CDKN2A somatic copy number amplification in normal tissues surrounding gastric carcinoma reduces cancer metastasis risk in droplet digital PCR analysis.

BACKGROUND: The CDKN2A gene is frequently affected by somatic copy number variations (SCNVs, including deletions and amplifications [SCNdel and SCNamp]) in the cancer genome. Using surgical gastric margin tissue samples (SMs) as the diploid reference in SCNV analysis via CDKN2A/P16-specific real-time PCR (P16-Light), we previously reported that the CDKN2A SCNdel was associated with a high risk of metastasis of gastric carcinoma (GC). However, the status of CDKN2A SCNVs in SMs and their clinical significance have not been reported. METHODS: Peripheral white blood cell (WBC) and frozen GC and SM tissue samples were collected from patients (n = 80). Droplet digital PCR (ddPCR) was used to determine the copy number (CN) of the CDKN2A gene in tissue samples using paired WBCs as the diploid reference. RESULTS: A novel P16-ddPCR system was initially established with a minimal proportion (or limit, 10%) of the detection of CDKN2A CN alterations. While CDKN2A SCNamp events were detected in both SMs and GCs, fewer CDKN2A SCNdel events were detected in SMs than in GCs (15.0% vs. 41.3%, P = 4.77E-04). Notably, significantly more SCNamp and fewer SCNdel of the CDKN2A gene were detected in SMs from GC patients without metastasis than in those from patients with lymph node metastasis by P16-ddPCR (P = 0.023). The status of CDKN2A SCNVs in SM samples was significantly associated with overall survival (P = 0.032). No cancer deaths were observed among the 11 patients with CDKN2A SCNamp. CONCLUSION: CDKN2A SCNVs in SMs identified by P16-ddPCR are prevalent and significantly associated with GC metastasis and overall survival.

labelSeg: segment annotation for tumor copy number alteration profiles.

Somatic copy number alterations (SCNAs) are a predominant type of oncogenomic alterations that affect a large proportion of the genome in the majority of cancer samples. Current technologies allow high-throughput measurement of such copy number aberrations, generating results consisting of frequently large sets of SCNA segments. However, the automated annotation and integration of such data are particularly challenging because the measured signals reflect biased, relative copy number ratios. In this study, we introduce labelSeg, an algorithm designed for rapid and accurate annotation of CNA segments, with the aim of enhancing the interpretation of tumor SCNA profiles. Leveraging density-based clustering and exploiting the length-amplitude relationships of SCNA, our algorithm proficiently identifies distinct relative copy number states from individual segment profiles. Its compatibility with most CNA measurement platforms makes it suitable for large-scale integrative data analysis. We confirmed its performance on both simulated and sample-derived data from The Cancer Genome Atlas reference dataset, and we demonstrated its utility in integrating heterogeneous segment profiles from different data sources and measurement platforms. Our comparative and integrative analysis revealed common SCNA patterns in cancer and protein-coding genes with a strong correlation between SCNA and messenger RNA expression, promoting the investigation into the role of SCNA in cancer development.

Somatic Copy Number Alterations in Colorectal Cancer Lead to a Differentially Expressed ceRNA Network (ceRNet).

Colorectal cancer (CRC) represents the second deadliest malignancy worldwide. Around 75% of CRC patients exhibit high levels of chromosome instability that result in the accumulation of somatic copy number alterations. These alterations are associated with the amplification of oncogenes and deletion of tumor-ppressor genes and contribute to the tumoral phenotype in different malignancies. Even though this relationship is well known, much remains to be investigated regarding the effect of said alterations in long non-coding RNAs (lncRNAs) and, in turn, the impact these alterations have on the tumor phenotype. The present study aimed to evaluate the role of differentially expressed lncRNAs coded in regions with copy number alterations in colorectal cancer patient samples. We downloaded RNA-seq files of the Colorectal Adenocarcinoma Project from the The Cancer Genome Atlas (TCGA) repository (285 sequenced tumor tissues and 41 non-tumor tissues), evaluated differential expression, and mapped them over genome sequencing data with regions presenting copy number alterations. We obtained 78 differentially expressed (LFC > 1|< -1, padj < 0.05) lncRNAs, 410 miRNAs, and 5028 mRNAs and constructed a competing endogenous RNA (ceRNA) network, predicting significant lncRNA-miRNA-mRNA interactions. Said network consisted of 30 lncRNAs, 19 miRNAs, and 77 mRNAs. To understand the role that our ceRNA network played, we performed KEGG and GO analysis and found several oncogenic and anti-oncogenic processes enriched by the molecular players in our network. Finally, to evaluate the clinical relevance of the lncRNA expression, we performed survival analysis and found that C5orf64, HOTAIR, and RRN3P3 correlated with overall patient survival. Our results showed that lncRNAs coded in regions affected by SCNAs form a complex gene regulatory network in CCR.

Aneuploidy in human cancer: new tools and perspectives.

Chromosome copy number imbalances, otherwise known as aneuploidies, are a common but poorly understood feature of cancer. Here, we describe recent advances in both detecting and manipulating aneuploidies that have greatly advanced our ability to study their role in tumorigenesis. In particular, new clustered regularly interspaced short palindromic repeats (CRISPR)-based techniques have been developed that allow the creation of isogenic cell lines with specific chromosomal changes, thereby facilitating experiments in genetically controlled backgrounds to uncover the consequences of aneuploidy. These approaches provide increasing evidence that aneuploidy is a key driver of cancer development and enable the identification of multiple dosage-sensitive genes encoded on aneuploid chromosomes. Consequently, measuring aneuploidy may inform clinical prognosis, while treatment strategies that target aneuploidy could represent a novel method to counter malignant growth.

DNA cytosine deamination is associated with recurrent Somatic Copy Number Alterations in stomach adenocarcinoma.

Stomach Adenocarcinoma (STAD) is a leading cause of death worldwide. Somatic Copy Number Alterations (SCNAs), which result in Homologous recombination (HR) deficiency in double-strand break repair, are associated with the progression of STAD. However, the landscape of frequent breakpoints of SCNAs (hotspots) and their functional impacts remain poorly understood. In this study, we aimed to explore the frequency and impact of these hotspots in 332 STAD patients and 1,043 cancer cells using data from the Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE). We studied the rates of DSB (Double-Strand Breaks) loci in STAD patients by employing the Non-Homogeneous Poisson Distribution (λ), based on which we identified 145 DSB-hotspots with genes affected. We further verified DNA cytosine deamination as a critical process underlying the burden of DSB in STAD. Finally, we illustrated the clinical impact of the significant biological processes. Our findings highlighted the relationship between DNA cytosine deamination and SCNA in cancer was associated with recurrent Somatic Copy Number Alterations in STAD.

Genomic analyses of germline and somatic variation in high-grade serous ovarian cancer.

BACKGROUND: High-grade serous ovarian cancers (HGSCs) display a high degree of complex genetic alterations. In this study, we identified germline and somatic genetic alterations in HGSC and their association with relapse-free and overall survival. Using a targeted capture of 557 genes involved in DNA damage response and PI3K/AKT/mTOR pathways, we conducted next-generation sequencing of DNA from matched blood and tumor tissue from 71 HGSC participants. In addition, we performed the OncoScan assay on tumor DNA from 61 participants to examine somatic copy number alterations (SCNA). RESULTS: Approximately one-third of tumors had loss-of-function (LOF) germline (18/71, 25.4%) or somatic (7/71, 9.9%) variants in the DNA homologous recombination repair pathway genes BRCA1, BRCA2, CHEK2, MRE11A, BLM, and PALB2. LOF germline variants also were identified in other Fanconi anemia genes and in MAPK and PI3K/AKT/mTOR pathway genes. Most tumors harbored somatic TP53 variants (65/71, 91.5%). Using the OncoScan assay on tumor DNA from 61 participants, we identified focal homozygous deletions in BRCA1, BRCA2, MAP2K4, PTEN, RB1, SLX4, STK11, CREBBP, and NF1. In total, 38% (27/71) of HGSC patients harbored pathogenic variants in DNA homologous recombination repair genes. For patients with multiple tissues from the primary debulking or from multiple surgeries, the somatic mutations were maintained with few newly acquired point mutations suggesting that tumor evolution was not through somatic mutations. There was a significant association of LOF variants in homologous recombination repair pathway genes and high-amplitude somatic copy number alterations. Using GISTIC analysis, we identified NOTCH3, ZNF536, and PIK3R2 in these regions that were significantly associated with an increase in cancer recurrence and a reduction in overall survival. CONCLUSIONS: From 71 patients with HGCS, we performed targeted germline and tumor sequencing and provided a comprehensive analysis of these 557 genes. We identified germline and somatic genetic alterations including somatic copy number alterations and analyzed their associations with relapse-free and overall survival. This single-site long-term follow-up study provides additional information on genetic alterations related to occurrence and outcome of HGSC. Our findings suggest that targeted treatments based on both variant and SCNA profile potentially could improve relapse-free and overall survival.

Simultaneous Copy Number Alteration and Single-Nucleotide Variation Analysis in Matched Aqueous Humor and Tumor Samples in Children with Retinoblastoma.

Retinoblastoma (RB) is a childhood cancer that forms in the developing retina of young children; this tumor cannot be biopsied due to the risk of provoking extraocular tumor spread, which dramatically alters the treatment and survival of the patient. Recently, aqueous humor (AH), the clear fluid in the anterior chamber of the eye, has been developed as an organ-specific liquid biopsy for investigation of in vivo tumor-derived information found in the cell-free DNA (cfDNA) of the biofluid. However, identifying somatic genomic alterations, including both somatic copy number alterations (SCNAs) and single nucleotide variations (SNVs) of the RB1 gene, typically requires either: (1) two distinct experimental protocols-low-pass whole genome sequencing for SCNAs and targeted sequencing for SNVs-or (2) expensive deep whole genome or exome sequencing. To save time and cost, we applied a one-step targeted sequencing method to identify both SCNAs and RB1 SNVs in children with RB. High concordance (median = 96.2%) was observed in comparing SCNA calls derived from targeted sequencing to the traditional low-pass whole genome sequencing method. We further applied this method to investigate the degree of concordance of genomic alterations between paired tumor and AH samples from 11 RB eyes. We found 11/11 AH samples (100%) had SCNAs, and 10 of them (90.1%) with recurrent RB-SCNAs, while only nine out of 11 tumor samples (81.8%) had positive RB-SCNA signatures in both low-pass and targeted methods. Eight out of the nine (88.9%) detected SNVs were shared between AH and tumor samples. Ultimately, 11/11 cases have somatic alterations identified, including nine RB1 SNVs and 10 recurrent RB-SCNAs with four focal RB1 deletions and one MYCN gain. The results presented show the feasibility of utilizing one sequencing approach to obtain SCNA and targeted SNV data to capture a broad genomic scope of RB disease, which may ultimately expedite clinical intervention and be less expensive than other methods.

SOX2 dosage sustains tumor-promoting inflammation to drive disease aggressiveness by modulating the FOSL2/IL6 axis.

BACKGROUND: Inflammation is undoubtedly a hallmark of cancer development. Its maintenance within tumors and the consequences on disease aggressiveness are insufficiently understood. METHODS: Data of 27 tumor entities (about 5000 samples) were downloaded from the TCGA and GEO databases. Multi-omic analyses were performed on these and in-house data to investigate molecular determinants of tumor aggressiveness. Using molecular loss-of-function data, the mechanistic underpinnings of inflammation-induced tumor aggressiveness were addressed. Patient specimens and in vivo disease models were subsequently used to validate findings. RESULTS: There was significant association between somatic copy number alterations (sCNAs) and tumor aggressiveness. SOX2 amplification was the most important feature among novel and known aggressiveness-associated alterations. Mechanistically, SOX2 regulates a group of genes, in particular the AP1 transcription factor FOSL2, to sustain pro-inflammatory signaling pathways, such as IL6-JAK-STAT3, TNFA and IL17. FOSL2 was found overexpressed in tumor sections of specifically aggressive cancers. In consequence, prolonged inflammation induces immunosuppression and activates cytidine deamination and thus DNA damage as evidenced by related mutational signatures in aggressive tumors. The DNA damage affects tumor suppressor genes such as TP53, which is the most mutated gene in aggressive tumors compared to less aggressive ones (38% vs 14%), thereby releasing cell cycle control. These results were confirmed by analyzing tissues from various tumor types and in vivo studies. CONCLUSION: Our data demonstrate the implication of SOX2 in promoting DNA damage and genome instability by sustaining inflammation via FOSL2/IL6, resulting in tumor aggressiveness.

Subclonal somatic copy number alterations emerge and dominate in recurrent osteosarcoma.

Multiple large-scale tumor genomic profiling efforts have been undertaken in osteosarcoma, however, little is known about the spatial and temporal intratumor heterogeneity and how it may drive treatment resistance. We performed whole-genome sequencing of 37 tumor samples from eight patients with relapsed or refractory osteosarcoma. Each patient had at least one sample from a primary site and a metastatic or relapse site. We identified subclonal copy number alterations in all but one patient. We observed that in five patients, a subclonal copy number clone from the primary tumor emerged and dominated at subsequent relapses. MYC gain/amplification was enriched in the treatment-resistant clone in 6 out of 7 patients with more than one clone. Amplifications in other potential driver genes, such as CCNE1, RAD21, VEGFA, and IGF1R, were also observed in the resistant copy number clones. Our study sheds light on intratumor heterogeneity and the potential drivers of treatment resistance in osteosarcoma.

Evaluation of cell-free DNA approaches for multi-cancer early detection.

In the Circulating Cell-free Genome Atlas (NCT02889978) substudy 1, we evaluate several approaches for a circulating cell-free DNA (cfDNA)-based multi-cancer early detection (MCED) test by defining clinical limit of detection (LOD) based on circulating tumor allele fraction (cTAF), enabling performance comparisons. Among 10 machine-learning classifiers trained on the same samples and independently validated, when evaluated at 98% specificity, those using whole-genome (WG) methylation, single nucleotide variants with paired white blood cell background removal, and combined scores from classifiers evaluated in this study show the highest cancer signal detection sensitivities. Compared with clinical stage and tumor type, cTAF is a more significant predictor of classifier performance and may more closely reflect tumor biology. Clinical LODs mirror relative sensitivities for all approaches. The WG methylation feature best predicts cancer signal origin. WG methylation is the most promising technology for MCED and informs development of a targeted methylation MCED test.

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution.

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

Chromosome 6p amplification detected in blood cell-free DNA in advanced intraocular retinoblastoma.

BACKGROUND: In patients with retinoblastoma, gains of chromosome 6p have been associated with less differentiated tumors. In cell-free DNA from the aqueous humor (AH), 6p gain has been associated with an increased risk of enucleation. While the identification of somatic copy number alterations (SCNAs) via the AH has been well established, these alterations are not routinely identified in the blood due to low tumor fraction. MATERIALS AND METHODS: SCNAs were considered positive at 20% deflection from the baseline. Somatic RB1 pathogenic variants were identified with targeted sequencing using a panel including all RB1 exons. RESULTS: A 24-month-old patient presented with unilateral retinoblastoma (Group D/AJCC Stage cT2B) and was treated with primary enucleation. In the peripheral blood, a heterozygous mutation (c.3920T>A) in the APC gene was reported. Genomic analysis of the tumor and AH revealed two novel somatic RB1 mutations (c.1589_1590del and c.2330dupC). Both also demonstrated highly recurrent RB-related SCNAs. Chromosome 6p gain was detected in the blood with an amplitude suggesting approximately 12% tumor fraction. At a follow-up of 24 months, there has been no evidence of metastatic disease. CONCLUSIONS: To our knowledge, this is the first time an SCNA has been detected in the blood of an RB patient, suggesting in some advanced eyes there may be a high enough tumor fraction to detect these alterations (>5% needed). It remains unclear whether 6p gain or increased tumor fraction in the blood is indicative of increased risk of metastatic disease or new primary cancer; studies to address this are ongoing.

Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients.

BACKGROUND: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. METHODS: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~ 6× coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. RESULTS: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and somatic copy number alterations. We further combined global and regional fragmentation pattern into a machine learning (ML) classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. CONCLUSION: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring. Trial registration DRKS00012890.

Low-cost and clinically applicable copy number profiling using repeat DNA.

BACKGROUND: Somatic copy number alterations (SCNAs) are an important class of genomic alteration in cancer. They are frequently observed in cancer samples, with studies showing that, on average, SCNAs affect 34% of a cancer cell's genome. Furthermore, SCNAs have been shown to be major drivers of tumour development and have been associated with response to therapy and prognosis. Large-scale cancer genome studies suggest that tumours are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Despite the frequency of SCNAs and their clinical relevance, the use of genomics assays in the clinic is biased towards targeted gene panels, which identify SNVs but provide limited scope to detect SCNAs throughout the genome. There is a need for a comparably low-cost and simple method for high-resolution SCNA profiling. RESULTS: We present conliga, a fully probabilistic method that infers SCNA profiles from a low-cost, simple, and clinically-relevant assay (FAST-SeqS). When applied to 11 high-purity oesophageal adenocarcinoma samples, we obtain good agreement (Spearman's rank correlation coefficient, rs=0.94) between conliga's inferred SCNA profiles using FAST-SeqS data (approximately £14 per sample) and those inferred by ASCAT using high-coverage WGS (gold-standard). We find that conliga outperforms CNVkit (rs=0.89), also applied to FAST-SeqS data, and is comparable to QDNAseq (rs=0.96) applied to low-coverage WGS, which is approximately four-fold more expensive, more laborious and less clinically-relevant. By performing an in silico dilution series experiment, we find that conliga is particularly suited to detecting SCNAs in low tumour purity samples. At two million reads per sample, conliga is able to detect SCNAs in all nine samples at 3% tumour purity and as low as 0.5% purity in one sample. Crucially, we show that conliga's hidden state information can be used to decide when a sample is abnormal or normal, whereas CNVkit and QDNAseq cannot provide this critical information. CONCLUSIONS: We show that conliga provides high-resolution SCNA profiles using a convenient, low-cost assay. We believe conliga makes FAST-SeqS a more clinically valuable assay as well as a useful research tool, enabling inexpensive and fast copy number profiling of pre-malignant and cancer samples.

Robustness of the Autophagy Pathway to Somatic Copy Number Losses.

Autophagy allows cells to temporarily tolerate energy stress by replenishing critical metabolites through self-digestion, thereby attenuating the cytotoxic effects of anticancer drugs that target tumor metabolism. Autophagy defects could therefore mark a metabolically vulnerable cancer state and open a therapeutic window. While mutations of autophagy genes (ATGs) are notably rare in cancer, haploinsufficiency network analyses across many cancers have shown that the autophagy pathway is frequently hit by somatic copy number losses of ATGs such as MAP1LC3B/ATG8F (LC3), BECN1/ATG6 (Beclin-1), and ATG10. Here, we used CRISPR/Cas9 technology to delete increasing numbers of copies of one or more of these ATGs in non-small cell lung cancer cells and examined the effects on sensitivity to compounds targeting aerobic glycolysis, a hallmark of cancer metabolism. Whereas the complete knockout of one ATG blocked autophagy and led to profound metabolic vulnerability, this was not the case for combinations of different nonhomozygous deletions. In cancer patients, the effect of ATG copy number loss was blunted at the protein level and did not lead to the accumulation of p62 as a sign of reduced autophagic flux. Thus, the autophagy pathway is shown to be markedly robust and resilient, even with the concomitant copy number loss of key autophagy genes.

Genomic Analysis Made It Possible to Identify Gene-Driver Alterations Covering the Time Window between Diagnosis of Neuroblastoma 4S and the Progression to Stage 4.

Neuroblastoma (NB) is a tumor of the developing sympathetic nervous system. Despite recent advances in understanding the complexity of NB, the mechanisms that determine its regression or progression are still largely unknown. Stage 4S NB is characterized by a favorable course of disease and often by spontaneous regression, while progression to true stage 4 is a very rare event. Here, we focused on genomic analysis of an NB case that progressed from stage 4S to stage 4 with a very poor outcome. Array-comparative genomic hybridization (a-CGH) on tumor-tissue DNA, and whole-exome sequencing (WES) on exosomes DNA derived from plasma collected at the onset and at the tumor progression, pointed out relevant genetic changes that can explain this clinical worsening. The combination of a-CGH and WES data allowed for the identification iof somatic copy number aberrations and single-nucleotide variants in genes known to be responsible for aggressive NB. KLRB1, MAPK3 and FANCA genes, which were lost at the time of progression, were studied for their possible role in this event by analyzing in silico the impact of their expression on the outcome of 786 NB patients.

Classification of lung adenocarcinoma based on stemness scores in bulk and single cell transcriptomes.

Tumor stemness is associated with tumor progression and therapy resistance. The recent advances in sequencing, genomics, and computational technologies have facilitated investigation into the tumor stemness cell-like characteristics. We identified subtypes of lung adenocarcinoma (LUAD) in bulk tumors or single cells based on the enrichment scores of 12 stemness signatures by clustering analysis of their transcriptomic profiles. Three stemness subtypes of LUAD were identified: St-H, St-M, and St-L, having high, medium, and low stemness signatures, respectively, consistently in six different datasets. Among the three subtypes, St-H was the most enriched in epithelial-mesenchymal transition, invasion, and metastasis signaling, genomically instable, irresponsive to immunotherapies and targeted therapies, and hence had the worst prognosis. We observed that intratumor heterogeneity was significantly higher in high-stemness than in low-stemness bulk tumors, but significantly lower in high-stemness than in low-stemness single cancer cells. Moreover, tumor immunity was stronger in high-stemness than in low-stemness cancer cells, but weaker in high-stemness than in low-stemness bulk tumors. These differences between bulk tumors and single cancer cells could be attributed to the non-tumor cells in bulk tumors that confounded the results of correlation analysis. Furthermore, pseudotime analysis showed that many St-H cells were at the beginning of the cell evolution trajectory, compared to most St-L cells in the terminal or later phase, suggesting that many low-stemness cells are originated from high-stemness cells. The stemness-based classification of LUAD may provide novel insights into the tumor biology as well as precise clinical management of this disease.

Refinement of computational identification of somatic copy number alterations using DNA methylation microarrays illustrated in cancers of unknown primary.

High-throughput genomic technologies are increasingly used in personalized cancer medicine. However, computational tools to maximize the use of scarce tissues combining distinct molecular layers are needed. Here we present a refined strategy, based on the R-package 'conumee', to better predict somatic copy number alterations (SCNA) from deoxyribonucleic acid (DNA) methylation arrays. Our approach, termed hereafter as 'conumee-KCN', improves SCNA prediction by incorporating tumor purity and dynamic thresholding. We trained our algorithm using paired DNA methylation and SNP Array 6.0 data from The Cancer Genome Atlas samples and confirmed its performance in cancer cell lines. Most importantly, the application of our approach in cancers of unknown primary identified amplified potentially actionable targets that were experimentally validated by Fluorescence in situ hybridization and immunostaining, reaching 100% specificity and 93.3% sensitivity.

Alterations of DNA damage response pathway: Biomarker and therapeutic strategy for cancer immunotherapy.

Genomic instability remains an enabling feature of cancer and promotes malignant transformation. Alterations of DNA damage response (DDR) pathways allow genomic instability, generate neoantigens, upregulate the expression of programmed death ligand 1 (PD-L1) and interact with signaling such as cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) signaling. Here, we review the basic knowledge of DDR pathways, mechanisms of genomic instability induced by DDR alterations, impacts of DDR alterations on immune system, and the potential applications of DDR alterations as biomarkers and therapeutic targets in cancer immunotherapy.

MicroRNA-regulated transcriptome analysis identifies four major subtypes with prognostic and therapeutic implications in prostate cancer.

MicroRNA (miRNA) deregulation plays a critical role in the heterogeneous development of prostate cancer (PCa) by tuning mRNA levels. Herein, we aimed to characterize the molecular features of PCa by clustering the miRNA-regulated transcriptome with non-negative matrix factorization. Using 478 PCa samples from The Cancer Genome Atlas, four molecular subtypes (S-I, S-II, S-III, and S-IV) were identified and validated in two merged microarray and RNAseq datasets with 656 and 252 samples, respectively. Interestingly, the four subtypes showed distinct clinical and biological features after comprehensive analyses of clinical features, multiomic profiles, immune infiltration, and drug sensitivity. S-I is basal/stem/mesenchymal-like and immune-excluded with marked transforming growth factor ß, epithelial-mesenchymal transition and hypoxia signals, increased sensitivity to olaparib, and intermediate prognosis. S-II is luminal/metabolism-active and responsive to androgen deprivation therapy with frequent TMPRSS2-ERG fusion and a good prognosis. S-III is characterized by moderate proliferative and metabolic activity, sensitivity to taxane-based chemotherapy, and intermediate prognosis. S-IV is highly proliferative with moderate EMT and stemness, frequent deletions of TP53, PTEN and RB, and the poorest prognosis; it is also immune-inflamed and sensitive to anti-PD-L1 therapy. Overall, based on miRNA-regulated gene profiles, this study identified four distinct PCa subtypes that could improve risk stratification at diagnosis and provide therapeutic guidance.