Analysis of the EGFR Amplification and CDKN2A Deletion Regulated Transcriptomic Signatures Reveals the Prognostic Significance of SPATS2L in Patients With Glioma

Application of novel PACS-based informatics platform to identify imaging based predictors of CDKN2A allelic status in glioblastomas

Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features with Visually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. Sixty nine patients undergoing GBM resection with CDKN2A status determined by whole-exome sequencing were included. GBMs on magnetic resonance images were automatically 3D segmented using deep learning algorithms incorporated within PACS. VASARI features were assessed using FHIR forms integrated within PACS. GBMs without CDKN2A alterations were significantly larger (64 vs. 30%, p = 0.007) compared to tumors with homozygous deletion (HOMDEL) and heterozygous loss (HETLOSS). Lesions larger than 8 cm were four times more likely to have no CDKN2A alteration (OR: 4.3; 95% CI 1.5-12.1; p < 0.001). We developed a novel integrated PACS informatics platform for the assessment of GBM molecular subtypes and show that tumors with HOMDEL are more likely to have radiographic evidence of pial invasion and less likely to have deep white matter invasion or subependymal invasion. These imaging features may allow noninvasive identification of CDKN2A allele status.

Oncogenes and cancer associated thrombosis: what can we learn from single cell genomics about risks and mechanisms?

Single cell analysis of cancer cell transcriptome may shed a completely new light on cancer-associated thrombosis (CAT). CAT causes morbid, and sometimes lethal complications in certain human cancers known to be associated with high risk of venous thromboembolism (VTE), pulmonary embolism (PE) or arterial thromboembolism (ATE), all of which worsen patients' prognosis. How active cancers drive these processes has long evaded scrutiny. While "unspecific" microenvironmental effects and consequences of patient care (e.g., chemotherapy) have been implicated in pathogenesis of CAT, it has also been suggested that oncogenic pathways driven by either genetic (mutations), or epigenetic (methylation) events may influence the coagulant phenotype of cancer cells and stroma, and thereby modulate the VTE/PE risk. Consequently, the spectrum of driver events and their downstream effector mechanisms may, to some extent, explain the heterogeneity of CAT manifestations between cancer types, molecular subtypes, and individual cases, with thrombosis-promoting, or -protective mutations. Understanding this molecular causation is important if rationally designed countermeasures were to be deployed to mitigate the clinical impact of CAT in individual cancer patients. In this regard, multi-omic analysis of human cancers, especially at a single cell level, has brought a new meaning to concepts of cellular heterogeneity, plasticity, and multicellular complexity of the tumour microenvironment, with profound and still relatively unexplored implications for the pathogenesis of CAT. Indeed, cancers may contain molecularly distinct cellular subpopulations, or dynamic epigenetic states associated with different profiles of coagulant activity. In this article we discuss some of the relevant lessons from the single cell "omics" and how they could unlock new potential mechanisms through which cancer driving oncogenic lesions may modulate CAT, with possible consequences for patient stratification, care, and outcomes.

Therapy-induced senescence as a component of tumor biology: Evidence from clinical cancer

Therapy-Induced Senescence (TIS) is an established response to anticancer therapy in a variety of cancer models. Ample evidence has characterized the triggers, hallmarks, and functional outcomes of TIS in preclinical studies; however, limited evidence delineates TIS in clinical cancer (human tumor samples). We examined the literature that investigated the induction of TIS in samples derived from human cancers and highlighted the major findings that suggested that TIS represents a main constituent of tumor biology. The most frequently utilized approach to identify TIS in human cancers was to investigate the protein expression of senescence-associated markers (such as cyclins, cyclin-dependent kinase inhibitors, Ki67, DNA damage repair response markers, DEC1, and DcR1) via immunohistochemical techniques using formalin-fixed paraffin-embedded (FFPE) tissue samples and/or testing the upregulation of Senescence-Associated β-galactosidase (SA-β-gal) in frozen sections of unfixed tumor samples. Collectively, and in studies where the extent of TIS was determined, TIS was detected in 31-66% of tumors exposed to various forms of chemotherapy. Moreover, TIS was not only limited to both malignant and non-malignant components of tumoral tissue but was also identified in samples of normal (non-transformed) tissue upon chemo- or radiotherapy exposure. Nevertheless, the available evidence continues to be limited and requires a more rigorous assessment of in vivo senescence based on novel approaches and more reliable molecular signatures. The accurate assessment of TIS will be beneficial for determining its relevant contribution to the overall outcome of cancer therapy and the potential translatability of senotherapeutics.

Dynamic contrast-enhanced MRI radiomics model predicts epidermal growth factor receptor amplification in glioblastoma, IDH-wildtype

PURPOSE

To develop and validate a dynamic contrast-enhanced (DCE) MRI-based radiomics model to predict epidermal growth factor receptor (EGFR) amplification in patients with glioblastoma, isocitrate dehydrogenase (IDH) wildtype.

METHODS

Patients with pathologically confirmed glioblastoma, IDH wildtype, from January 2015 to December 2020, with an EGFR amplification status, were included. Patients who did not undergo DCE or conventional brain MRI were excluded. Patients were categorized into training and test sets by a ratio of 7:3. DCE MRI data were used to generate volume transfer constant (Ktrans) and extracellular volume fraction (Ve) maps. Ktrans, Ve, and conventional MRI were then used to extract the radiomics features, from which the prediction models for EGFR amplification status were developed and validated.

RESULTS

A total of 190 patients (mean age, 59.9; male, 55.3%), divided into training (n = 133) and test (n = 57) sets, were enrolled. In the test set, the radiomics model using the Ktrans map exhibited the highest area under the receiver operating characteristic curve (AUROC), 0.80 (95% confidence interval [CI], 0.65-0.95). The AUROC for the Ve map-based and conventional MRI-based models were 0.74 (95% CI, 0.58-0.90) and 0.76 (95% CI, 0.61-0.91).

CONCLUSION

The DCE MRI-based radiomics model that predicts EGFR amplification in glioblastoma, IDH wildtype, was developed and validated. The MRI-based radiomics model using the Ktrans map has higher AUROC than conventional MRI.

Using EGFR amplification to stratify recurrent glioblastoma treated with immune checkpoint inhibitors

PURPOSE

While immune checkpoint inhibitors (ICI) have had success with various malignancies, their efficacy in brain cancer is still unclear. Retrospective and prospective studies using PD-1 inhibitors for recurrent glioblastoma (GBM) have not established survival benefit. This study evaluated if ICI may be effective for select patients with recurrent GBM.

METHODS

This was a single-center retrospective study of adult patients diagnosed with first recurrence GBM and received pembrolizumab or nivolumab with or without concurrent bevacizumab. Archival tissue was used for immunohistochemistry (IHC) and targeted DNA next-generation sequencing (NGS) analysis.

RESULTS

Median overall survival (mOS) from initial diagnosis was 24.5 months (range 10-42). mOS from onset of ICI was 10 months (range 1-31) with 75% surviving > 6 months and 46% > 12 months. Additional IHC analysis on tumors from eight patients demonstrated a trend of longer survival after ICI for those with elevated PD-L1 expression. NGS of samples from 15 patients identified EGFR amplification at initial diagnosis and at any time point to be associated with worse survival after ICI (HR 12.2, 95% CI 1.37-108, p = 0.025 and HR 3.92, 95% CI 1.03-14.9, p = 0.045, respectively). This significance was corroborated with previously tested EGFR amplification via in situ hybridization.

CONCLUSION

ICI did not extend overall survival for recurrent GBM. However, molecular sequencing identified EGFR amplification as associated with worse survival. Prospective studies can validate if EGFR amplification is a biomarker of ICI resistance and determine if its use can stratify responders from non-responders.

Prognostic Values of Gene Copy Number Alterations in Prostate Cancer

Whilst risk prediction for individual prostate cancer (PCa) cases is of a high priority, the current risk stratification indices for PCa management have severe limitations. This study aimed to identify gene copy number alterations (CNAs) with prognostic values and to determine if any combination of gene CNAs could have risk stratification potentials. Clinical and genomic data of 500 PCa cases from the Cancer Genome Atlas stable were retrieved from the Genomic Data Commons and cBioPortal databases. The CNA statuses of a total of 52 genetic markers, including 21 novel markers and 31 previously identified potential prognostic markers, were tested for prognostic significance. The CNA statuses of a total of 51/52 genetic markers were significantly associated with advanced disease at an odds ratio threshold of ≥1.5 or ≤0.667. Moreover, a Kaplan-Meier test identified 27/52 marker CNAs which correlated with disease progression. A Cox Regression analysis showed that the amplification of MIR602 and deletions of MIR602, ZNF267, MROH1, PARP8, and HCN1 correlated with a progression-free survival independent of the disease stage and Gleason prognostic group grade. Furthermore, a binary logistic regression analysis identified twenty-two panels of markers with risk stratification potentials. The best model of 7/52 genetic CNAs, which included the SPOP alteration, SPP1 alteration, CCND1 amplification, PTEN deletion, CDKN1B deletion, PARP8 deletion, and NKX3.1 deletion, stratified the PCa cases into a localised and advanced disease with an accuracy of 70.0%, sensitivity of 85.4%, specificity of 44.9%, positive predictive value of 71.67%, and negative predictive value of 65.35%. This study validated prognostic gene level CNAs identified in previous studies, as well as identified new genetic markers with CNAs that could potentially impact risk stratification in PCa.

Insights into the Peritumoural Brain Zone of Glioblastoma: CDK4 and EXT2 May Be Potential Drivers of Malignancy

Despite the efforts made in recent decades, glioblastoma is still the deadliest primary brain cancer without cure. The potential role in tumour maintenance and progression of the peritumoural brain zone (PBZ), the apparently normal area surrounding the tumour, has emerged. Little is known about this area due to a lack of common definition and due to difficult sampling related to the functional role of peritumoural healthy brain. The aim of this work was to better characterize the PBZ and to identify genes that may have role in its malignant transformation. Starting from our previous study on the comparison of the genomic profiles of matched tumour core and PBZ biopsies, we selected CDK4 and EXT2 as putative malignant drivers of PBZ. The gene expression analysis confirmed their over-expression in PBZ, similarly to what happens in low-grade glioma and glioblastoma, and CDK4 high levels seem to negatively influence patient overall survival. The prognostic role of CDK4 and EXT2 was further confirmed by analysing the TCGA cohort and bioinformatics prediction on their gene networks and protein-protein interactions. These preliminary data constitute a good premise for future investigations on the possible role of CDK4 and EXT2 in the malignant transformation of PBZ.

Co-amplified with PDGFRA, IGFBP7 is a prognostic biomarker correlated with the immune infiltrations of glioma

BACKGROUND

A subgroup of glioma carry genetic 4q12 amplification including platelet derived growth factor receptor α (PDGFRA) and insulin like growth factor binding protein 7 (IGFBP7). However, the prognosis of PDGFRA and IGFBP7 in glioma is unclear.

METHODS

The prognosis of PDGFRA and IGFBP7 was determined using cox regression and Kaplan-Meier survival analysis. Pathways associated with IGFBP7 were analyzed through gene set enrichment analysis (GSEA). Immune profiling of glioma was determined using "ESTIMATE" and "TIMER" database.

RESULTS

PDGFRA amplification or expression was not correlated with the outcomes of glioblastoma (GBM). IGFBP7 but not PDGFRA was over-expressed in GBM. IGFBP7 over-expression was correlated with the unfavorable outcomes of GBM. In lower grade glioma (LGG), PDGFRA over-expression was not correlated with the unfavorable prognosis of LGG, while, IGFBP7 was a prognostic biomarker of LGG. LGG patients with IGFBP7 lower expressions had prolonged clinical overall survival. Combination of IDH mutation, LGG grade and IGFBP7 achieved even better prognostic effects in LGG. Moreover, IGFBP7 was over-expressed in glioma patients with wild type IDH or with high grades. IGFBP7 over-expression was correlated with the unfavorable outcomes of glioma. Furthermore, IGFBP7 was hypo-methylated in GBM or LGG patients without IDH mutations. IGFBP7 hyper-methylation was correlated with the lower overall survival of GBM or LGG. LGG patients with wild type IDH and with IGFBP7 hypo-methylation demonstrated even worse prognosis. IGFBP7 was associated with multiple immune-related signaling pathways in GBM or LGG. The stromal score, immune score and the infiltrations of immune cells were also correlated with IGFBP7 and the prognosis of LGG.

CONCLUSIONS

IGFBP7 but not PDGFRA served an ideal prognostic marker and therapeutic target of glioma.

Establishment and analysis of a disease risk prediction model for the systemic lupus erythematosus with random forest

Systemic lupus erythematosus (SLE) is a latent, insidious autoimmune disease, and with the development of gene sequencing in recent years, our study aims to develop a gene-based predictive model to explore the identification of SLE at the genetic level. First, gene expression datasets of SLE whole blood samples were collected from the Gene Expression Omnibus (GEO) database. After the datasets were merged, they were divided into training and validation datasets in the ratio of 7:3, where the SLE samples and healthy samples of the training dataset were 334 and 71, respectively, and the SLE samples and healthy samples of the validation dataset were 143 and 30, respectively. The training dataset was used to build the disease risk prediction model, and the validation dataset was used to verify the model identification ability. We first analyzed differentially expressed genes (DEGs) and then used Lasso and random forest (RF) to screen out six key genes (OAS3, USP18, RTP4, SPATS2L, IFI27 and OAS1), which are essential to distinguish SLE from healthy samples. With six key genes incorporated and five iterations of 10-fold cross-validation performed into the RF model, we finally determined the RF model with optimal mtry. The mean values of area under the curve (AUC) and accuracy of the models were over 0.95. The validation dataset was then used to evaluate the AUC performance and our model had an AUC of 0.948. An external validation dataset (GSE99967) with an AUC of 0.810, an accuracy of 0.836, and a sensitivity of 0.921 was used to assess the model's performance. The external validation dataset (GSE185047) of all SLE patients yielded an SLE sensitivity of up to 0.954. The final high-throughput RF model had a mean value of AUC over 0.9, again showing good results. In conclusion, we identified key genetic biomarkers and successfully developed a novel disease risk prediction model for SLE that can be used as a new SLE disease risk prediction aid and contribute to the identification of SLE.

CiberAMP: An R Package to Identify Differential mRNA Expression Linked to Somatic Copy Number Variations in Cancer Datasets

Simple Summary

The ability to establish accurate correlations between the number of copies of genes and the expression levels of their encoded transcripts remains a challenge despite the extensive progress made in the understanding of the genome of cancer cells. Here, we describe a new algorithm that does so by integrating both genomics and transcriptomics data from the Cancer Genome Atlas. In addition to explaining the step-by-step basis of this new method, we provide examples of how this new algorithm can help identify functionally meaningful gene copy alterations that are recurrently detected in cancer patients.

Abstract

Somatic copy number variations (SCNVs) are genetic alterations frequently found in cancer cells. These genetic alterations can lead to concomitant perturbations in the expression of the genes included in them and, as a result, promote a selective advantage to cancer cells. However, this is not always the case. Due to this, it is important to develop in silico tools to facilitate the accurate identification and functional cataloging of gene expression changes associated with SCNVs from pan-cancer data. Here, we present a new R-coded tool, designated as CiberAMP, which utilizes genomic and transcriptomic data contained in the Cancer Genome Atlas (TCGA) to identify such events. It also includes information on the genomic context in which such SCNVs take place. By doing so, CiberAMP provides clues about the potential functional relevance of each of the SCNV-associated gene expression changes found in the interrogated tumor samples. The main features and advantages of this new algorithm are illustrated using glioblastoma data from the TCGA database.

Advances in nano-based materials for glioblastoma multiforme diagnosis: A mini-review

The development of nano-based materials for diagnosis enables a more precise prognosis and results. Inorganic, organic, or hybrid nanoparticles using nanomaterials, such as quantum dots, extracellular vesicle systems, and others, with different molecular compositions, have been extensively explored as a better strategy to overcome the blood-brain barrier and target brain tissue and tumors. Glioblastoma multiforme (GBM) is the most common and aggressive primary tumor of the central nervous system, with a short, established prognosis. The delay in early detection is considered a key challenge in designing a precise and efficient treatment with the most encouraging prognosis. Therefore, the present mini-review focuses on discussing distinct strategies presented recently in the literature regarding nanostructures’ use, design, and application for GBM diagnosis.

CCT6A and CHCHD2 Are Coamplified with EGFR and Associated with the Unfavorable Clinical Outcomes of Lung Adenocarcinoma

Chaperonin containing TCP1 subunit 6A (CCT6A) and coiled-coil-helix-coiled-coil-helix domain containing 2 (CHCHD2) are located at the chromosome 7p11 region proximal to epidermal growth factor receptor (EGFR). However, the amplifications, expressions, and the prognostic effects of CCT6A and CHCDH2 in lung adenocarcinoma (LUAD) are unclear. Here, using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, we found that CCT6A was coamplified and coexpressed with EGFR in LUAD patients. CCT6A amplification was correlated with the unfavorable outcomes of LUAD. Moreover, CCT6A was upregulated in LUAD tissues, and CCT6A overexpression was correlated with the unfavorable relapse free survival or overall survival of LUAD. On the contrary, CCT6A was hypomethylated in LUAD, and CCT6A hypermethylation was correlated with the favorable overall survival of LUAD. Similar expression and methylation profiling of CCT6A were obtained in 479 lung normal tissues and 544 LUAD tissues collected from 11 independent datasets. In 1,462 LUAD patients from eight independent cohorts, CCT6A was also correlated with LUAD relapse-free survival or overall survival. Furthermore, CCT6A overexpression promoted the cell growth and invasion of LUAD. Identification of genes differentially expressed in CCT6A highly expressed LUAD patients revealed that CHCHD2 was the most correlated with CCT6A expression. CHCHD2 was coamplified with CCT6A. CHCHD2 was upregulated in LUAD tissues, and overexpression of CHCHD2 was correlated with the shorted relapse-free survival or overall survival of LUAD. Overall, our results revealed that CCT6A and CHCHD2 were coamplifying and coexpressing with EGFR and were correlated with the unfavorable clinical outcomes of LUAD.

Sedoheptulose Kinase SHPK Expression in Glioblastoma: Emerging Role of the Nonoxidative Pentose Phosphate Pathway in Tumor Proliferation

Glioblastoma (GBM) is the most common form of malignant brain cancer and is considered the deadliest human cancer. Because of poor outcomes in this disease, there is an urgent need for progress in understanding the molecular mechanisms of GBM therapeutic resistance, as well as novel and innovative therapies for cancer prevention and treatment. The pentose phosphate pathway (PPP) is a metabolic pathway complementary to glycolysis, and several PPP enzymes have already been demonstrated as potential targets in cancer therapy. In this work, we aimed to evaluate the role of sedoheptulose kinase (SHPK), a key regulator of carbon flux that catalyzes the phosphorylation of sedoheptulose in the nonoxidative arm of the PPP. SHPK expression was investigated in patients with GBM using microarray data. SHPK was also overexpressed in GBM cells, and functional studies were conducted. SHPK expression in GBM shows a significant correlation with histology, prognosis, and survival. In particular, its increased expression is associated with a worse prognosis. Furthermore, its overexpression in GBM cells confirms an increase in cell proliferation. This work highlights for the first time the importance of SHPK in GBM for tumor progression and proposes this enzyme and the nonoxidative PPP as possible therapeutic targets.

miR-1269a and miR-1269b: Emerging Carcinogenic Genes of the miR-1269 Family

miRNAs play an important role in the occurrence and development of human cancer. Among them, hsa-mir-1269a and hsa-mir-1269b are located on human chromosomes 4 and 17, respectively, and their mature miRNAs (miR-1269a and miR-1269b) have the same sequence. miR-1269a is overexpressed in 9 cancers. The high expression of miR-1269a not only has diagnostic significance in hepatocellular carcinoma and non-small cell lung cancer but also is related to the poor prognosis of cancer patients such as esophageal cancer, hepatocellular carcinoma, and glioma. miR-1269a can target 8 downstream genes (CXCL9, SOX6, FOXO1, ATRX, RASSF9, SMAD7, HOXD10, and VASH1). The expression of miR-1269a is regulated by three non-coding RNAs (RP11-1094M14.8, LINC00261, and circASS1). miR-1269a participates in the regulation of the TGF-β signaling pathway, PI3K/AKT signaling pathway, p53 signaling pathway, and caspase-9-mediated apoptotic pathway, thereby affecting the occurrence and development of cancer. There are fewer studies on miR-1269b compared to miR-1269a. miR-1269b is highly expressed in hepatocellular carcinoma, non-small cell lung cancer, oral squamous cell carcinoma, and pharyngeal squamous cell carcinoma, but miR-1269b is low expressed in gastric cancer. miR-1269b can target downstream genes (METTL3, CDC40, SVEP1, and PTEN) and regulate the PI3K/AKT signaling pathway. In addition, sequence mutations on miR-1269a and miR-1269b can affect their regulation of cancer. The current studies have shown that miR-1269a and miR-1269b have the potential to be diagnostic and prognostic markers for cancer. Future research on miR-1269a and miR-1269b can focus on elucidating more of their upstream and downstream genes and exploring the clinical application value of miR-1269a and miR-1269b.At present, there is no systematic summary of the research on miR-1269a and miR-1269b. This paper aims to comprehensively analyze the abnormal expression, diagnostic and prognostic value, and molecular regulatory pathways of miR-1269a and miR-1269b in multiple cancers. The overview in our work can provide useful clues and directions for future related research.

Long non-coding RNA HOXA11 antisense RNA upregulates spermatogenesis-associated serine-rich 2-like to enhance cisplatin resistance in laryngeal squamous cell carcinoma by suppressing microRNA-518a

Long noncoding RNAs (LncRNAs) are closely associated with the chemoresistance of laryngeal squamous cell carcinoma (LSCC). Previous studies indicated that HOXA11-AS could function as a vital regulator in human cancers. However, the regulatory mechanisms of HOXA11-AS in the chemoresistance of LSCC remain unclear. In this study, it was found that HOXA11-AS expression was upregulated in cisplatin (CDDP)-resistant LSCC tissues and cells. Loss-of-function assays revealed that HOXA11-AS knockdown inhibited the viability, migration, and invasion, but promoted the apoptosis of CDDP-resistant LSCC cells. Meanwhile, we identified miR-518a as a downstream gene of HOXA11-AS in LSCC, and miR-518a silencing reversed the promotive effect of HOXA11-AS knockdown on CDDP sensitivity of LSCC cells. In addition, miR-518a could inhibit spermatogenesis-associated serine-rich 2-like (SPATS2L) expression by direct interaction, and upregulation of SPATS2L abrogated the inhibitory effect of HOXA11-AS silencing or miR-518a overexpression on CDDP resistance of CDDP-resistant LSCC cells. In sum, our results demonstrated that HOXA11-AS enhanced CDDP resistance of LSCC via miR-518a/SPATS2L axis, which might offer novel therapeutic strategies for CDDP-resistant LSCC.

Prognostic and Predictive Biomarkers in Gliomas

Gliomas are the most common central nervous system tumors. New technologies, including genetic research and advanced statistical methods, revolutionize the therapeutic approach to the patient and reveal new points of treatment options. Moreover, the 2021 World Health Organization Classification of Tumors of the Central Nervous System has fundamentally changed the classification of gliomas and incorporated many molecular biomarkers. Given the rapid progress in neuro-oncology, here we compile the latest research on prognostic and predictive biomarkers in gliomas. In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. Finally, we discussed liquid biopsies, which are promising diagnostic, prognostic, and predictive techniques, but further work is needed to implement these novel technologies in clinical practice.