CoNVaQ: a web tool for copy number variation-based association studies

Context-Dependent Regulation of Peripheral Nerve Abundance by the PI3K Pathway in the Tumor Microenvironment of Head and Neck Squamous Cell Carcinoma

Recent studies have highlighted neurons and their associated Schwann cells (SCs) as key regulators of cancer development. However, the mode of their interaction with tumor cells or other components of the tumor microenvironment (TME) remains elusive. We established an SC-related 43-gene set as a surrogate for peripheral nerves in the TME. Head and neck squamous cell carcinoma (HNSCC) from The Cancer Genome Atlas (TCGA) were classified into low, intermediate and high SC score groups based on the expression of this gene set. Perineural invasion (PNI) and TGF-β signaling were hallmarks of SChigh tumors, whereas SClow tumors were enriched for HPV16-positive OPSCC and higher PI3K-MTOR activity. The latter activity was partially explained by a higher frequency of PTEN mutation and PIK3CA copy number gain. The inverse association between PI3K-MTOR activity and peripheral nerve abundance was context-dependent and influenced by the TP53 mutation status. An in silico drug screening approach highlighted the potential vulnerabilities of HNSCC with variable SC scores and predicted a higher sensitivity of SClow tumors to DNA topoisomerase inhibitors. In conclusion, we have established a tool for assessing peripheral nerve abundance in the TME and provided new clinical and biological insights into their regulation. This knowledge may pave the way for new therapeutic strategies and impart proof of concept in appropriate preclinical models.

Identification of a cancer-associated fibroblast classifier for predicting prognosis and therapeutic response in lung squamous cell carcinoma

Reliable prognostic gene signatures for cancer-associated fibroblasts (CAFs) in lung squamous cell carcinoma (LUSC) are still lacking, and the underlying genetic principles remain unclear. Therefore, the 2 main aims of our study were to establish a reliable CAFs prognostic gene signature that can be used to stratify patients with LUSC and to identify promising potential targets for more effective and individualized therapies. Clinical information and mRNA expression were accessed of the cancer genome atlas-LUSC cohort (n = 501) and GSE157011 cohort (n = 484). CAFs abundance were quantified by the multi-estimated algorithms. Stromal CAF-related genes were identified by weighted gene co-expression network analysis. The least absolute shrinkage and selection operator Cox regression method was utilized to identify the most relevant CAFs candidates for predicting prognosis. Chemotherapy sensitivity scores were calculated using the "pRRophetic" package in R software, and the tumor immune dysfunction and exclusion algorithm was employed to evaluate immunotherapy response. Gene set enrichment analysis and the Search Tool for Interaction of Chemicals database were applied to clarify the molecular mechanisms. In this study, we identified 288 hub CAF-related candidate genes by weighted gene co-expression network analysis. Next, 34 potential prognostic CAFs candidate genes were identified by univariate Cox regression in the cancer genome atlas-LUSC cohort. We prioritized the top 8 CAFs prognostic genes (DCBLD1, SLC24A3, ILK, SMAD7, SERPINE1, SNX9, PDGFA, and KLF10) by a least absolute shrinkage and selection operator Cox regression model, and these genes were used to identify low- and high-risk subgroups for unfavorable survival. In silico drug screening identified 6 effective compounds for high-risk CAFs-related LUSC: TAK-715, GW 441756, OSU-03012, MP470, FH535, and KIN001-266. Additionally, search tool for interaction of chemicals database highlighted PI3K-Akt signaling as a potential target pathway for high-risk CAFs-related LUSC. Overall, our findings provide a molecular classifier for high-risk CAFs-related LUSC and suggest that treatment with PI3K-Akt signaling inhibitors could benefit these patients.

Uncovering structural variants associated with body weight and obesity risk in labrador retrievers: a genome-wide study

Although obesity in the domestic dog (Canis lupus familiaris) is known to decrease well-being and shorten lifespan, the genetic risk variants associated with canine obesity remain largely unknown. In our study, which focused on the obesity-prone Labrador Retriever breed, we conducted a genome-wide analysis to identify structural variants linked to body weight and obesity. Obesity status was based on a 5-point body condition score (BCS) and the obese dog group included all dogs with a BCS of 5, along with dogs with the highest body weight within the BCS 4 group. Data from whole-gene sequencing of fifty dogs, including 28 obese dogs, were bioinformatically analyzed to identify potential structural variants that varied in frequency between obese and healthy dogs. The seven most promising variants were further analyzed by droplet digital PCR in a group of 110 dogs, including 63 obese. Our statistical evidence suggests that common structural mutations in or near six genes, specifically ALPL, KCTD8, SGSM1, SLC12A6, RYR3, and VPS26C, may contribute to the variability observed in body weight and body condition scores among Labrador Retriever dogs. These findings emphasize the need for additional research to validate the associations and explore the specific functions of these genes in relation to canine obesity.

Establishment of a Machine Learning Model for the Risk Assessment of Perineural Invasion in Head and Neck Squamous Cell Carcinoma

Perineural invasion is a prevalent pathological finding in head and neck squamous cell carcinoma and a risk factor for unfavorable survival. An adequate diagnosis of perineural invasion by pathologic examination is limited due to the availability of tumor samples from surgical resection, which can arise in cases of definitive nonsurgical treatment. To address this medical need, we established a random forest prediction model for the risk assessment of perineural invasion, including occult perineural invasion, and characterized distinct cellular and molecular features based on our new and extended classification. RNA sequencing data of head and neck squamous cell carcinoma from The Cancer Genome Atlas were used as a training cohort to identify differentially expressed genes that are associated with perineural invasion. A random forest classification model was established based on these differentially expressed genes and was validated by inspection of H&E-stained whole image slides. Differences in epigenetic regulation and the mutational landscape were detected by an integrative analysis of multiomics data and single-cell RNA-sequencing data were analyzed. We identified a 44-gene expression signature related to perineural invasion and enriched for genes mainly expressed in cancer cells according to single-cell RNA-sequencing data. A machine learning model was trained based on the expression pattern of the 44-gene set with the unique feature to predict occult perineural invasion. This extended classification model enabled a more accurate analysis of alterations in the mutational landscape and epigenetic regulation by DNA methylation as well as quantitative and qualitative differences in the cellular composition in the tumor microenvironment between head and neck squamous cell carcinoma with or without perineural invasion. In conclusion, the newly established model could not only complement histopathologic examination as an additional diagnostic tool but also guide the identification of new drug targets for therapeutic intervention in future clinical trials with head and neck squamous cell carcinoma patients at a higher risk for treatment failure due to perineural invasion.

PeakCNV: A multi-feature ranking algorithm-based tool for genome-wide copy number variation-association study

Copy Number Variation (CNV) refers to a type of structural genomic alteration in which a segment of chromosome is duplicated or deleted. To date, many CNVs have been identified as causative genetic elements for several diseases and phenotypes. However, performing a CNV-based genome-wide association study is challenging due to inconsistency in length and occurrence of CNVs across different individuals under investigation. One of the most efficient strategies to address this issue is building CNV regions (genomic regions in which CNVs are overlapping - CNVRs). However, this approach is susceptible to a high false positive rate due to overlapping and co-occurring of confounding CNVRs with true positive CNVRs. Here, we develop PeakCNV that differentiates false-positive CNVRs from true positives by calculating a new metric, independence ranking score, (IR-score) via a feature ranking approach. We compared the performance of PeakCNV with other current existing tools by carrying out two case studies one using the CNV genotype data for individuals with prostate cancer (194 cases and 2,392 healthy individuals) and the second one for individuals with neurodevelopmental disorders (19,642 cases and 6,451 healthy individuals). Crucially, our benchmarking analyses on prostate cancer cohort indicated that PeakCNV identifies a fewer risk candidate CNVRs with shorter lengths compared to other tools. Importantly, these CNVRs cover a greater proportion of case over healthy individuals compared to other tools. The accuracy of PeakCNV in identifying relevant candidate CNVRs was reproducible in the case study on neurodevelopmental disorders. Using data from the FANTOM5 expression atlas and the Clinical Genomic Database, we show that the candidate CNVRs identified by PeakCNV for neurodevelopmental disorders overlap with a greater number of genes with the brain-enriched expression, and a greater number of genes that are associated with neurological conditions compared to candidate CNVRs identified by other tools. Taken together, PeakCNV outperformed current existing CNV association study tools by identifying more biologically meaningful CNVRs relevant to the phenotype of interest. PeakCNV is publicly available for the analysis of CNV-associated diseases and is accessible from https://rdrr.io/github/mahdieh1/PeakCNV.

Whole genome sequencing identifies a missense polymorphism in PADI6 associated with testicular/ovotesticular XX disorder of sex development in dogs

Disorders of sex development (DSDs) are congenital malformations defined as discrepancies between sex chromosomes and phenotypical sex. Testicular or ovotesticular XX DSDs are frequently observed in female dogs, while monogenic XY DSDs are less frequent. Here, we applied whole genome sequencing (WGS) to search for causative mutations in XX DSD females in French Bulldogs (FB) and American Staffordshire Terries (AST) and in XY DSD Yorkshire Terries (YT). The WGS results were validated by Sanger sequencing and ddPCR. It was shown that a missense SNP of the PADI6 gene, is significantly associated with the XX DSD (SRY-negative) phenotype in AST (P = 0.0051) and FB (P = 0.0306). On the contrary, we did not find any associated variant with XY DSD in YTs. Our study suggests that the genetic background of the XX DSD may be more complex and breed-specific.

Whole-genome sequencing analysis of clozapine-induced myocarditis

One of the concerns limiting the use of clozapine in schizophrenia treatment is the risk of rare but potentially fatal myocarditis. Our previous genome-wide association study and human leucocyte antigen analyses identified putative loci associated with clozapine-induced myocarditis. However, the contribution of DNA variation in cytochrome P450 genes, copy number variants and rare deleterious variants have not been investigated. We explored these unexplored classes of DNA variation using whole-genome sequencing data from 25 cases with clozapine-induced myocarditis and 25 demographically-matched clozapine-tolerant control subjects. We identified 15 genes based on rare variant gene-burden analysis (MLLT6, CADPS, TACC2, L3MBTL4, NPY, SLC25A21, PARVB, GPR179, ACAD9, NOL8, C5orf33, FAM127A, AFDN, SLC6A11, PXDN) nominally associated (p < 0.05) with clozapine-induced myocarditis. Of these genes, 13 were expressed in human myocardial tissue. Although independent replication of these findings is required, our study provides preliminary insights into the potential role of rare genetic variants in susceptibility to clozapine-induced myocarditis.

No evidence that long runs of homozygosity tend to harbor risk variants for polygenic obesity in Labrador retriever dogs

Canine polygenic obesity can be influenced by relatively recent mutations with large effects. We determined whether, as with monogenic diseases, long autozygous tracts may be disproportionately likely to harbor detrimental variants for additive polygenic obesity in Labrador retriever dogs. Both our detection of runs of homozygosity (ROH) and our preliminary association study were based on whole-genome sequencing of 28 obese and 22 healthy dogs. We detected and analyzed the distribution of 19,655 ROH. We observed 237 and 98 ROH-harboring genotypes associated with obesity and increased body mass, respectively. We found no evidence that long ROH tend to harbor genotypes linked to obesity or increased body weight, and we concluded that data on ROH overlapping GWAS signals for canine obesity are unlikely to help prioritize candidate genes for validation studies.

Multi-omics analysis of an immune-based prognostic predictor in non-small cell lung cancer

BACKGROUND

Inhibitors targeting immune checkpoints, such as PD-1/PD-L1 and CTLA-4, have prolonged survival in small groups of non-small cell lung cancer (NSCLC) patients, but biomarkers predictive of the response to the immune checkpoint inhibitors (ICIs) remain rare.

METHODS

The nonnegative matrix factorization (NMF) was performed for TCGA-NSCLC tumor samples based on the LM22 immune signature to construct subgroups. Characterization of NMF subgroups involved the single sample gene set variation analysis (ssGSVA), and mutation/copy number alteration and methylation analyses. Construction of RNA interaction network was based on the identification of differentially expressed RNAs (DERs). The prognostic predictor was constructed by a LASSO-Cox regression model. Four GEO datasets were used for the validation analysis.

RESULTS

Four immune based NMF subgroups among NSCLC patients were identified. Genetic and epigenetic analyses between subgroups revealed an important role of somatic copy number alterations in determining the immune checkpoint expression on specific immune cells. Seven hub genes were recognized in the regulatory network closely related to the immune phenotype, and a three-gene prognosis predictor was constructed.

CONCLUSIONS

Our study established an immune-based prognosis predictor, which might have the potential to select subgroups benefiting from the ICI treatment, for NSCLC patients using publicly available databases.

Prognostic Gene Signature for Squamous Cell Carcinoma with a Higher Risk for Treatment Failure and Accelerated MEK-ERK Pathway Activity

Simple Summary

Squamous cell carcinoma (SCC) is the most prevalent type of human cancer worldwide and represents the majority of head and neck tumors. As SCC from aerodigestive or genitourinary tracts share not only common etiology and histological features but also molecular patterns, the major objectives of this study were the establishment of a pan-SCC-related prognostic gene signature by an integrative analysis of multi-omics data and the elucidation of underlying oncogenic pathway activities as potential vulnerabilities for a more efficient and less toxic therapy. Our approach delivers a reliable molecular classifier to identify HNSCC and other SCC patients at higher risk for treatment failure with tumors characterized by a more prominent MAPK activity, who might benefit from a targeted treatment with MEK inhibitors.

Abstract

Squamous cell carcinoma (SCC) is the most prevalent histological type of human cancer, including head and neck squamous cell carcinoma (HNSCC). However, reliable prognostic gene signatures for SCC and underlying genetic and/or epigenetic principles are still unclear. We identified 37 prognostic candidate genes by best cutoff computation based on survival in a pan-SCC cohort (n = 1334) of The Cancer Genome Atlas (TCGA), whose expression stratified not only the pan-SCC cohort but also independent HNSCC validation cohorts into three distinct prognostic subgroups. The most relevant prognostic genes were prioritized by a Least Absolute Shrinkage and Selection Operator Cox regression model and were used to identify subgroups with high or low risks for unfavorable survival. An integrative analysis of multi-omics data identified FN1, SEMA3A, CDH2, FBN1, COL5A1, and ADAM12 as key nodes in a regulatory network related to the prognostic phenotype. An in-silico drug screen predicted two MEK inhibitors (Trametinib and Selumetinib) as effective compounds for high-risk SCC based on the Cancer Cell Line Encyclopedia, which is supported by a higher p-MEK1/2 immunohistochemical staining of high-risk HNSCC. In conclusion, our data identified a molecular classifier for high-risk HNSCC as well as other SCC patients, who might benefit from treatment with MEK inhibitors.

Genome-wide CNV investigation suggests a role for cadherin, Wnt, and p53 pathways in primary open-angle glaucoma

BACKGROUND

To investigate whether copy number variations (CNVs) are implicated in molecular mechanisms underlying primary open-angle glaucoma (POAG), we used genotype data of POAG individuals and healthy controls from two case-control studies, AGS (n = 278) and GLGS-UGLI (n = 1292). PennCNV, QuantiSNP, and cnvPartition programs were used to detect CNV. Stringent quality controls at both sample and marker levels were applied. The identified CNVs were intersected in CNV region (CNVR). After, we performed burden analysis, CNV-genome-wide association analysis, gene set overrepresentation and pathway analysis. In addition, in human eye tissues we assessed the expression of the genes lying within significant CNVRs.

RESULTS

We reported a statistically significant greater burden of CNVs in POAG cases compared to controls (p-value = 0,007). In common between the two cohorts, CNV-association analysis identified statistically significant CNVRs associated with POAG that span 11 genes (APC, BRCA2, COL3A1, HLA-DRB1, HLA-DRB5, HLA-DRB6, MFSD8, NIPBL, SCN1A, SDHB, and ZDHHC11). Functional annotation and pathway analysis suggested the involvement of cadherin, Wnt signalling, and p53 pathways.

CONCLUSIONS

Our data suggest that CNVs may have a role in the susceptibility of POAG and they can reveal more information on the mechanism behind this disease. Additional genetic and functional studies are warranted to ascertain the contribution of CNVs in POAG.

Establishment of a Plasticity-Associated Risk Model Based on a SOX2- and SOX9-Related Gene Set in Head and Neck Squamous Cell Carcinoma

Recent studies highlighted SOX2 and SOX9 as key determinants for cancer-cell plasticity and demonstrated that cisplatin-induced adaptation in oral squamous cell carcinoma (SCC) is acquired by an inverse regulation of both transcription factors. However, the association between SOX2/SOX9-related genetic programs with risk factors and genetic or epigenetic alterations in primary head and neck SCC (HNSCC), and their prognostic value is largely unknown.Here, we identified differentially-expressed genes (DEG) related to SOX2 and SOX9 transcription in The Cancer Genome Atlas (TCGA)-HNSC, which enable clustering of patients into groups with distinct clinical features and survival. A prognostic risk model was established by LASSO Cox regression based on expression patterns of DEGs in TCGA-HNSC (training cohort), and was confirmed in independent HNSCC validation cohorts as well as other cancer cohorts from TCGA. Differences in the mutational landscape among risk groups of TCGA-HNSC demonstrated an enrichment of truncating NSD1 mutations for the low-risk group and elucidated DNA methylation as modulator of SOX2 expression. Gene set variation analysis (GSVA) revealed differences in several oncogenic pathways among risk groups, including upregulation of gene sets related to oncogenic KRAS signaling for the high-risk group. Finally, in silico drug screen analysis revealed numerous compounds targeting EGFR signaling with significantly lower efficacy for cancer cell lines with a higher risk phenotype, but also indicated potential vulnerabilities. IMPLICATIONS: The established risk model identifies patients with primary HNSCC, but also other cancers at a higher risk for treatment failure, who might benefit from a therapy targeting SOX2/SOX9-related gene regulatory and signaling networks.

Copy Number Analysis Reveal Genetic Risks of Penile Cancer

Objectives

To evaluate copy number alterations (CNAs) in genes associated with penile cancer (PeC) and determine their correlation and prognostic ability with PeC.

Methods

Whole-exome sequencing was performed for tumor tissue and matched normal DNA of 35 patients diagnosed with penile squamous cell carcinoma from 2011 to 2016. Somatic CNAs were detected using the Genome Analysis Toolkit (GATK). Retrospective clinical data were collected and analyzed. All the data were statistically analyzed using SPSS 16.0 software. The cancer-specific survival rates were estimated by Kaplan-Meier curves and compared with the log-rank test.

Results

CNAs in the MYCN gene was detected in 19 (amplification: 54.29%) patients. Other CNAs gene targets were FAK (amplification: 45.72%, deletion: 8.57%), TP53 (amplification: 2.86%, deletion: 51.43%), TRKA (amplification: 34.29%, deletion: 2.86%), p75NTR (amplification: 5.71%, deletion: 42.86%), Miz-1 (amplification: 14.29%, deletion: 20.00%), Max (amplification: 17.14%, deletion: 2.86%), Bmi1 (amplification:14.29%, deletion: 48.57%), and MDM2 (amplification: 5.71%, deletion: 45.72%). The CNAs in MYCN and FAK correlated significantly with patient prognosis (P<0.05). The 3-year Recurrence-free survival rate was 87.10% among patients followed up. The 5-year survival rate of patients with MYCN amplification was 69.2%, compared to 94.4% in the non-amplification group. The 5-year survival rate of patients with FAK amplification was 65.6%, compared to 94.7% in the non-amplification group. The PPI network showed that TP53 and MYCN might play meaningful functional roles in PeC.

Conclusion

MYCN and FAK amplification and TP53 deletion were apparent in PeC. MYCN and TP53 were hub genes in PeC. MYCN and FAK amplification was also detected and analyzed, and the findings indicated that these two genes are predictors of poor prognosis in PeC.

Inflammatory Breast Cancer: Clinical Implications of Genomic Alterations and Mutational Profiling

Simple Summary

Inflammatory breast cancer (IBC) is an aggressive disease with high mortality rates. Nowadays, there is no targeted treatment for this tumor type. Based on this context, we investigated the molecular profile of this disease by using well-established methodologies (high-resolution microarray platform, targeted next-generation sequencing, and immunohistochemistry) that have proven potential to unveil cancer biomarkers. We found alterations related to IBC aggressiveness and metastasis (gains of MDM4, losses of CHL1, and high homologous recombination deficiency scores), and worse overall survival (variants in HR and mismatch repair genes). We also compared the mutational profiling of our cases with literature data, which includes both non-IBC and IBC cases, validating our findings. Overall, we describe genetic alterations with the potential to be used as prognostic or predictive biomarkers and ultimately improve IBC patients’ care.

Abstract

Inflammatory breast cancer (IBC) is a rare and aggressive type of breast cancer whose molecular basis is poorly understood. We performed a comprehensive molecular analysis of 24 IBC biopsies naïve of treatment, using a high-resolution microarray platform and targeted next-generation sequencing (105 cancer-related genes). The genes more frequently affected by gains were MYC (75%) and MDM4 (71%), while frequent losses encompassed TP53 (71%) and RB1 (58%). Increased MYC and MDM4 protein expression levels were detected in 18 cases. These genes have been related to IBC aggressiveness, and MDM4 is a potential therapeutic target in IBC. Functional enrichment analysis revealed genes associated with inflammatory regulation and immune response. High homologous recombination (HR) deficiency scores were detected in triple-negative and metastatic IBC cases. A high telomeric allelic imbalance score was found in patients having worse overall survival (OS). The mutational profiling was compared with non-IBC (TCGA, n = 250) and IBC (n = 118) from four datasets, validating our findings. Higher frequency of TP53 and BRCA2 variants were detected compared to non-IBC, while PIKC3A showed similar frequency. Variants in mismatch repair and HR genes were associated with worse OS. Our study provided a framework for improved diagnosis and therapeutic alternatives for this aggressive tumor type.

Genomic and Transcriptomic Characterisation of Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

Standard treatment for locally advanced rectal cancer (LARC) is neoadjuvant chemoradiotherapy (NACRT), followed by surgical resection. However, >70% of patients do not achieve a complete pathological response and have higher rates of relapse and death. There are no validated pre- or on-treatment factors that predict response to NACRT besides tumour stage and size. We characterised the response of 33 LARC patients to NACRT, collected tumour samples from patients prior to, during and after NACRT, and performed whole exome, transcriptome and high-depth targeted sequencing. The pre-treatment LARC genome was not predictive of response to NACRT. However, in line with the increasing recognition of microbial influence in cancer, RNA analysis of pre-treatment tumours suggested a greater abundance of Fusobacteria in intermediate and poor responders. In addition, we investigated tumour heterogeneity and evolution in response to NACRT. While matched pre-treatment, on-treatment and post-treatment tumours revealed minimal genome evolution overall, we identified cases in which microsatellite instability developed or was selected for during NACRT. Recent research has suggested a role for adaptive mutability to targeted therapy in colorectal cancer cells. We provide preliminary evidence of selection for mismatch repair deficiency in response to NACRT. Furthermore, pre-NACRT genomic landscapes do not predict treatment response but pre-NACRT microbiome characteristics may be informative.

Integrative Analysis of Multi-omics Data Identified EGFR and PTGS2 as Key Nodes in a Gene Regulatory Network Related to Immune Phenotypes in Head and Neck Cancer

PURPOSE

Malignant progression exhibits a tightly orchestrated balance between immune effector response and tolerance. However, underlying molecular principles that drive the establishment and maintenance of the tumor immune phenotype remain to be elucidated.

EXPERIMENTAL DESIGN

We trained a novel molecular classifier based on immune cell subsets related to programmed death-ligand 1 (PD-L1) and interferon γ (IFNγ) expression, which revealed distinct subgroups with higher (cluster A) or lower (subcluster B3) cytotoxic immune phenotypes. Integrative analysis of multi-omics data was conducted to identify differences in genetic and epigenetic landscapes as well as their impact on differentially expressed genes (DEG) among immune phenotypes. A prognostic gene signature for immune checkpoint inhibition (ICI) was established by a least absolute shrinkage and selection operator (LASSO)-Cox regression model.

RESULTS

Mutational landscape analyses unraveled a higher frequency of CASP8 somatic mutations in subcluster A1, while subcluster B3 exhibited a characteristic pattern of copy-number alterations affecting chemokine signaling and immune effector response. The integrative multi-omics approach identified EGFR and PTGS2 as key nodes in a gene regulatory network related to the immune phenotype, and several DEGs related to the immune phenotypes were affected by EGFR inhibition in tumor cell lines. Finally, we established a prognostic gene signature by a LASSO-Cox regression model based on DEGs between nonprogressive disease and progressive disease subgroups for ICI.

CONCLUSIONS

Our data highlight a complex interplay between genetic and epigenetic events in the establishment of the tumor immune phenotype and provide compelling experimental evidence that a patient with squamous cell carcinoma of the head and neck at higher risk for ICI treatment failure might benefit from a combination with EGFR inhibition.

CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications

Somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. Here, we developed CNApp, a web-based tool that allows a comprehensive exploration of CNAs by using purity-corrected segmented data from multiple genomic platforms. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at https://tools.idibaps.org/CNApp/.

The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome

Aneuploidy, the unbalanced state of the chromosome content, represents a hallmark of most solid tumors, including colorectal cancer. Such aneuploidies result in tumor specific genomic imbalances, which emerge in premalignant precursor lesions. Moreover, increasing levels of chromosomal instability have been observed in adenocarcinomas and are maintained in distant metastases. A number of studies have systematically integrated copy number alterations with gene expression changes in primary carcinomas, cell lines, and experimental models of aneuploidy. In fact, chromosomal aneuploidies target a number of genes conferring a selective advantage for the metabolism of the cancer cell. Copy number alterations not only have a positive correlation with expression changes of the majority of genes on the altered genomic segment, but also have effects on the transcriptional levels of genes genome-wide. Finally, copy number alterations have been associated with disease outcome; nevertheless, the translational applicability in clinical practice requires further studies. Here, we (i) review the spectrum of genetic alterations that lead to colorectal cancer, (ii) describe the most frequent copy number alterations at different stages of colorectal carcinogenesis, (iii) exemplify their positive correlation with gene expression levels, and (iv) discuss copy number alterations that are potentially involved in disease outcome of individual patients.

Increased Levels of Genomic Instability and Mutations in Homologous Recombination Genes in Locally Advanced Rectal Carcinomas

Pre-operative 5-fluoracil-based chemoradiotherapy (nCRT) is the standard treatment for patients with locally advanced rectal cancer (LARC). Patients with pathological complete response (pCR–0% of tumor cells in the surgical specimen after nCRT) have better overall survival and lower risk of recurrence in comparison with incomplete responders (pIR). Predictive biomarkers to be used for new therapeutic strategies and capable of stratifying patients to avoid overtreatment are needed. We evaluated the genomic profiles of 33 pre-treatment LARC biopsies using SNP array and targeted-next generation sequencing (tNGS). Based on the large number of identified genomic alterations, we calculated the genomic instability index (GII) and three homologous recombination deficiency (HRD) scores, which have been reported as impaired DNA repair markers. We observed high GII in our LARC cases, which was confirmed in 165 rectal cancer cases from TCGA. Patients with pCR presented higher GII compared with pIR. Moreover, a negative correlation between GII and the fraction of tumor cells remaining after surgery was observed (ρ = –0.382, P = 0.02). High HRD scores were detected in 61% of LARC, of which 70% were incomplete responders. Using tNGS (105 cancer-related genes, 13 involved in HR and 5 in mismatch repair pathways), we identified 23% of cases with mutations in HR genes, mostly in pIR cases (86% of mutated cases). In agreement, the analysis of the TCGA dataset (N = 145) revealed 21% of tumors with mutations in HR genes. The HRD scores were shown to be predictive of better response to PARP-inhibitors and platinum-based chemotherapy in breast and ovarian cancer. Our results suggest that the same strategy could be applied in a set of LARC patients with HRD. In conclusion, we identified high genomic instability in LARC, which was related to alterations in the HR pathway, especially in pIR. These findings suggest that patients with impaired HRD would clinically benefit from PARP-inhibitors and platinum-based therapy.

Comprehensive Genomic Profiling of Androgen-Receptor-Negative Canine Prostate Cancer

Canine carcinomas have been considered natural models for human diseases; however, the genomic profile of canine prostate cancers (PCs) has not been explored. In this study, 14 PC androgen-receptor-negative cases, 4 proliferative inflammatory atrophies (PIA), and 5 normal prostate tissues were investigated by array-based comparative genomic hybridization (aCGH). Copy number alterations (CNAs) were assessed using the Canine Genome CGH Microarray 4 × 44K (Agilent Technologies). Genes covered by recurrent CNAs were submitted to enrichment and cross-validation analysis. In addition, the expression levels of TP53, MDM2 and ZBTB4 were evaluated in an independent set of cases by qPCR. PC cases presented genomic complexity, while PIA samples had a small number of CNAs. Recurrent losses covering well-known tumor suppressor genes, such as ATM, BRCA1, CDH1, MEN1 and TP53, were found in PC. The in silico functional analysis showed several cancer-related genes associated with canonical pathways and interaction networks previously described in human PC. The MDM2, TP53, and ZBTB4 copy number alterations were translated into altered expression levels. A cross-validation analysis using The Cancer Genome Atlas (TCGA) database for human PC uncovered similarities between canine and human PCs. Androgen-receptor-negative canine PC is a complex disease characterized by high genomic instability, showing a set of genes with similar alterations to human cancer.