Case of multifocal glioblastoma with four fusion transcripts of ALK, FGFR2, NTRK2, and NTRK3 genes stresses the need for tumor tissue multisampling for transcriptomic analysis

Prospective trial of the Oncobox platform RNA sequencing bioinformatic analysis for personalized prescription of targeted drugs

Interrogating gene expression in tumor can identify up- and downregulated molecular targets of cancer drugs. Here we report the results of prospective clinical investigation of using RNA sequencing analysis for personalized cancer therapy. Transcriptomic profiles were analyzed using Oncobox platform that identifies altered expression of drug target genes and molecular pathways and builds a personalized rating of targeted therapeutics. Totally, 239 adult solid cancer patients were enrolled: 135 received cancer drug therapy, others received palliative treatment or radiotherapy, or died before therapy started. Oncobox recommended drugs were prescribed in 59 % of the cases receiving therapy. Otherwise, patients received non-targeted therapy or targeted therapy predicted as inefficient by Oncobox (controls). Patients in the Oncobox group were significantly pre-treated compared to controls, but we observed a longer progression-free survival (PFS) trend in the Oncobox group. Furthermore, post-hoc analysis revealed that time between biopsy collection and tumor profiling significantly impacts Oncobox predictive capacity. Excluding patient cases with biopsy obtained more than 7 months before sequencing lead to a significant difference in PFS between Oncobox and control groups with hazard ratio of 0.45 (p-value = 0.023). These results suggest that transcriptomic profiling provides clinically relevant therapeutic match and can improve disease control rate in solid cancers.

Detection of fusion events by RNA sequencing in FFPE versus freshly frozen colorectal cancer tissue samples

Gene fusion events result in chimeric proteins that are frequently found in human cancers. Specific targeted therapies are available for several types of cancer fusions including receptor tyrosine kinase gene moieties. RNA sequencing (RNAseq) can directly be used for detection of gene rearrangements in a single test, along with multiple additional biomarkers. However, tumor biosamples are usually formalin-fixed paraffin-embedded (FFPE) tissue blocks where RNA is heavily degraded, which in theory may result in decreased efficiency of fusion detection. Here, for the first time, we compared the efficacy of gene fusion detection by RNAseq for matched pairs of freshly frozen in RNA stabilizing solution (FF) and FFPE tumor tissue samples obtained from 29 human colorectal cancer patients. We detected no statistically significant difference in the number of chimeric transcripts in FFPE and FF RNAseq profiles. The known fusion KANSL1-ARL17A/B occurred with a high frequency in 69% of the patients. We also detected 93 new fusion genes not mentioned in the literature or listed in the ChimerSeq database. Among them, 11 were found in two or more patients, suggesting their potential role in carcinogenesis. Most of the fusions detected most probably represented read-through, microdeletion or local duplication events. Finally, in one patient, we detected a potentially clinically actionable in-frame fusion of LRRFIP2 and ALK genes not previously described in colorectal cancer with an intact tyrosine kinase domain that can be potentially targeted by ALK inhibitors.

Cancer fusion transcripts with human non-coding RNAs

Cancer chimeric, or fusion, transcripts are thought to most frequently appear due to chromosomal aberrations that combine moieties of unrelated normal genes. When being expressed, this results in chimeric RNAs having upstream and downstream parts relatively to the breakpoint position for the 5'- and 3'-fusion components, respectively. As many other types of cancer mutations, fusion genes can be of either driver or passenger type. The driver fusions may have pivotal roles in malignisation by regulating survival, growth, and proliferation of tumor cells, whereas the passenger fusions most likely have no specific function in cancer. The majority of research on fusion gene formation events is concentrated on identifying fusion proteins through chimeric transcripts. However, contemporary studies evidence that fusion events involving non-coding RNA (ncRNA) genes may also have strong oncogenic potential. In this review we highlight most frequent classes of ncRNAs fusions and summarize current understanding of their functional roles. In many cases, cancer ncRNA fusion can result in altered concentration of the non-coding RNA itself, or it can promote protein expression from the protein-coding fusion moiety. Differential splicing, in turn, can enrich the repertoire of cancer chimeric transcripts, e.g. as observed for the fusions of circular RNAs and long non-coding RNAs. These and other ncRNA fusions are being increasingly recognized as cancer biomarkers and even potential therapeutic targets. Finally, we discuss the use of ncRNA fusion genes in the context of cancer detection and therapy.

Clinically relevant fusion oncogenes: detection and practical implications

Mechanistically, chimeric genes result from DNA rearrangements and include parts of preexisting normal genes combined at the genomic junction site. Some rearranged genes encode pathological proteins with altered molecular functions. Those which can aberrantly promote carcinogenesis are called fusion oncogenes. Their formation is not a rare event in human cancers, and many of them were documented in numerous study reports and in specific databases. They may have various molecular peculiarities like increased stability of an oncogenic part, self-activation of tyrosine kinase receptor moiety, and altered transcriptional regulation activities. Currently, tens of low molecular mass inhibitors are approved in cancers as the drugs targeting receptor tyrosine kinase (RTK) oncogenic fusion proteins, that is, including ALK, ABL, EGFR, FGFR1-3, NTRK1-3, MET, RET, ROS1 moieties. Therein, the presence of the respective RTK fusion in the cancer genome is the diagnostic biomarker for drug prescription. However, identification of such fusion oncogenes is challenging as the breakpoint may arise in multiple sites within the gene, and the exact fusion partner is generally unknown. There is no gold standard method for RTK fusion detection, and many alternative experimental techniques are employed nowadays to solve this issue. Among them, RNA-seq-based methods offer an advantage of unbiased high-throughput analysis of only transcribed RTK fusion genes, and of simultaneous finding both fusion partners in a single RNA-seq read. Here we focus on current knowledge of biology and clinical aspects of RTK fusion genes, related databases, and laboratory detection methods.

Reclassification of TCGA Diffuse Glioma Profiles Linked to Transcriptomic, Epigenetic, Genomic and Clinical Data, According to the 2021 WHO CNS Tumor Classification

In 2021, the fifth edition of the WHO classification of tumors of the central nervous system (WHO CNS5) was published. Molecular features of tumors were directly incorporated into the diagnostic decision tree, thus affecting both the typing and staging of the tumor. It has changed the traditional approach, based solely on histopathological classification. The Cancer Genome Atlas project (TCGA) is one of the main sources of molecular information about gliomas, including clinically annotated transcriptomic and genomic profiles. Although TCGA itself has played a pivotal role in developing the WHO CNS5 classification, its proprietary databases still retain outdated diagnoses which frequently appear incorrect and misleading according to the WHO CNS5 standards. We aimed to define the up-to-date annotations for gliomas from TCGA's database that other scientists can use in their research. Based on WHO CNS5 guidelines, we developed an algorithm for the reclassification of TCGA glioma samples by molecular features. We updated tumor type and diagnosis for 828 out of a total of 1122 TCGA glioma cases, after which available transcriptomic and methylation data showed clustering features more consistent with the updated grouping. We also observed better stratification by overall survival for the updated diagnoses, yet WHO grade 3 IDH-mutant oligodendrogliomas and astrocytomas are still indistinguishable. We also detected altered performance in the previous diagnostic transcriptomic molecular biomarkers (expression of SPRY1, CRNDE and FREM2 genes and FREM2 molecular pathway) and prognostic gene signature (FN1, ITGA5, OSMR, and NGFR) after reclassification. Thus, we conclude that further efforts are needed to reconsider glioma molecular biomarkers.

Experimentally Deduced Criteria for Detection of Clinically Relevant Fusion 3′ Oncogenes from FFPE Bulk RNA Sequencing Data

Drugs targeting receptor tyrosine kinase (RTK) oncogenic fusion proteins demonstrate impressive anti-cancer activities. The fusion presence in the cancer is the respective drug prescription biomarker, but their identification is challenging as both the breakpoint and the exact fusion partners are unknown. RNAseq offers the advantage of finding both fusion parts by screening sequencing reads. Paraffin (FFPE) tissue blocks are the most common way of storing cancer biomaterials in biobanks. However, finding RTK fusions in FFPE samples is challenging as RNA fragments are short and their artifact ligation may appear in sequencing libraries. Here, we annotated RNAseq reads of 764 experimental FFPE solid cancer samples, 96 leukemia samples, and 2 cell lines, and identified 36 putative clinically relevant RTK fusions with junctions corresponding to exon borders of the fusion partners. Where possible, putative fusions were validated by RT-PCR (confirmed for 10/25 fusions tested). For the confirmed 3′RTK fusions, we observed the following distinguishing features. Both moieties were in-frame, and the tyrosine kinase domain was preserved. RTK exon coverage by RNAseq reads upstream of the junction site were lower than downstream. Finally, most of the true fusions were present by more than one RNAseq read. This provides the basis for automatic annotation of 3′RTK fusions using FFPE RNAseq profiles.

Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways

In gliomas, expression of certain marker genes is strongly associated with survival and tumor type and often exceeds histological assessments. Using a human interactome model, we algorithmically reconstructed 7494 new-type molecular pathways that are centered each on an individual protein. Each single-gene expression and gene-centric pathway activation was tested as a survival and tumor grade biomarker in gliomas and their diagnostic subgroups (IDH mutant or wild type, IDH mutant with 1p/19q co-deletion, MGMT promoter methylated or unmethylated), including the three major molecular subtypes of glioblastoma (proneural, mesenchymal, classical). We used three datasets from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, which in total include 527 glioblastoma and 1097 low grade glioma profiles. We identified 2724 such gene and 2418 pathway survival biomarkers out of total 17,717 genes and 7494 pathways analyzed. We then assessed tumor grade and molecular subtype biomarkers and with the threshold of AUC > 0.7 identified 1322/982 gene biomarkers and 472/537 pathway biomarkers. This suggests roughly two times greater efficacy of the reconstructed pathway approach compared to gene biomarkers. Thus, we conclude that activation levels of algorithmically reconstructed gene-centric pathways are a potent class of new-generation diagnostic and prognostic biomarkers for gliomas.

Transcriptomic Portraits and Molecular Pathway Activation Features of Adult Spinal Intramedullary Astrocytomas

In this study, we report 31 spinal intramedullary astrocytoma (SIA) RNA sequencing (RNA-seq) profiles for 25 adult patients with documented clinical annotations. To our knowledge, this is the first clinically annotated RNA-seq dataset of spinal astrocytomas derived from the intradural intramedullary compartment. We compared these tumor profiles with the previous healthy central nervous system (CNS) RNA-seq data for spinal cord and brain and identified SIA-specific gene sets and molecular pathways. Our findings suggest a trend for SIA-upregulated pathways governing interactions with the immune cells and downregulated pathways for the neuronal functioning in the context of normal CNS activity. In two patient tumor biosamples, we identified diagnostic KIAA1549-BRAF fusion oncogenes, and we also found 16 new SIA-associated fusion transcripts. In addition, we bioinformatically simulated activities of targeted cancer drugs in SIA samples and predicted that several tyrosine kinase inhibitory drugs and thalidomide analogs could be potentially effective as second-line treatment agents to aid in the prevention of SIA recurrence and progression.

RNA Sequencing for Personalized Treatment of Metastatic Leiomyosarcoma: Case Report

Uterine leiomyosarcoma (UL) is a rare malignant tumor that develops from the uterine smooth muscle tissue. Due to the low frequency and lack of sufficient data from clinical trials there is currently no effective treatment that is routinely accepted for UL. Here we report a case of a 65-years-old female patient with metastatic UL, who progressed on ifosfamide and doxorubicin therapy and developed severe hypertensive crisis after administration of second line pazopanib, which lead to treatment termination. Rapid progression of the tumor stressed the need for the alternative treatment options. We performed RNA sequencing and whole exome sequencing profiling of the patient's biopsy and applied Oncobox bioinformatic algorithm to prioritize targeted therapeutics. No clinically relevant mutations associated with drug efficiencies were found, but the Oncobox transcriptome analysis predicted regorafenib as the most effective targeted treatment option. Regorafenib administration resulted in a complete metabolic response which lasted for 10 months. In addition, RNA sequencing analysis revealed a novel cancer fusion transcript of YWHAE gene with fusion partner JAZF1. Several chimeric transcripts for YWHAE and JAZF1 genes were previously found in uterine neoplasms and some of them were associated with tumor prognosis. However, their combination was detected in this study for the first time. Taken together, these findings evidence that RNA sequencing may complement analysis of clinically relevant mutations and enhance management of oncological patients by suggesting putative treatment options.