Cancer diagnostics: The journey from histomorphology to molecular profiling

Acute myeloid leukemia with a novel AKAP9::PDGFRA fusion transformed from essential thrombocythemia: A case report and mini review

Acute myeloid leukemia (AML) is a heterogeneous hematological malignancy associated with various combinations of gene mutations, epigenetic abnormalities, and chromosome rearrangement-related gene fusions. Despite the significant degree of heterogeneity in its pathogenesis, many gene fusions and point mutations are recurrent in AML and have been employed in risk stratification over the last several decades. Gene fusions have long been recognized for understanding tumorigenesis and their proven roles in clinical diagnosis and targeted therapies. Advances in DNA sequencing technologies and computational biology have contributed significantly to the detection of known fusion genes as well as for the discovery of novel ones. Several recurring gene fusions in AML have been linked to prognosis, treatment response, and disease progression. In this report, we present a case with a long history of essential thrombocythemia and hallmark CALR mutation transforming to AML characterized by a previously unreported AKAP9::PDGFRA fusion gene. We propose mechanisms by which this fusion may contribute to the pathogenesis of AML and its potential as a molecular target for tyrosine kinase inhibitors.

LASSO regression and WGCNA-based telomerase-associated lncRNA signaling predicts clear cell renal cell carcinoma prognosis and immunotherapy response

OBJECTIVE

To investigate whether telomerase-associated lncRNA expression affects the prognosis and anti-tumor immunity of patients with renal clear cell carcinoma (ccRCC).

METHODS

A series of analyses were performed to establish a prognostic risk model and validate its accuracy. Immune-related analyses were performed to assess further the association between immune status, tumor microenvironment, and prognostic risk models.

RESULTS

Eight telomerase-associated lncRNAs associated with prognosis were identified and applied to establish a prognostic risk model. Overall survival was higher in the low-risk group.

CONCLUSION

The established prognostic risk model has a good predictive ability for the prognosis of ccRCC patients and provides a new possible therapeutic target for ccRCC.

Cuproptosis-related gene LIPT1 as a prognostic indicator in non-small cell lung cancer: Functional involvement and regulation of ATOX1 expression

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths, necessitating a deeper understanding of novel cell death pathways like cuproptosis. This study explored the relevance of cuproptosis-related genes in NSCLC and their potential prognostic significance. We analyzed the expression of 16 cuproptosis-related genes in 1017 NSCLC tumors and 578 Genotype-Tissue Expression (GTEx) normal samples from The Cancer Genome Atlas (TCGA) to identify significant genes. A risk model and prognostic nomogram were employed to identify the pivotal prognostic gene. Further in vitro experiments were conducted to investigate the functions of the identified genes in NSCLC cell lines. LIPT1, a gene for lipoate-protein ligase 1 enzyme, emerged as the central prognostic gene with decreased expression in NSCLC. Importantly, elevated LIPT1 levels were associated with a favorable prognosis for NSCLC patients. Overexpression of LIPT1 inhibited cell growth and enhanced apoptosis in NSCLC. We confirmed that LIPT1 downregulates the copper chaperone gene antioxidant 1 (ATOX1), thereby impeding NSCLC progression. Our study identified LIPT1 as a valuable prognostic biomarker in NSCLC as it elucidates its tumor-inhibitory role through the modulation of ATOX1. These findings offered insights into the potential therapeutic targeting of LIPT1 in NSCLC, contributing to a deeper understanding of this deadly disease.

Methods for the purification and detection of single nucleotide KRAS mutations on extrachromosomal circular DNA in human plasma

BACKGROUNDS

Despite recent advances, many cancers are still detected too late for curative treatment. There is, therefore, a need for the development of new diagnostic methods and biomarkers. One approach may arise from the detection of extrachromosomal circular DNA (eccDNA), which is part of cell-free DNA in human plasma.

AIMS

First, we assessed and compared two methods for the purification of eccDNA from plasma. Second, we tested for an easy diagnostic application of eccDNA liquid biopsy-based assays.

MATERIALS & METHODS

For the comparison we tested a solid-phase silica purification method and a phenol/chloroform method with salt precipitation. For the diagnostic application of eccDNA we developed and tested a qPCR primer-based SNP detection system, for the detection of two well-established cancer-causing KRAS mutations (G12V and G12R) on circular DNA. This investigation was supported by purifying, sequencing, and analysing clinical plasma samples for eccDNAs containing KRAS mutant alleles in 0.5 mL plasma from 16 pancreatic ductal adenocarcinoma patients and 19 healthy controls.

RESULTS

In our method comparison we observed, that following exonuclease treatment a lower eccDNA yield was found for the phenol/chloroform method (15.7%-26.7%) compared with the solid-phase purification approach (47.8%-65.9%). For the diagnostic application of eccDNA tests, the sensitivity of the tested qPCR assay only reached ~10-3 in a background of 105 wild type (wt) KRAS circular entities, which was not improved by general amplification or primer-based inhibition of wt KRAS amplification. Furthermore, we did not detect eccDNA containing KRAS in any of the clinical samples.

DISCUSSION

A potential explanation for our inability to detect any KRAS mutations in the clinical samples may be related to the general low abundance of eccDNA in plasma.

CONCLUSION

Taken together our results provide a benchmark for eccDNA purification methods while raising the question of what is required for the optimal fast and sensitive detection of SNP mutations on eccDNA with greater sensitivity than primer-based qPCR detection.

Tumor Response-speed Heterogeneity as a Novel Prognostic Factor in Patients With Metastatic Colorectal Cancer

PURPOSE

Differential tumor response to therapy is partially attributed to tumor heterogeneity. Additional efforts are needed to identify tumor heterogeneity parameters in response to therapy that is easily applicable in clinical practice. We aimed to describe tumor response-speed heterogeneity and evaluate its prognostic value in patients with metastatic colorectal cancer.

PATIENTS AND METHODS

Individual patient data from Amgen (NCT00364013) and Sanofi (NCT00305188; NCT00272051) trials were retrieved from Project Data Sphere. Patients in the Amgen 5-fluorouracil, leucovorin, oxaliplatin (FOLFOX) arm were used to establish response-speed heterogeneity. Its prognostic value was subsequently validated in the Sanofi FOLFOX arms and the Amgen panitumumab+FOLFOX arm. Kaplan-Meier method and Cox proportional hazards models were used for survival analyses.

RESULTS

Patients with high response-speed heterogeneity in the Amgen FOLFOX cohort had significantly shorter ( P <0.001) median progression-free survival (PFS) of 7.27 months (95% CI, 6.12-7.96 mo) and overall survival (OS) of 16.0 months (95% CI, 13.8-18.2 mo) than patients with low response-speed heterogeneity with median PFS of 9.41 months (95% CI, 8.75-10.89 mo) and OS of 22.4 months (95% CI, 20.1-26.7 mo), respectively. Tumor response-speed heterogeneity was a poor prognostic factor of shorter PFS (hazard ratio, 4.17; 95% CI, 2.49-6.99; P <0.001) and shorter OS (hazard ratio, 2.57; 95% CI, 1.64-4.01; P <0.001), after adjustment for other common prognostic factors. Comparable findings were found in the external validation cohorts.

CONCLUSION

Tumor response-speed heterogeneity to first-line chemotherapy was a novel prognostic factor associated with early disease progression and shorter survival in patients with metastatic colorectal cancer.

Transforming Diagnosis and Therapeutics Using Cancer Genomics

In past quarter of the century, much has been understood about the genetic variation and abnormal genes that activate cancer in humans. All the cancers somehow possess alterations in the DNA sequence of cancer cell's genome. In present, we are heading toward the era where it is possible to obtain complete genome of the cancer cells for their better diagnosis, categorization and to explore treatment options.

A new CCCH-type zinc finger-related lncRNA signature predicts the prognosis of clear cell renal cell carcinoma patients

Background: Clear cell renal cell carcinoma (ccRCC) is the main component of renal cell carcinoma (RCC), and advanced ccRCC frequently indicates a poor prognosis. The significance of the CCCH-type zinc finger (CTZF) gene in cancer has been increasingly demonstrated during the past few years. According to studies, targeted radical therapy for cancer treatment may be a revolutionary therapeutic approach. Both lncRNAs and CCCH-type zinc finger genes are essential in ccRCC. However, the predictive role of long non-coding RNA (lncRNA) associated with the CCCH-type zinc finger gene in ccRCC needs further elucidation. This study aims to predict patient prognosis and investigate the immunological profile of ccRCC patients using CCCH-type zinc finger-associated lncRNAs (CTZFLs).

Methods: From the Cancer Genome Atlas database, RNA-seq and corresponding clinical and prognostic data of ccRCC patients were downloaded. Univariate and multivariate Cox regression analyses were conducted to acquire CTZFLs for constructing prediction models. The risk model was verified using receiver operating characteristic curve analysis. The Kaplan-Meier method was used to analyze the overall survival (OS) of high-risk and low-risk groups. Multivariate Cox and stratified analyses were used to assess the prognostic value of the predictive feature in the entire cohort and different subgroups. In addition, the relationship between risk scores, immunological status, and treatment response was studied.

Results: We constructed a signature consisting of eight CTZFLs (LINC02100, AC002451.1, DBH-AS1, AC105105.3, AL357140.2, LINC00460, DLGAP1-AS2, AL162377.1). The results demonstrated that the prognosis of ccRCC patients was independently predicted by CTZFLs signature and that the prognosis of high-risk groups was poorer than that of the lower group. CTZFLs markers had the highest diagnostic adequacy compared to single clinicopathologic factors, and their AUC (area under the receiver operating characteristic curve) was 0.806. The overall survival of high-risk groups was shorter than that of low-risk groups when patients were divided into groups based on several clinicopathologic factors. There were substantial differences in immunological function, immune cell score, and immune checkpoint expression between high- and low-risk groups. Additionally, Four agents, including ABT737, WIKI4, afuresertib, and GNE 317, were more sensitive in the high-risk group.

Conclusion: The Eight-CTZFLs prognostic signature may be a helpful prognostic indicator and may help with medication selection for clear cell renal cell carcinoma.

Combining Molecular, Imaging, and Clinical Data Analysis for Predicting Cancer Prognosis

Simple Summary

The rise of Big Data, the widespread use of Machine Learning, and the cheapening of omics techniques have allowed for the creation of more sophisticated and accurate models in biomedical research. This article presents the state-of-the-art predictive models of cancer prognosis that use multimodal data, considering clinical, molecular (omics and non-omics), and image data. The subject of study, the data modalities used, the data processing and modelling methods applied, the validation strategies involved, the integration strategies encompassed, and the evolution of prognostic predictive models are discussed. Finally, we discuss challenges and opportunities in this field of cancer research, with great potential impact on the clinical management of patients and, by extension, on the implementation of personalised and precision medicine.

Abstract

Cancer is one of the most detrimental diseases globally. Accordingly, the prognosis prediction of cancer patients has become a field of interest. In this review, we have gathered 43 state-of-the-art scientific papers published in the last 6 years that built cancer prognosis predictive models using multimodal data. We have defined the multimodality of data as four main types: clinical, anatomopathological, molecular, and medical imaging; and we have expanded on the information that each modality provides. The 43 studies were divided into three categories based on the modelling approach taken, and their characteristics were further discussed together with current issues and future trends. Research in this area has evolved from survival analysis through statistical modelling using mainly clinical and anatomopathological data to the prediction of cancer prognosis through a multi-faceted data-driven approach by the integration of complex, multimodal, and high-dimensional data containing multi-omics and medical imaging information and by applying Machine Learning and, more recently, Deep Learning techniques. This review concludes that cancer prognosis predictive multimodal models are capable of better stratifying patients, which can improve clinical management and contribute to the implementation of personalised medicine as well as provide new and valuable knowledge on cancer biology and its progression.

The diagnostic accuracy of intravoxel incoherent motion and diffusion kurtosis imaging in the differentiation of malignant and benign soft-tissue masses: which is better?

BACKGROUND

It is difficult for conventional magnetic resonance imaging (MRI) to distinguish benign soft-tissue masses (STMs) from malignant masses.

PURPOSE

To quantitatively compare the diagnostic value of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in STMs.

MATERIAL AND METHODS

The data from 58 patients with STMs were retrospectively analyzed. The GE Discovery 3.0-T MRI scanner was used to acquire conventional MRI sequences, IVIM, and DKI images. The chi-square test, independent sample t-test, and Mann-Whitney U tests were used to compare the differences between conventional MRI features, IVIM, and DKI parameters (D_slow, D_fast, f, mean kurtosis [MK], and mean diffusivity [MD]) between the benign and malignant groups. Receiver-operating characteristic (ROC) curve analysis was also performed.

RESULTS

Tumor size and depth are statistically different in STTs. Ds_low, MK, and MD values in the malignant groups are significantly lower than the benign groups (P < 0.05). However, D_fast and f values are not statistically different between the two groups. The area under the curve (AUC) of D_slow value (0.859) is higher than MD (0.765) and MK (0.676) values for identifying benign and malignant STMs. The D_slow value showed the best specificity (82.93%). The sensitivity and specificity of IVIM and DKI parameters are higher than that of conventional MRI sequences.

CONCLUSION

IVIM and DKI can be used to distinguish between benign and malignant STMs, with D_slow as the most meaningful parameter.

Clinical outcomes as a function of the number of samples taken during stereotactic needle biopsies: a meta-analysis

BACKGROUND

Stereotactic needle biopsy remains the cornerstone for tissue diagnosis for tumors located in regions of the brain that are difficult to access through open surgery.

OBJECTIVE

We perform a meta-analysis of the literature to examine the relation between number of samples taken during biopsy and diagnostic yield, morbidity and mortality.

METHODS

We identified 2416 patients from 28 cohorts in studies published in PubMed database that studied stereotactic needle biopsies for tumor indications. Meta-analysis by proportions and meta-regression analyses were performed.

RESULTS

On meta-analysis, the morbidity profile of the published needle biopsy studies clustered into three groups: studies that performed < 3 samples (n = 8), 3-6 samples (n = 13), and > 6 samples during biopsy (n = 7). Pooled estimates for biopsy related morbidity were 4.3%, 16.3%, and 17% for studies reporting < 3, 3-6, and > 6 biopsy samples, respectively. While these morbidity estimates significantly differed (p < 0.001), the diagnostic yields reported for studies performing < 3 biopsies, 3-6 samples, and > 6 samples were comparable. Pooled estimates of diagnostic yield for these three groups were 90.4%, 93.8%, and 88.1%, respectively. Mortality did not significantly differ between studies reporting differing number of samples taken during biopsy.

CONCLUSIONS

Our meta-analysis suggests that morbidity risk in needle biopsy is non-linearly associated with the number of samples taken. There was no association between the number of biopsies taken, and diagnostic yield or mortality.

Potential applications of aptamers in veterinary science

Aptamers are small nucleic acids that fold in a three-dimensional conformation allowing them to bind specifically to a target. This target can be an organic molecule, free or carried in cells or tissues, or inorganic components, such as metal ions. Analogous to monoclonal antibodies, aptamers however have certain advantages over the latter: e.g., high specificity for their target, no to low immunogenicity and easy in vitro selection. Since their discovery more than 30 years ago, aptamers have led to various applications, although mainly restricted to basic research. This work reviews the applications of aptamers in veterinary science to date. First, we present aptamers, how they are selected and their properties, then we give examples of applications in food and environmental safety, as well as in diagnosis and medical treatment in the field of veterinary medicine. Because examples of applications in veterinary medicine are scarce, we explore the potential avenues for future applications based on discoveries made in human medicine. Aptamers may offer new possibilities for veterinarians to diagnose certain diseases—particularly infectious diseases—more rapidly or “at the patient’s bedside”. All the examples highlight the growing interest in aptamers and the premises of a potential market. Aptamers may benefit animals as well as their owners, breeders and even public health in a “One Health” approach.

Current update on nanoplatforms as therapeutic and diagnostic tools: A review for the materials used as nanotheranostics and imaging modalities

In the last decade, the use of nanotheranostics as emerging diagnostic and therapeutic tools for various diseases, especially cancer, is held great attention. Up to date, several approaches have been employed in order to develop smart nanotheranostics, which combine bioactive targeting on specific tissues as well as diagnostic properties. The nanotheranostics can deliver therapeutic agents by concomitantly monitor the therapy response in real-time. Consequently, the possibility of over- or under-dosing is decreased. Various non-invasive imaging techniques have been used to quantitatively monitor the drug delivery processes. Radiolabeling of nanomaterials is widely used as powerful diagnostic approach on nuclear medicine imaging. In fact, various radiolabeled nanomaterials have been designed and developed for imaging tumors and other lesions due to their efficient characteristics. Inorganic nanoparticles as gold, silver, silica based nanomaterials or organic nanoparticles as polymers, carbon based nanomaterials, liposomes have been reported as multifunctional nanotheranostics. In this review, the imaging modalities according to their use in various diseases are summarized, providing special details for radiolabeling. In further, the most current nanotheranostics categorized via the used nanomaterials are also summed up. To conclude, this review can be beneficial for medical and pharmaceutical society as well as material scientists who work in the field of nanotheranostics since they can use this research as guide for producing newer and more efficient nanotheranostics.

In vivo CRISPR/Cas9 targeting of fusion oncogenes for selective elimination of cancer cells

Fusion oncogenes (FOs) are common in many cancer types and are powerful drivers of tumor development. Because their expression is exclusive to cancer cells and their elimination induces cell apoptosis in FO-driven cancers, FOs are attractive therapeutic targets. However, specifically targeting the resulting chimeric products is challenging. Based on CRISPR/Cas9 technology, here we devise a simple, efficient and non-patient-specific gene-editing strategy through targeting of two introns of the genes involved in the rearrangement, allowing for robust disruption of the FO specifically in cancer cells. As a proof-of-concept of its potential, we demonstrate the efficacy of intron-based targeting of transcription factors or tyrosine kinase FOs in reducing tumor burden/mortality in in vivo models. The FO targeting approach presented here might open new horizons for the selective elimination of cancer cells.

In vivo CRISPR/Cas9 targeting of fusion oncogenes for selective elimination of cancer cells

Fusion oncogenes (FOs) are common in many cancer types and are powerful drivers of tumor development. Because their expression is exclusive to cancer cells and their elimination induces cell apoptosis in FO-driven cancers, FOs are attractive therapeutic targets. However, specifically targeting the resulting chimeric products is challenging. Based on CRISPR/Cas9 technology, here we devise a simple, efficient and non-patient-specific gene-editing strategy through targeting of two introns of the genes involved in the rearrangement, allowing for robust disruption of the FO specifically in cancer cells. As a proof-of-concept of its potential, we demonstrate the efficacy of intron-based targeting of transcription factors or tyrosine kinase FOs in reducing tumor burden/mortality in in vivo models. The FO targeting approach presented here might open new horizons for the selective elimination of cancer cells.

Integration of Transcriptome, Gross Morphology and Histopathology in the Gill of Sea Farmed Atlantic Salmon (Salmo salar): Lessons From Multi-Site Sampling

The gill of teleost fish is a multifunctional organ involved in many physiological processes such as gas exchange, osmotic and ionic regulation, acid-base balance and excretion of nitrogenous waste. Due to its extensive interface with the environment, the gill plays a key role as a primary mucosal defense tissue against pathogens, as manifested by the presence of the gill-associated lymphoid tissue (GIALT). In recent years, the prevalence of multifactorial gill pathologies has increased significantly, causing substantial losses in Atlantic salmon aquaculture. The transition from healthy to unhealthy gill phenotypes and the progression of multifactorial gill pathologies, such as proliferative gill disease (PGD), proliferative gill inflammation (PGI) and complex gill disorder (CGD), are commonly characterized by epithelial hyperplasia, lamellar fusion and inflammation. Routine monitoring for PGD relies on visual inspection and non-invasive scoring of the gill tissue (gross morphology), coupled with histopathological examination of gill sections. To explore the underlying molecular events that are associated with the progression of PGD, we sampled Atlantic salmon from three different marine production sites in Scotland and examined the gill tissue at three different levels of organization: gross morphology with the use of PGD scores (macroscopic examination), whole transcriptome (gene expression by RNA-seq) and histopathology (microscopic examination). Our results strongly suggested that the changes in PGD scores of the gill tissue were not associated with the changes in gene expression or histopathology. In contrast, integration of the gill RNA-seq data with the gill histopathology enabled us to identify common gene expression patterns associated with multifactorial gill disease, independently from the origin of samples. We demonstrated that the gene expression patterns associated with multifactorial gill disease were dominated by two processes: a range of immune responses driven by pro-inflammatory cytokines and the events associated with tissue damage and repair, driven by caspases and angiogenin.

Evolution in the management of soft tissue sarcoma: classification, surgery and use of radiotherapy

Background: Given the rapid evolution in the management of soft tissue sarcoma (STS), it is essential to revisit the evidence regularly. This review examines topics of interest for early management of STS: the impact of molecular genetics on sarcoma classification; the importance of a correct diagnosis and strategy in the surgical management of STS; current status on use of radiotherapy in STS.Areas covered: Accurate diagnosis of STS combines histomorphology, immunochemistry, and molecular genetics, although morphology is the mainstay of therapeutic planning. As diagnosis of STS is challenging, it is best conducted within a multidisciplinary environment. Expert surgery in STS takes into account multiple parameters including biopsy, imaging, pathological knowledge, technical issues, and a multidisciplinary approach. The sum of these factors informs decisions about whether or not to perform surgery and the choice of surgical technique. Advances in radiotherapy are challenging the paradigm of applying the same dose and treatment schedule to all STS patients irrespective of subtype. Preoperative radiotherapy of specific histotypes appears to be the future although more research is required to address uncertainties such as fraction size, total dose, combined modality regimens, and individual sensitivity to radiotherapy.Expert opinion: STS should be managed in a reference center.

Integrated diagnostics: the future of laboratory medicine?

The current scenario of in vitro and in vivo diagnostics can be summarized using the “silo metaphor”, where laboratory medicine, pathology and radiology are three conceptually separated diagnostic disciplines, which will increasingly share many comparable features. The substantial progresses in our understanding of biochemical-biological interplays that characterize many human diseases, coupled with extraordinary technical advances, are now generating important multidisciplinary convergences, leading the way to a new frontier, called integrated diagnostics. This new discipline, which is currently defined as convergence of imaging, pathology and laboratory tests with advanced information technology, has an enormous potential for revolutionizing diagnosis and therapeutic management of human diseases, including those causing the largest number of worldwide deaths (i.e. cardiovascular disease, cancer and infectious diseases). However, some important drawbacks should be overcome, mostly represented by insufficient information technology infrastructures, costs and enormous volume of different information that will be integrated and delivered. To overcome these hurdles, some specific strategies should be defined and implemented, such as planning major integration of exiting information systems or developing innovative ones, combining bioinformatics and imaging informatics, using health technology assessment for assessing cost and benefits, providing interpretative comments in integrated reports, developing and using expert systems and neural networks, overcoming cultural and political boundaries for generating multidisciplinary teams and integrated diagnostic algorithms.

Precision Medicine in Pediatric Cancer: Current Applications and Future Prospects

Precision oncologic medicine is an emerging approach for cancer treatment that has recently taken giant steps in solid clinical practice. Recent advances in molecular diagnostics that can analyze the individual tumor’s variability in genes have provided greater understanding and additional strategies to treat cancers. Although tumors can be tested by several molecular methods, the use of next-generation sequencing (NGS) has greatly facilitated our understanding of pediatric cancer and identified additional therapeutic opportunities. Pediatric tumors have a different genetic make-up, with a fewer number of actionable targets than adult tumors. Nevertheless, precision oncology in the pediatric population has greatly improved the survival of patients with leukemia and solid tumors. This review discusses the current status of pediatric precision oncology and the different clinical scenarios in which it can be effectively applied.

Immunogenetics of glioblastoma: the future of personalized patient management

The prognosis of glioblastoma has changed little over the past two decades, with only minor improvements in length of overall survival through the addition of temozolomide (temodal) to standard of care and the recommended use of alternating electric field therapy (optune) to newly diagnosed patients. In an effort to define novel therapeutic targets across molecularly heterogeneous disease subgroups, researchers have begun to uncover the complex interplay between epigenetics, cell signaling, metabolism, and the immunosuppressive tumor microenvironment. Indeed, IDH mutations are now recognized as a defining differential factor not only influencing global hypermethylation and patient prognosis but also degree of immune infiltration within individual tumors. Likewise, next-generation sequencing has defined subgroup-specific transcriptional profiles that correlate with different mechanisms of immune evasion, including increased PD-L1 and CTLA-4 among mesenchymal tumors. Interestingly, sequencing of the T cell repertoire from numerous patient samples suggests that the correlation between mutational burden and enrichment of tumor-specific peptides may be less convincing than originally suspected. While this raises questions over the efficacy of dendritic cell or tumor-lysate vaccines and CAR-T therapies, these avenues continue to be explored. In addition to these active immunotherapies, inhibitors of molecular hubs with wide reaching effects, including STAT3, IDO, and TGF-β, are now in early-phase clinical trials. With the potential to block intrinsic biological properties of tumor growth and invasion while bolstering the immunogenic profile of the tumor microenvironment, these new targets represent a new direction for GBM therapies. In this review, we show the advances in molecular profiling and immunophenotyping of GBM, which may lead to the development of new personalized therapeutic strategies.

The key role of pathology, surgery and radiotherapy in the initial management of soft tissue sarcoma

Soft tissue sarcomas are a heterogeneous group of rare malignancies. The diagnostic gold standard is conventional histomorphology with integrated immunohistochemistry. Molecular genetic profiling has identified new subgroups of undifferentiated sarcomas involving genetic rearrangements with creation of fusion genes. Accurate classification of sarcomas is critical for appropriate clinical decision-making which should involve a multidisciplinary team. A preoperative biopsy is necessary to confirm a diagnosis. Strategy is discussed in the multidisciplinary board. Reconstructive surgery must be planned in advance taking into account possible surgical morbidity. In high-risk situations, neo-adjuvant treatment could facilitate surgery in some cases, increase survival and provide indications of tumor biology. The decision is based on tumor subtype, grade and location, patient age and presence of comorbidities.

Fusion genes: A promising tool combating against cancer

The driving roles of fusion genes during tumorigenesis have been recognized for decades, with efficacies demonstrated in clinical diagnosis and targeted therapy. With advances in sequencing technologies and computational biology, a surge in the identification of fusion genes has been witnessed during the past decade. The discovery and presence of splicing based fusions in normal tissues have challenged our canonical conceptions on fusion genes and offered us novel medical opportunities. The specificity of fusion genes to neoplastic tissues and their diverse functionalities during carcinogenesis foster them as promising tools in the battle against cancer. It is time to re-visit and comb through our cutting-edge knowledge on fusion genes to accelerate clinical translation of these internal markers. Urged as such, we are encouraged to categorize fusion events according to mechanisms leading to their generation, oncological consequences and clinical implications, offer insights on fusion occurrence across tumors from the system level, highlight feasible practices in fusion-related pharmaceutical development, and identify understudied yet important niches that may lead future research trend in this field.

Low neighbor of Brca1 gene expression predicts poor clinical outcome and resistance of sunitinib in clear cell renal cell carcinoma

Objective

To study the expression of Neighbor of Brca1 gene (NBR1) in clear cell renal cell carcinoma (ccRCC), renal cancer cells and the chemoresistance cells and to elucidate its clinical prognostic and chemoresistance value.

Materials and Methods

We screened the NBR1 mRNA in ccRCC from The Cancer Genome Atlas (TCGA) database and examined expression levels of NBR1 mRNA in 48 cases of ccRCC tissues, renal cancer cell lines and chemoresistance cells by qRT-PCR. Then, we extended two additional data sets in oncomine datebase (https://www.oncomine.org) to further confirm the results of the TCGA database. Immunohistochemistry (IHC) assay data performed in ccRCC tissues and normal tissues were downloaded from The Human Protein Atlas.

Results

The mRNA levels of NBR1 were downregulated in TCGA-KIRC database (n = 533) and ccRCC patient samples (n=48) as well as in RCC cell lines and their chemoresistance cells. Similarly, the protein levels of NBR1 were lower in ccRCC patient samples. NBR1 level was associated with the clinical pathological stage and could discriminate metastasis, recurrence and prognosis in ccRCC patients. Low level of NBR1 mRNA showed a significance poor prognostic of overall survival (OS), disease–free survival (DFS) with univariate and multivariate analyses in ccRCC patients and sunitinib resistance.

Conclusions

Taken together, our results suggest that low level of NBR1 can predict poor clinical outcome and resistance of sunitinib in patients with ccRCC.

Characterisation of the changing genomic landscape of metastatic melanoma using cell free DNA

Cancer is characterised by complex somatically acquired genetic aberrations that manifest as intra-tumour and inter-tumour genetic heterogeneity and can lead to treatment resistance. In this case study, we characterise the genome-wide somatic mutation dynamics in a metastatic melanoma patient during therapy using low-input (50 ng) PCR-free whole genome sequencing of cell-free DNA from pre-treatment and post-relapse blood samples. We identify de novo tumour-specific somatic mutations from cell-free DNA, while the sequence context of single nucleotide variants showed the characteristic UV-damage mutation signature of melanoma. To investigate the behaviour of individual somatic mutations during proto-oncogene B-Raf -targeted and immune checkpoint inhibition, amplicon-based deep sequencing was used to verify and track frequencies of 212 single nucleotide variants at 10 distinct time points over 13 months of treatment. Under checkpoint inhibition therapy, we observed an increase in mutant allele frequencies indicating progression on therapy 88 days before clinical determination of non-response positron emission tomogrophy-computed tomography. We also revealed mutations from whole genome sequencing of cell-free DNA that were not present in the tissue biopsy, but that later contributed to relapse. Our findings have potential clinical applications where high quality tumour-tissue derived DNA is not available.