The emerging roles of NGS in clinical oncology and personalized medicine

Partial remission with sintilimab monotherapy in a patient carrying a CD274 amplification in refractory diffuse large B‑cell lymphoma: A case report

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with varying characteristics, in terms of genomic variation, cell morphology and clinical presentation. At present, only ~66% of patients are cured with initial treatment and those with refractory DLBCL exhibit a poor prognosis. Thus, further investigations into novel effective treatment options for DLBCL are required. The present study reports the case of a patient resistant to multiple therapies, including rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) plus enzastaurin (trial no. CTR20171560), GemOx plus lenalidomide and selinexor (trial no. ATG-010-DLBCL-001). The patient harbored a CD274 amplification, as identified via next-generation sequencing (NGS), and exhibited a high programmed death-ligand 1 Tumor Proportion Score of up to 95%. Consequently, the patient was treated with sintilimab monotherapy and the response lasted for 12 months of follow-up without major immune-related adverse events. This case highlights the role of NGS technology in selecting treatment options for refractory DLBCL. Furthermore, the results of the present study suggest that sintilimab may have potential in the treatment of patients with refractory DLBCL.

The Third-Generation Sequencing Challenge: Novel Insights for the Omic Sciences

The understanding of the human genome has been greatly improved by the advent of next-generation sequencing technologies (NGS). Despite the undeniable advantages responsible for their widespread diffusion, these methods have some constraints, mainly related to short read length and the need for PCR amplification. As a consequence, long-read sequencers, called third-generation sequencing (TGS), have been developed, promising to overcome NGS. Starting from the first prototype, TGS has progressively ameliorated its chemistries by improving both read length and base-calling accuracy, as well as simultaneously reducing the costs/base. Based on these premises, TGS is showing its potential in many fields, including the analysis of difficult-to-sequence genomic regions, structural variations detection, RNA expression profiling, DNA methylation study, and metagenomic analyses. Protocol standardization and the development of easy-to-use pipelines for data analysis will enhance TGS use, also opening the way for their routine applications in diagnostic contexts.

Beyond traditional therapies: clinical significance of complex molecular profiling in patients with advanced solid tumours-results from a Turkish multi-centre study

OBJECTIVE

The objective of this multi-centre, real-world study was to examine the potential influence of comprehensive molecular profiling on the development of treatment decisions or adjustments for patients with advanced solid malignancies. We then evaluated the impact of these informed choices on patient treatment outcomes.

METHODS

The study encompassed 234 adult patients (mean age: 52.7 ± 14.3 years, 54.7% women) who were diagnosed with solid tumours at 21 different medical centres in Turkey. Remarkably, 67.9% of the patients exhibited metastasis at the time of diagnosis. We utilized an OncoDNA (Gosselies, Belgium) platform (OncoDEEP) integrating next-generation sequencing with additional tests to harvest complex molecular profiling data. The results were analyzed in relation with two specific outcomes: (i) the impact on therapeutic decisions, including formulation or modifications, and (ii) associated treatment response.

RESULTS

Out of the 228 patients with final molecular profiling results, 118 (50.4%) had their treatment modified, whilst the remaining 110 (47.0%) did not. The response rates were comparable, with 3.9 versus 3.4% for complete response, 13.6 versus 29.3% for partial response, 66.9 versus 51.7% for progressive disease and 15.5 versus 15.5% for stable disease for treatments informed and not informed by complex molecular profiling, respectively (P = 0.16).

CONCLUSION

Our real-world findings highlight the significant impact of complex molecular profiling on the treatment decisions made by oncologists for a substantial portion of patients with advanced solid tumours. Regrettably, no significant advantage was detected in terms of treatment response or disease control rates.

Temporal trends and regional variability in BRAF and KRAS genetic testing in Denmark (2010-2022): Implications for precision medicine

OBJECTIVE

This study aims to evaluate the developments in the testing of Kirsten Rat Sarcoma viral oncogene homolog (KRAS) and v-Raf murine sarcoma viral oncogene homolog B1 (BRAF) mutations across different cancer types and regions in Denmark from 2010 to 2022.

STUDY DESIGN AND SETTING

Using comprehensive data from the Danish health registries, we linked molecular test results from the Danish Pathology Registry with cancer diagnoses from the Danish National Patient Registry between 2010 and 2022. We assessed the frequency and distribution of KRAS and BRAF mutations across all cancer types, years of testing, and the five Danish regions.

RESULTS

The study included records of KRAS testing for 30 671 patients and BRAF testing for 30 860 patients. Most KRAS testing was performed in colorectal (78%) and lung cancer (18%), and BRAF testing in malignant melanoma (13%), colorectal cancer (67%), and lung cancer (12%). Testing rates and documentation mutational subtypes increased over time. Reporting of wildtype results varied between lung and colorectal cancer, with underreporting in lung cancer. Regional variations in testing and reporting were observed.

CONCLUSION

Our study highlights substantial progress in KRAS and BRAF testing in Denmark from 2010 to 2022, evidenced by increased and more specific reporting of mutational test results, thereby improving the precision of cancer diagnosis and treatment. However, persistent regional variations and limited testing for cancer types beyond melanoma, colorectal, and lung cancer highlight the necessity for a nationwide assessment of the optimal testing approach.

Current treatment and novel insights regarding ROS1-targeted therapy in malignant tumors

BACKGROUND

The proto-oncogene ROS1 encodes an intrinsic type I membrane protein of the tyrosine kinase/insulin receptor family. ROS1 facilitates the progression of various malignancies via self-mutations or rearrangements. Studies on ROS1-directed tyrosine kinase inhibitors have been conducted, and some have been approved by the FDA for clinical use. However, the adverse effects and mechanisms of resistance associated with ROS1 inhibitors remain unknown. In addition, next-generation ROS1 inhibitors, which have the advantage of treating central nervous system metastases and alleviating endogenous drug resistance, are still in the clinical trial stage.

METHOD

In this study, we searched relevant articles reporting the mechanism and clinical application of ROS1 in recent years; systematically reviewed the biological mechanisms, diagnostic methods, and research progress on ROS1 inhibitors; and provided perspectives for the future of ROS1-targeted therapy.

RESULTS

ROS1 is most expressed in malignant tumours. Only a few ROS1 kinase inhibitors are currently approved for use in NSCLC, the efficacy of other TKIs for NSCLC and other malignancies has not been ascertained. There is no effective standard treatment for adverse events or resistance to ROS1-targeted therapy. Next-generation TKIs appear capable of overcoming resistance and delaying central nervous system metastasis, but with a greater incidence of adverse effects.

CONCLUSIONS

Further research on next-generation TKIs regarding the localization of ROS1 and its fusion partners, binding sites for targeted drugs, and coadministration with other drugs is required. The correlation between TKIs and chemotherapy or immunotherapy in clinical practice requires further study.

Assessing the complementary information from an increased number of biologically relevant features in liquid biopsy-derived RNA-Seq data

Liquid biopsy-derived RNA sequencing (lbRNA-seq) exhibits significant promise for clinic-oriented cancer diagnostics due to its non-invasiveness and ease of repeatability. Despite substantial advancements, obstacles like technical artefacts and process standardisation impede seamless clinical integration. Alongside addressing technical aspects such as normalising fluctuating low-input material and establishing a standardised clinical workflow, the lack of result validation using independent datasets remains a critical factor contributing to the often low reproducibility of liquid biopsy-detected biomarkers. Considering the outlined drawbacks, our objective was to establish a workflow/methodology characterised by: 1. Harness the rich diversity of biological features accessible through lbRNA-seq data, encompassing a holistic range of molecular and functional attributes. These components are seamlessly integrated via a Machine Learning-based Ensemble Classification framework, enabling a unified and comprehensive analysis of the intricate information encoded within the data. 2. Implementing and rigorously benchmarking intra-sample normalisation methods to heighten their relevance within clinical settings. 3. Thoroughly assessing its efficacy across independent test sets to ascertain its robustness and potential utility. Using ten datasets from several studies comprising three different sources of biological material, we first show that while the best-performing normalisation methods depend strongly on the dataset and coupled Machine Learning method, the rather simple Counts Per Million method is generally very robust, showing comparable performance to cross-sample methods. Subsequently, we demonstrate that the innovative biofeature types introduced in this study, such as the Fraction of Canonical Transcript, harbour complementary information. Consequently, their inclusion consistently enhances prediction power compared to models relying solely on gene expression-based biofeatures. Finally, we demonstrate that the workflow is robust on completely independent datasets, generally from different labs and/or different protocols. Taken together, the workflow presented here outperforms generally employed methods in prediction accuracy and may hold potential for clinical diagnostics application due to its specific design.

Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the approach to cancer research. Applications of NGS include the identification of tumor specific alterations that can influence tumor pathobiology and also impact diagnosis, prognosis and therapeutic options. Pharmacogenomics (PGx) studies the role of inheritance of individual genetic patterns in drug response and has taken advantage of NGS technology as it provides access to high-throughput data that can, however, be difficult to manage. Machine learning (ML) has recently been used in the life sciences to discover hidden patterns from complex NGS data and to solve various PGx problems. In this review, we provide a comprehensive overview of the NGS approaches that can be employed and the different PGx studies implicating the use of NGS data. We also provide an excursus of the ML algorithms that can exert a role as fundamental strategies in the PGx field to improve personalized medicine in cancer.

An update on pharmacotherapies for colorectal cancer: 2023 and beyond

INTRODUCTION

Colorectal cancer (CRC) is one of the most prevalent and lethal cancers worldwide. The treatment of metastatic colorectal cancer (mCRC) is difficult, and mCRC has a survival rate of only 13-17% compared with 70-90% in locoregional CRC. There is ongoing research effort on pharmacotherapy for CRC to improve the treatment outcome.

AREAS COVERED

We reviewed the current literature and ongoing clinical trials on CRC pharmacotherapy, with a focus on targeted therapy based on the results of genetic testing. The pharmacotherapies covered in this article include novel agents targeting EGFR and EGFR-related pathways, agents targeting the VEGF pathway, immunotherapy options depending on the MMR/MSI status, and new therapies targeting genetic fusions such as NTRK. We also briefly discuss the value of next-generation sequencing (NGS) in treatment selection and response monitoring.

EXPERT OPINION

We advocate for the early and routine use of NGS to genetically characterize CRC to assist with pharmacotherapy selection. Targeted therapy is a promising field of ongoing research and improves CRC treatment outcome.

Molecular profiling in cholangiocarcinoma: A practical guide to next-generation sequencing

Cholangiocarcinomas (CCA) are a heterogeneous group of tumors that are classified as intrahepatic, perihilar, or distal according to the anatomic location within the biliary tract. Each CCA subtype is associated with distinct genomic alterations, including single nucleotide variants, copy number variants, and chromosomal rearrangements or gene fusions, each of which can influence disease prognosis and/or treatment outcomes. Molecular profiling using next-generation sequencing (NGS) is a powerful technique for identifying unique gene variants carried by an individual tumor, which can facilitate their accurate diagnosis as well as promote the optimal selection of gene variant-matched targeted treatments. NGS is particularly useful in patients with CCA because between one-third and one-half of these patients have genomic alterations that can be targeted by drugs that are either approved or in clinical development. NGS can also provide information about disease evolution and secondary resistance alterations that can develop during targeted therapy, and thus facilitate assessment of prognosis and choice of alternative targeted treatments. Pathologists play a critical role in assessing the viability of biopsy samples for NGS, and advising treating clinicians whether NGS can be performed and which of the available platforms should be used to optimize testing outcomes. This review aims to provide clinical pathologists and other healthcare professionals with practical step-by-step guidance on the use of NGS for molecular profiling of patients with CCA, with respect to tumor biopsy techniques, pre-analytic sample preparation, selecting the appropriate NGS panel, and understanding and interpreting results of the NGS test.

Comprehensive next-generation sequencing reveals double primary colorectal carcinoma missed by diagnostic imaging: A case report

BACKGROUND

Multiple primary colorectal carcinoma (MPCC) is a rare clinical disease, which is challenging to differentiate from metastatic disease using histopathological methods. Next-generation sequencing (NGS) has been employed to identify multiple primary cancers.

CASE SUMMARY

This study a rare case of a 63-year-old male patient diagnosed with MPCC by targeted NGS, which was initially missed by radiological evaluation. The patient was found to have two tumors located on the surface of the colorectum which had distinct genomic alterations. Based on wild-type KRAS detected in the unresected tumor, the patient benefited from the epidermal growth factor receptor (EGFR) inhibitor cetuximab treatment, but developed novel mutations including KIF5B-RET fusion, which provides a possible resistance mechanism to anti-EGFR therapy.

CONCLUSION

Our case highlights the necessity of using genetic testing for primary tumor diagnosis and the application of serial plasma circulating tumor DNA profiling for dynamic disease monitoring.

Diagnostics and treatment of ovarian cancer in the era of precision medicine - opportunities and challenges

Due to predictions of increasing incidences and deaths from ovarian cancer, this neoplasm is a challenge for modern health care. The advent of NGS technology has made it possible to understand the molecular characteristics of many cancers, including ovarian cancer. The data obtained in research became the basis for the development of molecularly targeted therapies thus leading to the entry of NGS analysis into the diagnostic process of oncological patients. This review presents targeted therapies currently in preclinical or clinical trials, whose promising results offer hope for their use in clinical practice in the future. As more therapeutic options emerge, it will be necessary to modify molecular diagnostic regimens to select the best treatment for a given patient. New biomarkers are needed to predict the success of planned therapy. An important aspect of public health is molecular testing in women with a familial predisposition to ovarian cancer enabling patients to be included in prevention programs. NGS technology, despite its high throughput, poses many challenges, from the quality of the diagnostic material used for testing to the interpretation of results and classification of sequence variants. The article highlights the role of molecular testing in ongoing research and also its role in the diagnostic and therapeutic process in the era of personalized medicine. The spread of genetic testing in high-risk groups, the introduction of more targeted therapies and also the possibility of agnostic therapies could significantly improve the health situation for many women worldwide.

Next-Generation Sequencing of Breast Cancer in the Neoadjuvant Setting

INTRODUCTION

Many patients with locally advanced breast cancer are proposed to neoadjuvant chemotherapy (NAT) before surgery. Only some of them achieve a pathological complete response (pCR). The determination of gene somatic alterations using next-generation sequencing (NGS) in the non-pCR tumors is important, in order to identify potential opportunities of treatment for the patients, if targeted therapies are available.

METHODS

Breast cancer tissue samples of 31 patients, collected before NAT, were analyzed by NGS using the Oncomine™ Comprehensive Assay Plus (OCA-Plus) panel.

RESULTS

Twelve patients achieved pCR after NAT. ERBB2 gene alterations were the most frequent in this cohort of pCR patients, followed by BRCA 1 and 2, MYC, TP53, PIK3CA, and MET alterations. Tumors that did not achieve a pCR were mainly triple negative. In this subgroup some BRCA 1 and 2 and PIK3CA gene alterations were identified, as well as TP53 mutations. The NGS panel employed in this study also allowed for the determination of tumor mutation burden (TMB).

CONCLUSION

This study showcases the significance of employing comprehensive genomic testing in breast cancer cases, primarily due to the scarcity of specific target assays. The detection of somatic mutations, coupled with the availability of targeted therapies, holds promise as a potential therapeutic avenue to enhance tumor response rates during NAT, or as a complementary treatment following surgery. Moreover, evaluating the TMB in non-pCR samples could serve as a valuable criterion for selecting patients suitable for immunotherapy. Further exploration through clinical trials is imperative to investigate these prospects.

miRNA-Seq Tissue Diagnostic Signature: A Novel Model for NSCLC Subtyping

Non-small cell lung cancer (NSCLC) encompasses distinct histopathological subtypes, namely adenocarcinoma (AC) and squamous cell lung carcinoma (SCC), which require precise differentiation for effective treatment strategies. In this study, we present a novel molecular diagnostic model that integrates tissue-specific expression profiles of microRNAs (miRNAs) obtained through next-generation sequencing (NGS) to discriminate between AC and SCC subtypes of NSCLC. This approach offers a more comprehensive and precise molecular characterization compared to conventional methods such as histopathology or immunohistochemistry. Firstly, we identified 31 miRNAs with significant differential expression between AC and SCC cases. Subsequently, we constructed a 17-miRNA signature through rigorous multistep analyses, including LASSO/elastic net regression. The signature includes both upregulated miRNAs (hsa-miR-326, hsa-miR-450a-5p, hsa-miR-1287-5p, hsa-miR-556-5p, hsa-miR-542-3p, hsa-miR-30b-5p, hsa-miR-4728-3p, hsa-miR-450a-1-3p, hsa-miR-375, hsa-miR-147b, hsa-miR-7705, and hsa-miR-653-3p) and downregulated miRNAs (hsa-miR-944, hsa-miR-205-5p, hsa-miR-205-3p, hsa-miR-149-5p, and hsa-miR-6510-3p). To assess the discriminative capability of the 17-miRNA signature, we performed receiver operating characteristic (ROC) curve analysis, which demonstrated an impressive area under the curve (AUC) value of 0.994. Our findings highlight the exceptional diagnostic performance of the miRNA signature as a stratifying biomarker for distinguishing between AC and SCC subtypes in lung cancer. The developed molecular diagnostic model holds promise for providing a more accurate and comprehensive molecular characterization of NSCLC, thereby guiding personalized treatment decisions and improving clinical management and prognosis for patients.

Cross-platform comparisons for targeted bisulfite sequencing of MGISEQ-2000 and NovaSeq6000

BACKGROUND

An accurate and reproducible next-generation sequencing platform is essential to identify malignancy-related abnormal DNA methylation changes and translate them into clinical applications including cancer detection, prognosis, and surveillance. However, high-quality DNA methylation sequencing has been challenging because poor sequence diversity of the bisulfite-converted libraries severely impairs sequencing quality and yield. In this study, we tested MGISEQ-2000 Sequencer's capability of DNA methylation sequencing with a published non-invasive pancreatic cancer detection assay, using NovaSeq6000 as the benchmark.

RESULTS

We sequenced a series of synthetic cell-free DNA (cfDNA) samples with different tumor fractions and found MGISEQ-2000 yielded data with similar quality as NovaSeq6000. The methylation levels measured by MGISEQ-2000 demonstrated high consistency with NovaSeq6000. Moreover, MGISEQ-2000 showed a comparable analytic sensitivity with NovaSeq6000, suggesting its potential for clinical detection. As to evaluate the clinical performance of MGISEQ-2000, we sequenced 24 clinical samples and predicted the pathology of the samples with a clinical diagnosis model, PDACatch classifier. The clinical model performance of MGISEQ-2000's data was highly consistent with that of NovaSeq6000's data, with the area under the curve of 1. We also tested the model's robustness with MGISEQ-2000's data when reducing the sequencing depth. The results showed that MGISEQ-2000's data showed matching robustness of the PDACatch classifier with NovaSeq6000's data.

CONCLUSIONS

Taken together, MGISEQ-2000 demonstrated similar data quality, consistency of the methylation levels, comparable analytic sensitivity, and matching clinical performance, supporting its application in future non-invasive early cancer detection investigations by detecting distinct methylation patterns of cfDNAs.

Identification of five novel variants of ADAR1 in dyschromatosis symmetrica hereditaria by next-generation sequencing

Background

Dyschromatosis symmetrica hereditaria (DSH) is a rare autosomal dominant inherited pigmentary dermatosis characterized by a mixture of hyperpigmented and hypopigmented freckles on the dorsal aspect of the distal extremities. To date, pathogenic mutations causing DSH have been identified in the adenosine deaminase acting on RNA1 gene (ADAR1), which is mapped to chromosome 1q21.

Objective

The present study aimed to investigate the underlying pathological mechanism in 14 patients with DSH from five unrelated Chinese families. Next-generation sequencing (NGS) and direct sequencing were performed on a proband with DSH to identify causative mutations. All coding, adjacent intronic, and 5'- and 3'-untranslated regions of ADAR1 were screened, and variants were identified.

Result

These mutations consisted of three missense mutations (NM_001025107: c.716G>A, NM_001111.5: c.3384G>C, and NM_001111.5: c.3385T>G), one nonsense mutation (NM_001111.5:c.511G>T), and one splice-site mutation (NM_001111.5: c.2080-1G>T) located in exon 2, exon 14, and the adjacent intronic region according to recommended Human Genome Variation Society (HGVS) nomenclature. Moreover, using polymerase chain reaction and Sanger sequencing, we identified five novel ADAR1 variants, which can be predicted to be pathogenic by in silico genome sequence analysis. Among the mutations, the missense mutations had no significant effect on the spatial structure of the protein, while the stop codon introduced by the nonsense mutation truncated the protein.

Conclusion

Our results highlighted that the advent of NGS has facilitated high-throughput screening for the identification of disease-causing mutations with high accuracy, stability, and specificity. Five novel genetic mutations were found in five unrelated families, thereby extending the pathogenic mutational spectrum of ADAR1 in DSH and providing new insights into this complex genetic disorder.

Protein Profiling in Human Papillomavirus-Associated Cervical Carcinogenesis: Cornulin as a Biomarker for Disease Progression

Nearly 90% of cervical cancers are linked to human papillomavirus (HPV). Uncovering the protein signatures in each histological phase of cervical oncogenesis provides a path to biomarker discovery. The proteomes extracted from formalin-fixed paraffin-embedded tissues of the normal cervix, HPV16/18-associated squamous intraepithelial lesion (SIL), and squamous cell carcinoma (SCC) were compared using liquid chromatography-mass spectrometry (LC-MS). A total of 3597 proteins were identified, with 589, 550, and 1570 proteins unique to the normal cervix, SIL, and SCC groups, respectively, while 332 proteins overlapped between the three groups. In the transition from normal cervix to SIL, all 39 differentially expressed proteins were downregulated, while all 51 proteins discovered were upregulated in SIL to SCC. The binding process was the top molecular function, while chromatin silencing in the SIL vs. normal group, and nucleosome assembly in SCC vs. SIL groups was the top biological process. The PI3 kinase pathway appears crucial in initiating neoplastic transformation, while viral carcinogenesis and necroptosis are important for cell proliferation, migration, and metastasis in cervical cancer development. Annexin A2 and cornulin were selected for validation based on LC-MS results. The former was downregulated in the SIL vs. normal cervix and upregulated in the progression from SIL to SCC. In contrast, cornulin exhibited the highest expression in the normal cervix and lowest in SCC. Although other proteins, such as histones, collagen, and vimentin, were differentially expressed, their ubiquitous expression in most cells precluded further analysis. Immunohistochemical analysis of tissue microarrays found no significant difference in Annexin A2 expression between the groups. Conversely, cornulin exhibited the strongest expression in the normal cervix and lowest in SCC, supporting its role as a tumor suppressor and potential biomarker for disease progression.

The upregulation of CLGN in hepatocellular carcinoma is potentially regulated by hsa-miR-194-3p and associated with patient progression

Background

Patients with hepatocellular carcinoma (HCC) have poor prognosis, especially in advanced stages. Targeted therapy is the main treatment for advanced HCC patients, but the optimal targets for HCC remain poorly understood. The main purpose of this study was to identify potential novel prognostic markers and therapeutic targets.

Methods

Firstly, differentially expressed genes (DEGs) in HCC were identified from the Gene Expression Omnibus (GEO) database. The expression, significance in prognosis, and potential mechanisms of DEGs were analyzed using GEPIA, TIMER, HPA, Kaplan Meier Plotter, CBioPortal, miRWalk, TargetScan, and ENCORI databases. Immunohistochemical staining was used to determine the protein expression levels of potential candidate genes.

Results

The mRNA levels of MND1, STXBP6, and CLGN were significantly increased in HCC (p< 0.01). HCC patients with elevated CLGN mRNA levels had poorer overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and disease-specific survival (DSS) (p < 0.05). Higher MND1 mRNA levels significantly correlated with poorer DFS in HCC patients (p< 0.05). However, there was no significant correlation between STXBP6 expression and prognosis of HCC (p> 0.05). Further analysis revealed that patients with elevated CLGN mRNA expression in advanced pathology stages had poorer prognosis (p< 0.01). In addition, CLGN protein levels were elevated in HCC compared to their levels in normal tissues. The mRNA levels of CLGN had no significant correlation with the abundance of six common tumor infiltrating lymphocytes in HCC (COR < 0.5). Moreover, the mutation rate of CLGN was less than 1% in HCC patients (10/1089). Finally, the expression level of hsa-miR-194-3p in HCC was significantly lower than that in normal tissues (p < 0.05), and prognosis of HCC with low expression of hsa-miR-194 was poor (p < 0.05).

Conclusion

The upregulation of CLGN in HCC is significantly associated with poor patient prognosis, especially in the advanced stages, and may be regulated by hsa-miR-194-3p. These findings suggest that CLGN may be closely related to the progression of HCC, and is a potential therapeutic target and prognostic indicator for patients with advanced HCC.

Dual NGS Comparative Analysis of Liquid Biopsy (LB) and Formalin-Fixed Paraffin-Embedded (FFPE) Samples of Non-Small Cell Lung Carcinoma (NSCLC)

Lung cancer ranks second worldwide after breast cancer and third in Europe after breast and colorectal cancers when both sexes and all ages are considered. In this context, the aim of this study was to emphasize the power of dual analysis of the molecular profile both in tumor tissue and plasma by NGS assay as a liquid biopsy approach with impact on prognosis and therapy modulation in NSCLC patients. NGS analysis was performed both from tissue biopsies and from cfNAs isolated from peripheral blood samples. Out of all 29 different mutations detectable by both NGS panels (plasma and tumor tissue), seven different variants (24.13%; EGFR L858R in two patients, KRAS G13D and Q61H and TP53 G244D, V197M, R213P, and R273H) were detected only in plasma and not in the tumor itself. These mutations were detected in seven different patients, two of them having known distant organ metastasis. Our data show that NGS analysis of cfDNA could identify actionable mutations in advanced NSCLC and, therefore, this analysis could be used to monitor the disease progression and the treatment response and even to modulate the therapy in real time.

From Samples to Germline and Somatic Sequence Variation: A Focus on Next-Generation Sequencing in Melanoma Research

Next-generation sequencing (NGS) applications have flourished in the last decade, permitting the identification of cancer driver genes and profoundly expanding the possibilities of genomic studies of cancer, including melanoma. Here we aimed to present a technical review across many of the methodological approaches brought by the use of NGS applications with a focus on assessing germline and somatic sequence variation. We provide cautionary notes and discuss key technical details involved in library preparation, the most common problems with the samples, and guidance to circumvent them. We also provide an overview of the sequence-based methods for cancer genomics, exposing the pros and cons of targeted sequencing vs. exome or whole-genome sequencing (WGS), the fundamentals of the most common commercial platforms, and a comparison of throughputs and key applications. Details of the steps and the main software involved in the bioinformatics processing of the sequencing results, from preprocessing to variant prioritization and filtering, are also provided in the context of the full spectrum of genetic variation (SNVs, indels, CNVs, structural variation, and gene fusions). Finally, we put the emphasis on selected bioinformatic pipelines behind (a) short-read WGS identification of small germline and somatic variants, (b) detection of gene fusions from transcriptomes, and (c) de novo assembly of genomes from long-read WGS data. Overall, we provide comprehensive guidance across the main methodological procedures involved in obtaining sequencing results for the most common short- and long-read NGS platforms, highlighting key applications in melanoma research.

Identification of immune-related signature for the prognosis and benefit of immunotherapy in triple-negative breast cancer

Background: There is a lack of biomarkers for predicting the efficacy of immunotherapy in triple-negative breast cancer (TNBC). Hence, we constructed an immune risk score (IRS) model to predict the prognosis of patients with TNBC and evaluate those who are sensitive to immunotherapy. Methods: The ribonucleic acid (RNA) sequencing data, mutation data, and clinical information of TNBC patients were obtained from The Cancer Genome Atlas database. Data of immune-related genes were obtained from the Import and InnateDB databases. The IRS model was constructed using univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses, and the predictive ability of the prognostic model was evaluated. Further external validation was performed using the Gene Expression Omnibus (GEO) databases GSE58812 and GSE135565. Data on the clinical characteristics, immune landscape, and immune checkpoint inhibitors used in different risk groups were analyzed. Finally, the drug sensitivity of the patients in the high- and low-risk groups was predicted. Results: The prognostic risk score model comprised six genes: HSPA6, LCN1, ARTN, IL36G, BCL2A1, and CASP12. The area under the curve values at 1 year, 3 years, and 5 years were 0.835, 0.852, and 0.843, respectively, indicating that the model has a good potential for predicting the long-term survival of TNBC patients, which is consistent with the results of the GEO cohort. Compared with the high-risk group, the low-risk group had a better prognosis; more abundant immune-activated cell infiltrates, such as CD8+ T cells and CD4 memory-activated T cells, and a higher enrichment of immune-related signaling pathways, such as the cytokine receptor interaction, nucleotide oligomerization domain-like receptor signal pathway, T-cell receptor signal pathway, and B-cell receptor signaling pathway, were observed. In addition, the immune checkpoint encoding genes, such as CD274, CTLA4, PDCD1, and PDCD1LG2 were highly expressed in the low-risk group, which showed that this group was more likely to benefit from immunotherapy. Conclusion: A new IRS gene feature was established to predict the patients' prognosis and guide immunotherapy. Moreover, it was revealed that several potential therapeutic drugs can be used in high-risk patients who are unresponsive to immunotherapy.

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice

The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient’s tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD).

A performance evaluation study: Variant annotation tools - The enigma of clinical next generation sequencing (NGS) based genetic testing

Dramatically expanding our ability for clinical genetic testing for inherited conditions and complex diseases such as cancer, next generation sequencing (NGS) technologies are allowing for rapid interrogation of thousands of genes and identification of millions of variants. Variant annotation, the process of assigning functional information to DNA variants based on the standardized Human Genome Variation Society (HGVS) nomenclature, is a fundamental challenge in the analysis of NGS data that has led to the development of many bioinformatic algorithms. In this study, we evaluated the performance of 3 variant annotation tools: Alamut® Batch, Ensembl Variant Effect Predictor (VEP), and ANNOVAR, benchmarked by a manually curated ground-truth set of 298 variants from the medical exome database at the Molecular Diagnostics Laboratory at Lurie Children's Hospital. Of the 3 tools, VEP produces the most accurate variant annotations (HGVS nomenclature for 297 of the 298 variants) due to usage of updated gene transcript versions within the algorithm. Alamut® Batch called 296 of the 298 variants correctly; strikingly, ANNOVAR exhibited the greatest number of discrepancies (20 of the 298 variants, 93.3% concordance with ground-truth set). Adoption of validated methods of variant annotation is critical in post-analytical phases of clinical testing.