Cancer genomic research at the crossroads: realizing the changing genetic landscape as intratumoral spatial and temporal heterogeneity becomes a confounding factor

Exploring treatment-driven subclonal evolution of prognostic triple biomarkers: Dual gene fusions and chimeric RNA variants in novel subtypes of acute myeloid leukemia patients with KMT2A rearrangement

Chromosomal rearrangements (CR) initiate leukemogenesis in approximately 50 % of acute myeloid leukemia (AML) patients; however, limited targeted therapies exist due to a lack of accurate molecular and genetic biomarkers of refractory mechanisms during treatment. Here, we investigated the pathological landscape of treatment resistance and relapse in 16 CR-AML patients by monitoring cytogenetic, RNAseq, and genome-wide changes among newly diagnosed, refractory, and relapsed AML. First, in FISH-diagnosed KMT2A (MLL gene, 11q23)/AFDN (AF6, 6q27)-rearrangement, RNA-sequencing identified an unknown CCDC32 (15q15.1)/CBX3 (7p15.2) gene fusion in both newly diagnosed and relapsed samples, which is previously unknown in KMT2A/AFDN-rearranged AML patients. Second, the unreported CCDC32/CBX3 gene fusion significantly affected the expression of wild-type genes of both CCDC32 (essential for embryonic development) and CBX3 (an oncogene for solid tumors) during the relapse, as demonstrated by Quantitative PCR analyses. Third, we further confirmed the existence of triple biomarkers - KMT2A/AFDN (AF6, 6q27) rearrangement, the unknown CCDC32 (15q15.1)/CBX3 (7p15.2) gene fusion and chimeric RNA variants (treatment-resistant leukemic blasts harboring distinct breakpoints) in a 21-year-old male patient of rapid relapsed/refractory AML. Most intriguingly, in this work regarding 16 patients, patients 7 and 20 initially showed the KMT2A/AFDN gene fusion; upon relapse, patient 20 did not show this fusion. On the other hand, patient 7 retained the KMT2A/AFDN fusion at diagnosis and during the relapse, only identified by PCR and Sanger's Sequencing, not by cytogenetics. Interestingly, the chimeric CCDC32/CBX3 gene fusion persisted in the 21-year-old male patient over the diagnostic and relapse phases. Most intriguingly, the overexpression of CCDC32/CBX3 fusion gene in AML patient-specific MV4-11 cells confirms the functional validation, providing experimental evidence of the biological impact of the CCDC32/CBX3 fusion on AML pathogenesis and treatment resistance by promoting cell cycle progression, a mechanism through which AML evolves to become treatment-resistant. All these might exhort differential resistance to treatment. Thus, we found that prognostic and predictive triple biomarkers - KRAS mutated, dual fusions (KMT2A/AFDN, CCDC32/CBX3), and chimeric variants - might evolve with a potential oncogenic role of subclonal evolution for poor clinical outcomes.

The role of NOP58 in prostate cancer progression through SUMOylation regulation and drug response

Background

Prostate cancer is one of the leading causes of cancer-related deaths in men. Its molecular pathogenesis is closely linked to various genetic and epigenetic alterations, including posttranslational modifications like SUMOylation. Identifying biomarkers that predict outcomes and specific therapeutic targets depends on a comprehensive understanding of these processes. With growing interest in SUMOylation as a mechanism affecting prostate cancer-related genes, this study aimed to investigate the central role of SUMOylation in prostate cancer prognostics, focusing on the significance of NOP58.

Methods

We conducted a comprehensive bioinformatics analysis, integrating differential expression analysis, survival analysis, gene set enrichment analysis (GSEA), and single-cell transcriptomic analyses using data from The Cancer Genome Atlas (TCGA). Key genes were identified through intersections of Venn diagrams, Boralta algorithm signatures, and machine learning models. These signaling mechanisms were validated through experimental studies, including immunohistochemical staining and gene ontology analyses.

Results

The dual-gene molecular subtype analysis with SUMO1, SUMO2, and XPO1 genes revealed significant differences in survival outcomes across molecular subtypes, further emphasizing the potential impact of NOP58 on SUMOylation, a key post-translational modification, in prostate cancer. NOP58 overexpression was strongly associated with shorter overall survival (OS), progression-free interval (PFI), and disease-specific death in prostate cancer patients. Immunohistochemical analysis confirmed that NOP58 was significantly overexpressed in prostate cancer tissues compared to normal tissues. ROC curve analysis demonstrated that NOP58 could distinguish prostate cancer from control samples with high diagnostic accuracy. Gene Ontology analysis, along with GSVA and GSEA, suggested that NOP58 may be involved in cell cycle regulation and DNA repair pathways. Moreover, NOP58 knockdown led to increased BCL2 expression and decreased Ki67 levels, promoting apoptosis and inhibiting cell proliferation. Colony formation assays further showed that NOP58 knockdown inhibited, while its overexpression promoted, colony formation, highlighting the critical role of NOP58 in prostate cancer cell growth and survival. Additionally, NOP58 was linked to drug responses, including Methotrexate, Rapamycin, Sorafenib, and Vorinostat.

Conclusion

NOP58 is a key regulator of prostate cancer progression through its mediation of the SUMOylation pathway. Its expression level serves as a reliable prognostic biomarker and an actionable therapeutic target, advancing precision medicine for prostate cancer. Targeting NOP58 may enhance therapeutic efficacy and improve outcomes in oncology.

Mastering the craft: Creating an insightful and widely-cited literature review

The art of constructing an insightful literature review manuscript has witnessed an exemplar in the work of Oz et al (2023), wherein concept progression harmoniously merges with figures and tables. Reflecting on retrospective data science, it is evident that well-cited articles can wield a transformative influence on the Journal Citation Reports Impact Factor score, as exemplified by Robert Weinberg's landmark on cancer (Hanahan and Weinberg, 2011). Here, we aim to spotlight a commendable contribution by Tuba Oz, Ajeet Kaushik, and Małgorzata Kujawska in this issue while pivoting towards identifying the hallmarks of a subpar literature review-elements that hinder rather than promote advancement. The hurdles and roadblocks encountered within subpar literature reviews are multifold. Anticipation of emerging trends, identification of challenges, and exploration of solutions remain conspicuously absent. Original Contributions fail to surface amidst the vast sea of pre-existing literature, with noticeable gaps amplified by the lack of illustrative figures and tables. The manuscript, at times, assumes a skeletal form, reflecting an attempt to accommodate an excess of references, leading to convoluted sentences laden with citations. In contrast, a potent solution lies in adopting a comprehensive approach. A nuanced and critical evaluation of sources can culminate in a robust discussion, surpassing the mere summarization of conclusions drawn by others. This approach, often dismissed, holds the potential to elevate clarity, coherence, and logical flow, ultimately inviting engaged readership and coveted citations. The critical necessity of integrating visionary insights is underscored and achieved through a rigorous analysis of pivotal concepts and innovative ideas. Examples can be harnessed to elucidate the application of these solutions. We advocate a paradigm shift, urging literature review writers to embrace the readers' perspective. A literature review's purpose extends beyond providing a comprehensive panorama; it should illuminate avenues for concept development within a specific field of interest. By achieving this balance, literature reviews stand to captivate a devoted readership, paving the way for manuscripts that are both widely read and frequently cited. The pathway forward requires a fusion of astute analysis and visionary insights, shaping the future of literature review composition.

Pilocytic Astrocytoma-Derived Cells in Peripheral Blood: A Case Report

Imaging limitations, invasive tissue biopsies and poor information over the course of treatment to evaluate ‘real-time’ tumor dynamics justify the emerging use of liquid biopsies in the field of brain tumors. Circulating tumor cells (CTCs) from high-grade astrocytomas might reach the circulation by crossing the blood–brain barrier. Here, for the first time, CTCs cytology in a case of pylocitic astrocytoma is described. An obstructive hydrocephalous due to a lateral mesencephalic tectum mass occluding the Silvio Aqueduct was diagnosed in a young, 18 years old, male. Considering the location of the tumor and the rapid deterioration of the neurological status, it has been decided to urgency treat the patient with ventriculoperitoneal shunting. Magnetic resonance imaging showed a nodular shaped lesion localized within the left lateral mesencephalic tectum. Stereotactic biopsy was not approachable due significant risk of neurological consequences. The diagnosis was performed by blood sampling, a non-invasive procedure for the patient, in order to provide tumor information. Cytopathological features on detected circulating atypical GFAP positive cells led to pilocytic diagnosis confirmed by the patient’s 68 months outcome.

A review on interplay between small RNAs and oxidative stress in cancer progression

Oxidative stress has been known to be the underlying cause in many instances of cancer development. The new aspect of cancer genesis that has caught the attention of many researchers worldwide is its connection to non-coding RNAs (ncRNAs). ncRNAs may not be protein coding, but in light of the more recent discovery of their wide range of functions, the term 'dark matter of the genome' has been rendered inapplicable. There is an extensive mention of colon cancer as an example, where some of these ncRNAs and their manipulations have seen significant progress. As of now, the focus is on discovering a non-invasive, cost-effective method for diagnosis that is easier to monitor and can be conducted before visible symptoms indicate cancer in a patient, by which time it may already be too late. The concept of liquid biopsies has revolutionized recent diagnostic measures. It has been possible to detect circulating parts of the cancer genome or other biomarkers in the patients' bodily fluids, resulting in the effective management of the disease. This has led these ncRNAs to be considered effective therapeutic targets and extrinsic modifications in several tumor types, proven to be effective as therapy. However, there is a vast scope for further understanding and pertinent application of our acquired knowledge and expanding it in enhancing the utilization of ncRNAs for a better prognosis, quicker diagnosis, and improved management of cancer. This review explores the prognosis of cancer and related mutations by scrutinizing small ncRNAs in the disease.

Clinical profile, treatment and outcome of pediatric brain tumors in Serbia in a 10-year period: A national referral institution experience

Objective

This study aimed to evaluate the characteristics of children with primary brain tumors, the effectiveness of treatment modalities, and to detect factors related to the outcome.

Methods

A detailed analysis was performed on a series of 173 pediatric patients treated in a Serbian referral oncology institution between 2007 and 2016, based on their clinical, histological, treatment, and follow-up data.

Results

Mean survival time of all children was 94.5months. 2-, 5- and 10-year overall survival probabilities were 68.8%, 59.4%, and 52.8%, respectively. Patients with supratentorial tumors had longer survival than patients with infratentorial tumors and patients with tumors in both compartments (p = 0.011). Children with the unknown histopathology (brainstem glioma) and high-grade glioma had a shorter life than embryonal tumors, ependymoma, and low-grade glioma (p<0.001). Survival of the children who underwent gross total resection was longer than the children in whom lesser degrees of resection were achieved (p = 0.015). The extent of the disease is a very important parameter found to be associated with survival. Patients with no evidence of disease after surgery had a mean survival of 123 months, compared with 82 months in patients with local residual disease and 55 months in patients with disseminated disease (p<0.001). By the univariate analysis, factors predicting poor outcome in our series were the presentation of disease with hormonal abnormalities, tumor location, and the extent of the disease, while the factors predicting a better outcome were age at the time of diagnosis, presentation of the disease with neurological deficit, and type of resection. By the multivariate analysis, the extent of the disease remained as the only strong adverse risk factor for survival (HR 2.06; 95% CI = 1.38–3.07; p<0.001).

Conclusions

With an organized and dedicated multidisciplinary team, the adequate outcomes can be achieved in a middle-income country setting. The presence of local residual disease after surgery and disseminated disease has a strong negative effect on survival.

Chromoanagenesis Landscape in 10,000 TCGA Patients

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumor's nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct and test a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 unlabeled TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.

Understanding tumour cell heterogeneity and its implication for immunotherapy in liver cancer using single-cell analysis

Over the last decade, precision medicine and immunotherapeutic approaches have become increasingly popular in oncology. Early clinical trials reported promising results, but response rates in phase III clinical trials have been suboptimal. Knowledge gained from subsequent translational studies indicates the importance of targeting the tumour microenvironment to overcome resistance to immunotherapy. In this era of precision medicine, it is crucial to consider inter- as well as intratumoural heterogeneity. Single-cell analysis is a cutting-edge technology that enables us to better define the tumour cell community and to identify potential targets for immunotherapy or combination treatments. This review focuses on single-cell analysis in the context of immunotherapy in liver cancer, including the rationale behind studying hepatocellular carcinoma biology at a single-cell level. Single-cell technologies have the potential to revolutionise our understanding of resistance mechanisms and to guide drug discovery efforts, leading to further advances in personalised medicine.

Biomolecular phenotyping and heterogeneity assessment of mesenchymal stromal cells using label-free Raman spectroscopy

Easy, quantitative measures of biomolecular heterogeneity and high-stratified phenotyping are needed to identify and characterise complex disease processes at the single-cell level, as well as to predict cell fate. Here, we demonstrate how Raman spectroscopy can be used in the difficult-to-assess case of clonal, bone-derived mesenchymal stromal cells (MSCs) to identify MSC lines and group these according to biological function (e.g., differentiation capacity). Biomolecular stratification is achieved using high-precision measures obtained from representative statistical sampling that also enable quantified heterogeneity assessment. Application to primary MSCs and human dermal fibroblasts shows use of these measures as a label-free assay to classify cell sub-types within complex heterogeneous cell populations, thus demonstrating the potential for therapeutic translation, and broad application to the phenotypic characterisation of other cells.

Serum-Based KRASG12/G13 Mutation Detection Using Droplet Digital PCR: Clinical Implications and Limitations in Colorectal Adenocarcinoma With Tumor Heterogeneity

Background

Cell-free DNA (cfDNA) has arisen as an alternative target for evaluating somatic mutations in cancer. KRAS mutation status is critical for targeted therapy in colorectal adenocarcinoma (CRAC). We evaluated KRAS^G12/G13 mutations in cfDNA extracted from serum and compared the results with KRAS^G12/G13 mutations detected in tissue samples. We assessed the clinical significance of KRAS^G12/G13 mutation in serum in regard to recurrence and metastasis of CRAC.

Methods

A total of 146 CRAC patients were enrolled, and KRAS^G12/G13 mutations were evaluated in 146 pairs of serum and tissue samples. In addition, 35 pairs of primary and metastatic CRAC tissue samples were evaluated for KRAS^G12/G13 mutational status.

Results

Detection of KRAS^G12/13 mutation from serum and tissue had a 55% concordance rate, and serum detection had a sensitivity of 39.8%. Detection of the KRAS^G12/13 mutation yielded a 14% discordance rate between primary and metastatic tissue. CRAC patients with mutant KRAS^G12/13 mutation in serum but wild-type KRAS^G12/13 in tissue had concurrent KRAS^G12/13-mutant metastatic tumors, indicating spatial genetic heterogeneity. Changes in serum KRAS^G12/G13 mutation status during postoperative follow-up were associated with recurrence. Conclusion: Although serum detection of the KRAS^G12/13 mutation cannot substitute for detection in tissue, serum testing can support the interpretation of a CRAC patient’s status in regard to concurrent metastasis. Dynamic changes in serum KRAS^G12/13 mutation status during follow-up indicated that cfDNA from serum represents a potential source for monitoring recurrence in CRAC patients.

Identification and Validation of the Immune Subtypes of Lung Adenocarcinoma: Implications for Immunotherapy

Lung adenocarcinoma (LUAD) is a devastating disease with poor patient survival. Cancer immunotherapy has revolutionized the treatment of LUAD, but only a limited number of patients effectively respond to this treatment. Thus, the work to elucidate the LUAD immune heterogeneity could be crucial in developing new immunotherapeutic strategies with better efficacy. Non-negative matrix factorization-based deconvolution was performed to identify robust clusters of 489 LUAD patients in The Cancer Genome Atlas (TCGA) and verify their reproducibility and stability in an independent LUAD cohort of 439 patients from the Gene Expression Omnibus (GEO). We used the graph learning-based dimensionality reduction to visualize the distribution of individual patients. In this study, four reproducible immune subtypes, Clusters 1-4 (C1-C4) associated with distinct gene module signatures, clinicopathological features, molecular and cellular characteristics were identified and validated. The immune-cold subtype, C3, was associated with the Dead event, the most advanced T stage, N stage, TNM stage and the worst prognosis for LUAD patients. Moreover, C3 exhibited the lowest infiltrating levels of B cells, T cell receptor (TCR) repertoire diversity and the highest level of neoantigen and mutation rate among C1-C4. On the other hand, the immune-hot subtype (C4) exhibited the highest infiltration of six types of infiltrating immune cells as well as the greatest leukocyte fraction, TCR and B cell receptor (BCR) repertoire diversity. C1 and C2 subtypes showed diverse clinicopathological and immunological features. Finally, our investigations discovered a complex immune landscape with a scattered immune subtype profile. This work may help inform immunotherapeutic decision-making and design advanced immunotherapy strategies for the treatment of lung cancer.

Chondroitin Sulphate Proteoglycan 4 (NG2/CSPG4) Localization in Low- and High-Grade Gliomas

BACKGROUND

Neuron glial antigen 2 or chondroitin sulphate proteoglycan 4 (NG2/CSPG4) is expressed by immature precursors/progenitor cells and is possibly involved in malignant cell transformation. The aim of this study was to investigate its role on the progression and survival of sixty-one adult gliomas and nine glioblastoma (GB)-derived cell lines.

METHODS

NG2/CSPG4 protein expression was assessed by immunohistochemistry and immunofluorescence. Genetic and epigenetic alterations were detected by molecular genetic techniques.

RESULTS

NG2/CSPG4 was frequently expressed in IDH-mutant/1p19q-codel oligodendrogliomas (59.1%) and IDH-wild type GBs (40%) and rarely expressed in IDH-mutant or IDH-wild type astrocytomas (14.3%). Besides tumor cells, NG2/CSPG4 immunoreactivity was found in the cytoplasm and/or cell membranes of reactive astrocytes and vascular pericytes/endothelial cells. In GB-derived neurospheres, it was variably detected according to the number of passages of the in vitro culture. In GB-derived adherent cells, a diffuse positivity was found in most cells. NG2/CSPG4 expression was significantly associated with EGFR gene amplification (p = 0.0005) and poor prognosis (p = 0.016) in astrocytic tumors.

CONCLUSION

The immunoreactivity of NG2/CSPG4 provides information on the timing of the neoplastic transformation and could have prognostic and therapeutic relevance as a promising tumor-associated antigen for antibody-based immunotherapy in patients with malignant gliomas.

In vivo modeling of metastatic human high-grade serous ovarian cancer in mice

Metastasis is responsible for 90% of human cancer mortality, yet it remains a challenge to model human cancer metastasis in vivo. Here we describe mouse models of high-grade serous ovarian cancer, also known as high-grade serous carcinoma (HGSC), the most common and deadliest human ovarian cancer type. Mice genetically engineered to harbor Dicer1 and Pten inactivation and mutant p53 robustly replicate the peritoneal metastases of human HGSC with complete penetrance. Arising from the fallopian tube, tumors spread to the ovary and metastasize throughout the pelvic and peritoneal cavities, invariably inducing hemorrhagic ascites. Widespread and abundant peritoneal metastases ultimately cause mouse deaths (100%). Besides the phenotypic and histopathological similarities, mouse HGSCs also display marked chromosomal instability, impaired DNA repair, and chemosensitivity. Faithfully recapitulating the clinical metastases as well as molecular and genomic features of human HGSC, this murine model will be valuable for elucidating the mechanisms underlying the development and progression of metastatic ovarian cancer and also for evaluating potential therapies.

Rarely does an experimental model fully replicate the clinical metastases of a human malignancy. Faithfully representing the clinical metastases of human high-grade serous ovarian cancer with complete penetrance, coupled with histopathological, molecular, and genomic similarities, these mouse models, particularly one harboring mutant p53, will be vital to elucidating the underlying pathogenesis of human ovarian cancer. In-depth understanding of the development and progression of ovarian cancer is crucial to medical advances in the early detection, effective treatment, and prevention of ovarian cancer. Also, these robust mouse models, as well as cell lines established from the mouse primary and metastatic tumors, will serve as useful preclinical tools to evaluate therapeutic target genes and new therapies in ovarian cancer.

Evaluation of X-Ray Repair Cross-Complementing Family Members as Potential Biomarkers for Predicting Progression and Prognosis in Hepatocellular Carcinoma

The X-ray repair cross-complementing (XRCC) gene family has been revealed to participate in the carcinogenesis and development of numerous cancers. However, the expression profiles and prognostic values of XRCCs (XRCC1-6) in hepatocellular carcinoma (HCC) have not been explored up to now. The transcriptional levels of XRCCs in primary HCC tissues were analyzed by UALCAN and GEPIA. The relationship between XRCCs expression and HCC clinical characteristics was evaluated using UALCAN. Moreover, the prognostic values of XRCCs expression and mutations in HCC patients were investigated via the GEPIA and cBioPortal, respectively. Last but not least, the functions and pathways of XRCCs in HCC were also predicted by cBioPortal and DVAID. The transcriptional levels of all XRCCs in HCC tissues were notably elevated compared with normal liver tissues. Meanwhile, upregulated XRCCs expression was positively associated with clinical stages and tumor grades of HCC patients. Survival analysis using the GEPIA database revealed that high transcription levels of XRCC2/3/4/5/6 were associated with lower overall survival (OS) and high transcription levels of XRCC1/2/3/6 were correlated with poor disease-free survival (DFS) in HCC patients. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated the possible mechanisms of XRCCs and their associated genes participating in the oncogenesis of HCC. Our findings systematically elucidate the expression profiles and distinct prognostic values of XRCCs in HCC, which might provide promising therapeutic targets and novel prognostic biomarkers for HCC patients.

Breathing Signature as Vitality Score Index Created by Exercises of Qigong: Implications of Artificial Intelligence Tools Used in Traditional Chinese Medicine

Rising concerns about the short- and long-term detrimental consequences of administration of conventional pharmacopeia are fueling the search for alternative, complementary, personalized, and comprehensive approaches to human healthcare. Qigong, a form of Traditional Chinese Medicine, represents a viable alternative approach. Here, we started with the practical, philosophical, and psychological background of Ki (in Japanese) or Qi (in Chinese) and their relationship to Qigong theory and clinical application. Noting the drawbacks of the current state of Qigong clinic, herein we propose that to manage the unique aspects of the Eastern 'non-linearity' and 'holistic' approach, it needs to be integrated with the Western "linearity" "one-direction" approach. This is done through developing the concepts of "Qigong breathing signatures," which can define our life breathing patterns associated with diseases using machine learning technology. We predict that this can be achieved by establishing an artificial intelligence (AI)-Medicine training camp of databases, which will integrate Qigong-like breathing patterns with different pathologies unique to individuals. Such an integrated connection will allow the AI-Medicine algorithm to identify breathing patterns and guide medical intervention. This unique view of potentially connecting Eastern Medicine and Western Technology can further add a novel insight to our current understanding of both Western and Eastern medicine, thereby establishing a vitality score index (VSI) that can predict the outcomes of lifestyle behaviors and medical conditions.

Cancer Niche as a Garbage Disposal Machine: Implications of TCM-Mediated Balance of Body-Disease for Treatment of Cancer

Cancer epidemic led to worldwide to search for a new “game changer” concept to govern cancer research and cancer treatment. Western medicine-based cancer research has been extending the impasse without resolution in sigh for improving survival of patients with solid malignant tumors in the last four decades due to heterogeneity in cancer tissues. Such a deadlock charts a course to learn lessons from the developing countries, directly or indirectly to complement the exhausted Western medicine. We propose a new concept of “Cancer niche as a garbage disposal machine” with implications of traditional Chinese medicine-mediated restoration of normal balance between body and disease to bring the fight against cancer under control.

Comprehensive analysis of peroxiredoxins expression profiles and prognostic values in breast cancer

BACKGROUND

The peroxiredoxins (PRDXs) gene family has been demonstrated to participate in carcinogenesis and development of numerous cancers and the prognostic values in several cancers have been evaluated already. Purpose of our research is to explore the expression profiles and prognostic values of PRDXs in breast cancer (BrCa).

METHODS

The transcriptional levels of PDRX family members in primary BrCa tissues and their association with intrinsic subclasses were analyzed using UALCAN database. Then, the genetic alterations of PDRXs were examined by cBioPortal database. Moreover, the prognostic values of PRDXs in BrCa patients were investigated via the Kaplan-Meier plotter.

RESULTS

The transcriptional levels of most PRDXs family members in BrCa tissues were significantly elevated compared with normal breast tissues. Meanwhile, dysregulated PRDXs expression was associated with intrinsic subclasses of BrCa. Besides, copy number alterations (CNA) of PRDXs positively regulated their mRNA expressions. Furthermore, high mRNA expression of PRDX4/6 was significantly associated with poor overall survival (OS) in BrCa patients, while high mRNA expression of PRDX3 was notably related to favorable OS. Simultaneously, high mRNA expression of PRDX1/2/4/5/6 was significantly associated with shorter relapse-free survival (RFS) in BrCa patients, while high mRNA expression of PRDX3 was notably related to favorable RFS. In addition, the prognostic value of PRDXs in the different clinicopathological features based on intrinsic subclasses and chemotherapeutic treatment of BrCa patients was further assessed in the KM plotter database.

CONCLUSION

Our findings systematically elucidate the expression profiles and distinct prognostic values of PRDXs in BrCa, which might provide novel therapeutic targets and potential prognostic biomarkers for BrCa patients.

Identification of five hub genes as monitoring biomarkers for breast cancer metastasis in silico

BACKGROUND

Breast cancer is one of the most common endocrine cancers among females worldwide. Distant metastasis of breast cancer is causing an increasing number of breast cancer-related deaths. However, the potential mechanisms of metastasis and candidate biomarkers remain to be further explored.

RESULTS

The gene expression profiles of GSE102484 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to screen for the most potent gene modules associated with the metastatic risk of breast cancer, and a total of 12 modules were identified based on the analysis. In the most significant module (R2 = 0.68), 21 network hub genes (MM > 0.90) were retained for further analyses. Next, protein-protein interaction (PPI) networks were used to further explore the biomarkers with the most interactions in gene modules. According to the PPI networks, five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) were identified as key genes associated with breast cancer progression. Furthermore, the prognostic value and differential expression of these genes were validated based on data from The Cancer Genome Atlas (TCGA) and Kaplan-Meier (KM) Plotter. Receiver operating characteristic (ROC) curve analysis revealed that the mRNA expression levels of these five hub genes showed excellent diagnostic value for breast cancer and adjacent tissues. Moreover, these five hub genes were significantly associated with worse distant metastasis-free survival (DMFS) in the patient cohort based on KM Plotter.

CONCLUSION

Five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) associated with the risk of distant metastasis were extracted for further research, which might be used as biomarkers to predict distant metastasis of breast cancer.

Recent Advances in Cancer Stem Cell-Targeted Immunotherapy

Cancer stem cells (CSCs) are one of the reasons for the relapse of cancer cells and metastasis. They have drug resistance against most chemotherapeutic agents. CSCs are also responsible for tumor cell heterogeneity and cause minimal residual disease. In order to achieve complete regression of tumors, CSCs have to be targeted. Recent advances in immunotherapies have shown promising outcomes in curing cancer, which are also applicable to target CSCs. CSCs express immune markers and exhibit specific immune characteristics in various cancers, which can be used in immunotherapies to target CSCs in the tumor microenvironment. Recently, various strategies have been used to target CSCs. Adaptive T-cells, dendritic cell (DC)-based vaccines, oncolytic viruses, immune checkpoint inhibitors, and combination therapies are now being used to target CSCs. Here, we discuss the feasibility of these immunological approaches and the recent trends in immunotherapies to target CSCs.

Relapse pathway of glioblastoma revealed by single-cell molecular analysis

Glioblastoma multiforme (GBM) remains an incurable brain tumor. The highly malignant behavior of GBM may, in part, be attributed to its intraclonal genetic and phenotypic diversity (subclonal evolution). Identifying the molecular pathways driving GBM relapse may provide novel, actionable targets for personalized diagnosis, characterization of prognosis and improvement of precision therapy. We screened single-cell transcriptomes, namely RNA-seq data of primary and relapsed GBM tumors from a patient, to define the molecular profile of relapse. Characterization of hundreds of individual tumor cells identified three mutated genes within single cells, involved in the RAS/GEF GTP-dependent signaling pathway. The identified molecular pathway was further verified by meta-analysis of RNA-seq data from more than 3000 patients. This study showed that single-cell molecular analysis overcomes the inherent heterogeneity of bulk tumors with respect to defining tumor subclonal evolution relevant to GBM relapse.

Precision Technique for Splenectomy Limits Mouse Stress Responses for Accurate and Realistic Measurements for Investigating Inflammation and Immunity

Splenectomy in an animal model requires a standardized technique utilizing best practice to avoid variability which can result in adverse impact to the animal resulting in flawed physiologic responses simply due to technique rather than to the studied variables. In the case of the spleen, often investigators are analyzing the animal immune or inflammatory responses. Surgical splenectomy involves many variables from the training and expertise of the surgeon, which directly correlates to surgical technique to the length of operation and ease of the procedure. This operation, in turn, impacts blood loss and insensible fluid losses, sterile technique, unintended trauma to the spleen and surrounding organs, the length of the incision and the duration of the operation with more prolonged exposure to anesthetic agents. All these variables ultimately play a significant role in the experiment since they directly affect the response of the model in terms of inflammation, immune activation, or even suppression. Undesired variables such as these go unnoticed and lead to inaccurate and misleading data.

Cancer Subclones Derived from the Patient's Head and Neck Squamous Cell Carcinoma Tumor Stem Cells for the Screening of Personalized Antitumor Immunotherapy and Chemotherapy

Studying on subclonal evolution of cancer stem cells can help illustrate how the immune system recognizes tumor cells, leading to subclonal treatment by immune-based therapies. Here, we discuss that cancer subclones derived from the patient's head and neck squamous cell carcinoma tumor stem cells can be used for the screening of personalized antitumor immunotherapy and chemotherapy, to maximize benefits and to minimize the adversary effects, toward personalized or precision medicine. We propose a "wait-and-watch" scheme for monitoring a lifetime cancer stem cell subclonal development evolved with local environments to cancer.

Advances in the classification of pediatric brain tumors through DNA methylation profiling: From research tool to frontline diagnostic

Despite significant improvements in pediatric brain tumor therapy and outcome, too many children still die of disease, and too many survivors experience significant sequelae as a result of conventional therapies. The molecular characterization of pediatric brain tumors has afforded tremendous insight into the basic biology and clinical management of these deadly childhood diseases. Genomic, epigenomic, and transcriptional profiling have facilitated the identification of significant heterogeneity among previously uniform disease entities. In particular, DNA methylation profiling has emerged as a robust tool for identifying key disease-specific subgroups that can exhibit distinct clinical outcomes. These approaches, which also complement classic histologic techniques, can suggest key mechanistic underpinnings of tumorigenesis and open the door for better informed and more tailored therapy. By leveraging the results of large-scale classifications of disease cohorts, novel driver mutations and pathways can be uncovered, enabling the generation of faithful animal models, promoting targeted drug design, informing developmental biology, and ultimately translating into improved clinical management. In this review, progress in the epigenetic classification of common malignant pediatric brain tumors, namely medulloblastoma, ependymoma, high-grade glioma, atypical teratoid/rhabdoid tumor, and central nervous system embryonal tumors, will be discussed, and the potential role of DNA methylation profiling as a frontline diagnostic modality will be emphasized.

Adverse genomic alterations and stemness features are induced by field cancerization in the microenvironment of hepatocellular carcinomas

Hepatocellular Carcinoma (HCC) commonly develops in chronically damaged liver tissues. The resulting regenerative and inflammatory processes create an adverse milieu that promotes tumor-initiation and progression. A better understanding of the hepatic tumor-microenvironment interaction might infer profound therapeutic implications.

Integrative whole genome and transcriptome analyses of different tumor regions, the invasive tumor border and tumor-surrounding liver (SL) were performed to identify associated molecular alterations and integrated with our existing HCC database. Expression levels and localization of established CSC markers were assessed in pre-neoplastic lesions and confirmed in two independent patient cohorts using qRT-PCR, immunohistochemistry and immunofluorescence.

Our results indicate that genomic and transcriptomic profiles between SL and different tumor regions are quite distinct. Progressive increase in genetic alterations and activation of pathways related to proliferation as well as apoptosis were observed in the tumor tissue, while activation of stemness markers was present in cirrhotic SL and continuously decreased from pre-neoplastic lesions to HCC. Interestingly, the invasive tumor border was characterized by inflammatory and EMT-related gene sets as well as activation of pro-survival signaling. Consistently, integration of gene expression signatures with two independent HCC databases containing 300 HCCs revealed that border signatures are predictive of HCC patient survival.

Prognostic significance of the permissive liver microenvironment might be a consequence of a pro-oncogenic field effect that is caused by chronic regenerative processes. Activation of key oncogenic features and immune-response signaling indicates that the cross-talk between tumor and microenvironment might be a promising therapeutic and/or preventive target.

Spatiotemporal switching signals for cancer stem cell activation in pediatric origins of adulthood cancer: Towards a watch-and-wait lifetime strategy for cancer treatment

Pediatric origin of cancer stem cell hypothesis holds great promise and potential in adult cancer treatment, however; the road to innovation is full of obstacles as there are plenty of questions left unanswered. First, the key question is to characterize the nature of such stem cells (concept). Second, the quantitative imaging of pediatric stem cells should be implemented (technology). Conceptually, pediatric stem cell origins of adult cancer are based on the notion that plasticity in early life developmental programming evolves local environments to cancer. Technologically, such imaging in children is lacking as all imaging is designed for adult patients. We postulate that the need for quantitative imaging to measure space-time changes of plasticity in early life developmental programming in children may trigger research and development of the imaging technology. Such quantitative imaging of pediatric origin of adulthood cancer will help develop a spatiotemporal monitoring system to determine cancer initiation and progression. Clinical validation of such speculative hypothesis-that cancer originates in a pediatric environment-will help implement a wait-and-watch strategy for cancer treatment.

Signatures of positive selection reveal a universal role of chromatin modifiers as cancer driver genes

Tumors are composed of an evolving population of cells subjected to tissue-specific selection, which fuels tumor heterogeneity and ultimately complicates cancer driver gene identification. Here, we integrate cancer cell fraction, population recurrence, and functional impact of somatic mutations as signatures of selection into a Bayesian model for driver prediction. We demonstrate that our model, cDriver, outperforms competing methods when analyzing solid tumors, hematological malignancies, and pan-cancer datasets. Applying cDriver to exome sequencing data of 21 cancer types from 6,870 individuals revealed 98 unreported tumor type-driver gene connections. These novel connections are highly enriched for chromatin-modifying proteins, hinting at a universal role of chromatin regulation in cancer etiology. Although infrequently mutated as single genes, we show that chromatin modifiers are altered in a large fraction of cancer patients. In summary, we demonstrate that integration of evolutionary signatures is key for identifying mutational driver genes, thereby facilitating the discovery of novel therapeutic targets for cancer treatment.

Future perspectives of circulating tumor DNA in colorectal cancer

Tumor biopsy is currently the gold standard for diagnosis and in determining cell signaling pathways involved in the development of treatment resistance. However, there are major challenges with this technique, including the need for serial sampling to monitor treatment resistance, which is invasive and also has the potential for selection bias due to intra-tumoral and inter-tumoral heterogeneity. These challenges highlight the need for more effective methods for obtaining Tumor samples. Liquid biopsy analyzes genetic material or tumor cells shed into the blood from the primary tumor and metastatic sites and consequently provides a comprehensive, real-time picture of the tumor burden in an individual patient. Indeed, liquid biopsy has the potential to revolutionize cancer management. Here, we review recent studies on the potential clinical applications of liquid biopsy using circulating tumor DNA in colorectal cancer, including screening, diagnosis, detection of minimal residual disease after surgery, detection of recurrence, prognosis, predicting treatment response, monitoring tumor burden or response during treatment, and tracking resistance. We also discuss recent data demonstrating the utility of detecting KRAS-mutated circulating tumor DNA, both at diagnosis to determine an appropriate treatment strategy and during anti-epidermal growth factor receptor therapy to predict treatment resistance. The future integration of liquid biopsy into clinical practice is discussed, together with alternative approaches and key questions that need to be answered in future clinical studies before this technology can be implemented and used routinely.

From big data to diagnosis and prognosis: gene expression signatures in liver hepatocellular carcinoma

Background

Liver hepatocellular carcinoma accounts for the overwhelming majority of primary liver cancers and its belated diagnosis and poor prognosis call for novel biomarkers to be discovered, which, in the era of big data, innovative bioinformatics and computational techniques can prove to be highly helpful in.

Methods

Big data aggregated from The Cancer Genome Atlas and Natural Language Processing were integrated to generate differentially expressed genes. Relevant signaling pathways of differentially expressed genes went through Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes and Panther pathway enrichment analysis and protein-protein interaction network. The pathway ranked high in the enrichment analysis was further investigated, and selected genes with top priority were evaluated and assessed in terms of their diagnostic and prognostic values.

Results

A list of 389 genes was generated by overlapping genes from The Cancer Genome Atlas and Natural Language Processing. Three pathways demonstrated top priorities, and the one with specific associations with cancers, ‘pathways in cancer,’ was analyzed with its four highlighted genes, namely, BIRC5, E2F1, CCNE1, and CDKN2A, which were validated using Oncomine. The detection pool composed of the four genes presented satisfactory diagnostic power with an outstanding integrated AUC of 0.990 (95% CI [0.982–0.998], P < 0.001, sensitivity: 96.0%, specificity: 96.5%). BIRC5 (P = 0.021) and CCNE1 (P = 0.027) were associated with poor prognosis, while CDKN2A (P = 0.066) and E2F1 (P = 0.088) demonstrated no statistically significant differences.

Discussion

The study illustrates liver hepatocellular carcinoma gene signatures, related pathways and networks from the perspective of big data, featuring the cancer-specific pathway with priority, ‘pathways in cancer.’ The detection pool of the four highlighted genes, namely BIRC5, E2F1, CCNE1 and CDKN2A, should be further investigated given its high evidence level of diagnosis, whereas the prognostic powers of BIRC5 and CCNE1 are equally attractive and worthy of attention.

Tissue Elasticity Bridges Cancer Stem Cells to the Tumor Microenvironment Through microRNAs: Implications for a "Watch-and-Wait" Approach to Cancer

BACKGROUND

Targeting the tumor microenvironment (TME) through which cancer stem cells (CSCs) crosstalk for cancer initiation and progression, may open new treatments different from those centered on the original hallmarks of cancer genetics thereby implying a new approach for suppression of TME driven activation of CSCs. Cancer is dynamic, heterogeneous, evolving with the TME and can be influenced by tissue-specific elasticity. One of the mediators and modulators of the crosstalk between CSCs and mechanical forces is miRNA, which can be developmentally regulated, in a tissue- and cellspecific manner.

OBJECTIVE

Here, based on our previous data, we provide a framework through which such gene expression changes in response to external mechanical forces can be understood during cancer progression. Recognizing the ways mechanical forces regulate and affect intracellular signals with applications in cancer stem cell biology. Such TME-targeted pathways shed new light on strategies for attacking cancer stem cells with fewer side effects than traditional gene-based treatments for cancer, requiring a "watchand- wait" approach. We attempt to address both normal brain microenvironment and tumor microenvironment as both works together, intertwining in pathology and physiology - a balance that needs to be maintained for the "watch-and-wait" approach to cancer.

CONCLUSION

This review connected the subjects of tissue elasticity, tumor microenvironment, epigenetic of miRNAs, and stem-cell biology that are very relevant in cancer research and therapy. It attempts to unify apparently separate entities in a complex biological web, network, and system in a realistic and practical manner, i.e., to bridge basic research with clinical application.

Functional and genetic deconstruction of the cellular origin in liver cancer

During the past decade, research on primary liver cancers has particularly highlighted the uncommon plasticity of differentiated parenchymal liver cells (that is, hepatocytes and cholangiocytes (also known as biliary epithelial cells)), the role of liver progenitor cells in malignant transformation, the importance of the tumour microenvironment and the molecular complexity of liver tumours. Whereas other reviews have focused on the landscape of genetic alterations that promote development and progression of primary liver cancers and the role of the tumour microenvironment, the crucial importance of the cellular origin of liver cancer has been much less explored. Therefore, in this Review, we emphasize the importance and complexity of the cellular origin in tumour initiation and progression, and attempt to integrate this aspect with recent discoveries in tumour genomics and the contribution of the disrupted hepatic microenvironment to liver carcinogenesis.

The Tip of the Iceberg: Clinical Implications of Genomic Sequencing Projects in Head and Neck Cancer

Recent genomic sequencing studies have provided valuable insight into genetic aberrations in head and neck squamous cell carcinoma. Despite these great advances, certain hurdles exist in translating genomic findings to clinical care. Further correlation of genetic findings to clinical outcomes, additional analyses of subgroups of head and neck cancers and follow-up investigation into genetic heterogeneity are needed. While the development of targeted therapy trials is of key importance, numerous challenges exist in establishing and optimizing such programs. This review discusses potential upcoming steps for further genetic evaluation of head and neck cancers and implementation of genetic findings into precision medicine trials.