaling pathways in PSCC, thus reinforcing the pivotal role of HPV infection in the molecular pathogenesis of these tumors.