Molecular biomarkers screened by next-generation RNA sequencing for non-sentinel lymph node status prediction in breast cancer patients with metastatic sentinel lymph nodes

Expression of small nucleolar RNA SNORA51 and its clinical significance in hepatocellular carcinoma

Small nucleolar RNA H/ACA Box 51 (SNORA51) is involved in progression of multiple cancers. However, its role in hepatocellular carcinoma (HCC) is still unclear. The aim of the present study was to analyze the expression of SNORA51 in HCC and its clinical significance. A total of 136 patients with HCC who underwent surgery from January 1, 2016 to December 31, 2018 were included. The expression of SNORA51 in cancer tissues and adjacent tissues was compared using reverse transcription-quantitative PCR and bioinformatics methods. Methylation of the SNORA51 promoter in cancer and adjacent tissues was compared using bioinformatics. The relationship between SNORA51 expression levels and clinicopathological characteristics of patients with HCC, in addition to prognosis, was analyzed. The expression of SNORA51 in HCC was significantly higher compared with that in adjacent tissues (P<0.05). starBase demonstrated that higher expression levels of SNORA51 were associated with a significantly worse prognosis of patients with HCC compared with those who had lower expression levels of SNORA51 (P<0.05). Bioinformatics analysis using The University of Alabama at Birmingham Cancer Data Analysis Portal demonstrated that methylation of the SNORA51 promoter region in HCC was significantly decreased compared with adjacent tissues (P<0.05). A high expression of SNORA51 was significantly associated with portal vein tumor thrombus, vascular invasion and TNM stage (P<0.05). The median survival time of patients with high SNORA51 expression was significantly lower compared with those who had low SNORA51 expression (P<0.05). Both uni- and multivariate Cox regression analysis demonstrated that SNORA51 expression was an independent risk factor that significantly worsened the prognosis of patients with HCC (P<0.05). The overexpression of SNORA51 in patients with HCC was significantly associated with a poor prognosis and may be related to the reduced methylation of the SNORA51 promoter region. Therefore, SNORA51 may be a promising biomarker for prediction of the prognosis of patients with HCC and may be a therapeutic target for the treatment of HCC in future.

Single-nucleus RNA sequencing and deep tissue proteomics reveal distinct tumour microenvironment in stage-I and II cervical cancer

BACKGROUND

Cervical cancer (CC) is the 3rd most common cancer in women and the 4th leading cause of deaths in gynaecological malignancies, yet the exact progression of CC is inconclusive, mainly due to the high complexity of the changing tumour microenvironment (TME) at different stages of tumorigenesis. Importantly, a detailed comparative single-nucleus transcriptomic analysis of tumour microenvironment (TME) of CC patients at different stages is lacking.

METHODS

In this study, a total of 42,928 and 29,200 nuclei isolated from the tumour tissues of stage-I and II CC patients and subjected to single-nucleus RNA sequencing (snRNA-seq) analysis. The cell heterogeneity and functions were comparatively investigated using bioinformatic tools. In addition, label-free quantitative mass spectrometry based proteomic analysis was carried out. The proteome profiles of stage-I and II CC patients were compared, and an integrative analysis with the snRNA-seq was performed.

RESULTS

Compared with the stage-I CC (CCI) patients, the immune response relevant signalling pathways were largely suppressed in various immune cells of the stage-II CC (CCII) patients, yet the signalling associated with cell and tissue development was enriched, as well as metabolism for energy production suggested by the upregulation of genes associated with mitochondria. This was consistent with the quantitative proteomic analysis that showed the dominance of proteins promoting cell growth and intercellular matrix development in the TME of CCII group. The interferon-α and γ responses appeared the most activated pathways in many cell populations of the CCI patients. Several collagens, such as COL12A1, COL5A1, COL4A1 and COL4A2, were found significantly upregulated in the CCII group, suggesting their roles in diagnosing CC progression. A novel transcript AC244205.1 was detected as the most upregulated gene in CCII patients, and its possible mechanistic role in CC may be investigated further.

CONCLUSIONS

Our study provides important resources for decoding the progression of CC and set the foundation for developing novel approaches for diagnosing CC and tackling the immunosuppressive TME.

A nomogram based on genotypic and clinicopathologic factors to predict the non-sentinel lymph node metastasis in Chinese women breast cancer patients

Background

Sentinel lymph node biopsy (SLNB) is the standard treatment for breast cancer patients with clinically negative axilla. However, axillary lymph node dissection (ALND) is still the standard care for sentinel lymph node (SLN) positive patients. Clinical data reveals about 40-75% of patients without non-sentinel lymph node (NSLN) metastasis after ALND. Unnecessary ALND increases the risk of complications and detracts from quality of life. In this study, we expect to develop a nomogram based on genotypic and clinicopathologic factors to predict the risk of NSLN metastasis in SLN-positive Chinese women breast cancer patients.

Methods

This retrospective study collected data from 1,879 women breast cancer patients enrolled from multiple centers. Genotypic features contain 96 single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility, therapy and prognosis. SNP genotyping was identified by the quantitative PCR detection platform. The genetic features were divided into two clusters by the mutational stability. The normalized polygenic risk score (PRS) was used to evaluate the combined effect of each SNP cluster. Recursive feature elimination (RFE) based on linear discriminant analysis (LDA) was adopted to select the most useful predictive features, and RFE based on support vector machine (SVM) was used to reduce the number of SNPs. Multivariable logistic regression models (i.e., nomogram) were built for predicting NSLN metastasis. The predictive abilities of three types of model (based on only clinicopathologic information, the integrated clinicopathologic and all SNPs information, and integrated clinicopathologic and significant SNPs information) were compared. Internal and external validations were performed and the area under ROC curves (AUCs) as well as a series of evaluation indicators were assessed.

Results

229 patients underwent SLNB followed by ALND and without any neo-adjuvant therapy, 79 among them (34%) had a positive axillary NSLN metastasis. The LDA-RFE identified the characteristics including lymphovascular invasion, number of positive SLNs, number of negative SLNs and two SNP clusters as significant predictors of NSLN metastasis. Furthermore, the SVM-RFE selected 29 significant SNPs in the prediction of NSLN metastasis. In internal validation, the median AUCs of the clinical and all SNPs combining model, the clinical and 29 significant SNPs combining model, and the clinical model were 0.837, 0.795 and 0.708 respectively. Meanwhile, in external validation, the AUCs of the three models were 0.817, 0.815 and 0.745 respectively.

Conclusion

We present a new nomogram by combining genotypic and clinicopathologic factors to achieve higher sensitivity and specificity comparing with traditional clinicopathologic factors to predict NSLN metastasis in Chinese women breast cancer. It is recommended that more validations are required in prospective studies among different patient populations.

Regulatory roles of RNA modifications in breast cancer

Collectively referred to as the epitranscriptome, RNA modifications play important roles in gene expression control regulating relevant cellular processes. In the last few decades, growing numbers of RNA modifications have been identified not only in abundant ribosomal (rRNA) and transfer RNA (tRNA) but also in messenger RNA (mRNA). In addition, many writers, erasers and readers that dynamically regulate the chemical marks have also been characterized. Correct deposition of RNA modifications is prerequisite for cellular homeostasis, and its alteration results in aberrant transcriptional programs that dictate human disease, including breast cancer, the most frequent female malignancy, and the leading cause of cancer-related death in women. In this review, we emphasize the major RNA modifications that are present in tRNA, rRNA and mRNA. We have categorized breast cancer-associated chemical marks and summarize their contribution to breast tumorigenesis. In addition, we describe less abundant tRNA modifications with related pathways implicated in breast cancer. Finally, we discuss current limitations and perspectives on epitranscriptomics for use in therapeutic strategies against breast and other cancers.

Comprehensive analysis of the cancer driver genes in breast cancer demonstrates their roles in cancer prognosis and tumor microenvironment

Background

Breast cancer is the most common malignancy in women. Cancer driver gene-mediated alterations in the tumor microenvironment are critical factors affecting the biological behavior of breast cancer. The purpose of this study was to identify the expression characteristics and prognostic value of cancer driver genes in breast cancer.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets are used as the training and test sets. Classified according to cancer and paracancerous tissues, we identified differentially expressed cancer driver genes. We further screened prognosis-associated genes, and candidate genes were submitted for the construction of a risk signature. Functional enrichment analysis and transcriptional regulatory networks were performed to search for possible mechanisms by which cancer driver genes affect breast cancer prognosis.

Results

We identified more than 200 differentially expressed driver genes and 27 prognosis-related genes. High-risk group patients had a lower survival rate compared to the low-risk group (P<0.05), and risk signature showed high specificity and sensitivity in predicting the patient prognosis (AUC 0.790). Multivariate regression analysis suggested that risk scores can independently predict patient prognosis. Further, we found differences in PD-1 expression, immune score, and stromal score among different risk groups.

Conclusion

Our study confirms the critical prognosis role of cancer driver genes in breast cancer. The cancer driver gene risk signature may provide a novel biomarker for clinical treatment strategy and survival prediction of breast cancer.

MicroRNA-638 inhibits the progression of breast cancer through targeting HOXA9 and suppressing Wnt/β-cadherin pathway

Background

Previous studies had shown that microRNA-638 (miR-638) exhibited different effects in malignant tumors. Moreover, the function of miR-638 has not been reported in breast cancer. Hence, we designed this research to explore the function of miR-638 in breast cancer.

Methods

Firstly, miR-638 expressions were measured in breast cancer tissues via RT-qPCR. Protein expressions were detected through immunocytochemical (IHC) assay and western blot analysis. Then, Cell Counting Kit-8 (CCK-8) assay and Transwell assay were conducted to observe proliferation and motility of the cells. Dual luciferase assay was performed to confirm the binding site between miR-638 and Homeobox protein Hox-A9 (HOXA9).

Results

Reduced expression of miR-638 was detected in breast cancer. And low miR-638 expression was related to poor prognosis in patients with breast cancer. Functionally, the viability, migration, and invasion of the breast cancer cells were suppressed by miR-638 overexpression. Furthermore, miR-638 can directly bind to HOXA9, and increased expression of HOXA9 was also detected in breast cancer. In particular, HOXA9 upregulation can impair anti-tumor effect of miR-638 in breast cancer, and miR-638 can hinder the Wnt/β-cadherin pathway and epithelial-mesenchymal transition (EMT) in breast cancer.

Conclusion

miR-638 inhibits breast cancer progression through binding to HOXA9.

Metastatic Breast Cancer, Organotropism and Therapeutics: A Review

The final stage of breast cancer involves spreading breast cancer cells to the vital organs like the brain, liver lungs and bones in the process called metastasis. Once the target organ is overtaken by the metastatic breast cancer cells, its usual function is compromised causing organ dysfunction and death. Despite the significant research on breast cancer metastasis, it's still the main culprit of breast cancer-related deaths. Exploring the complex molecular pathways associated with the initiation and progression of breast cancer metastasis could lead to the discovery of more effective ways of treating the devastating phenomenon. The present review article highlights the recent advances to understand the complexity associated with breast cancer metastases, organotropism and therapeutic advances.

IGLL5 is correlated with tumor-infiltrating immune cells in clear cell renal cell carcinoma

Renal cell carcinomas (RCCs) account for about 90% of renal tumors, and their major histological subtype is ccRCC (clear cell RCC). Increasing evidence has indicated that the tumor microenvironment plays a significant role in the occurrence and development of ccRCC. In this study, we used ESTIMATE and CIBERSORT computational methods to calculate the proportion of immune and stromal components and the rate of TICs (tumor‐infiltrating immune cells) in 539 ccRCC samples from The Cancer Genome Atlas database. By examining the intersection of the differentially expressed genes obtained by the protein–protein interaction network and Cox regression analysis, we identified only one overlapping gene: IGLL5 (immunoglobulin lambda‐like polypeptide 5). We report that IGLL5 expression is correlated with TICs. Furthermore, our immunoinfiltration analyses revealed that three types of TIC are positively correlated with IGLL5 expression. IGLL5 may have potential as a prognostic biomarker of ccRCC.

Identification of genes of prognostic value in the ccRCC microenvironment from TCGA database

Background

Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma. Bioinformatics analyses were used to screen candidate genes associated with the prognosis and microenvironment of ccRCC and elucidate the underlying molecular mechanisms of action.

Methods

The gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. The ESTIMATE algorithm was used to compute the immune and stromal scores of patients. Based on the median immune/stromal scores, all patients were sorted into low‐ and high‐immune/stromal score groups. Differentially expressed genes (DEGs) were extracted from high‐ versus low‐immune/stromal score groups and were described using functional annotations and protein‒protein interaction (PPI) network.

Results

Patients in the high‐immune/stromal score group had poorer survival outcome. In total, 95 DEGs (48 upregulated and 47 downregulated genes) were screened from the gene expression profiles of patients with high immune and stromal scores. The genes were primarily involved in six signaling pathways. Among the 95 DEGs, 43 were markedly related to overall survival of patients. The PPI network identified the top 10 hub genes—CD19, CD79A, IL10, IGLL5, POU2AF1, CCL19, AMBP, CCL18, CCL21, and IGJ—and four modules. Enrichment analyses revealed that the genes in the most important module were involved in the B‐cell receptor signaling pathway.

Conclusion

This study mainly revealed the relationship between the ccRCC microenvironment and prognosis of patients. These results also increase the understanding of how gene expression patterns can impact the prognosis and development of ccRCC by modulating the tumor microenvironment. The results could contribute to the search for ccRCC biomarkers and therapeutic targets.

A Gene-Related Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer

Purpose: To develop and validate a gene-related nomogram for predicting the risk of lymph node (LN) metastasis preoperatively in patients with colorectal cancer (CRC). Methods: RNA-seq data of 581 CRC and 51 normal cases with clinical features were downloaded from TCGA database. In the evaluation cohort with 381 CRC cases, the LASSO regression was used to reduce dimensionality of gene signatures extracted to build gene score. A gene-related nomogram was performed based on the multivariable logistic regression analysis. The performance of the nomogram was assessed by the discrimination, calibration, and clinical usefulness not only in the evaluation, but also in the validation cohort with 200 CRC cases. Results: A total of 12,590 differentially expressed genes were selected, in which 59 candidates associated with LN metastasis in differentially expressed genes set were screened by LASSO to form the gene score. Based on the analysis of multivariate logistic regression, the gene-related nomogram showed good calibration and discrimination not only in the evaluation cohort (concordance-index 0.93; 95%CI 0.91-0.96), but also in the validation cohort (concordance-index 0.70; 95%CI 0.63-0.78). The decision curve analysis of the gene-related nomogram also provides constructive guidance for the design of operation plan, preoperatively. Conclusions: The presented genes nomogram may predict the LN metastasis in CRC patients, preoperatively. And 59 hub genes were defined related to LN metastasis of CRC, which can serve as treatment targets for the further study. Preoperative biopsy and gene analysis are needed to develop the operation plan in clinical practice.

Guide snoRNAs: Drivers or Passengers in Human Disease?

In every domain of life, RNA-protein interactions play a significant role in co- and post-transcriptional modifications and mRNA translation. RNA performs diverse roles inside the cell, and therefore any aberrancy in their function can cause various diseases. During maturation from its primary transcript, RNA undergoes several functionally important post-transcriptional modifications including pseudouridylation and ribose 2′-O-methylation. These modifications play a critical role in the stability of the RNA. In the last few decades, small nucleolar RNAs (snoRNAs) were revealed to be one of the main components to guide these modifications. Due to their active links to the nucleoside modification, deregulation in the snoRNA expressions can cause multiple disorders in humans. Additionally, host genes carrying snoRNA-encoding sequences in their introns also show differential expression in disease. Although few reports support a causal link between snoRNA expression and disease manifestation, this emerging field will have an impact on the way we think about biomarkers or identify novel targets for therapy. This review focuses on the intriguing aspect of snoRNAs that function as a guide in post-transcriptional RNA modification, and regulation of their host genes in human disease.

Molecular patterns of cancer colonisation in lymph nodes of breast cancer patients

Lymph node (LN) metastasis is an important prognostic parameter in breast carcinoma, a crucial site for tumour–immune cell interaction and a gateway for further dissemination of tumour cells to other metastatic sites. To gain insight into the underlying molecular changes from the pre-metastatic, via initial colonisation to the fully involved LN, we reviewed transcriptional research along the evolving microenvironment of LNs in human breast cancers patients. Gene expression studies were compiled and subjected to pathway-based analyses, with an emphasis on immune cell-related genes. Of 366 studies, 14 performed genome-wide gene expression comparisons and were divided into six clinical-biological scenarios capturing different stages of the metastatic pathway in the LN, as follows: metastatically involved LNs are compared to their patient-matched primary breast carcinomas (scenario 1) or the normal breast tissue (scenario 2). In scenario 3, uninvolved LNs were compared between LN-positive patients and LN-negative patients. Scenario 4 homed in on the residual uninvolved portion of involved LNs and compared it to the patient-matched uninvolved LNs. Scenario 5 contrasted uninvolved and involved LNs, whilst in scenario 6 involved (sentinel) LNs were assessed between patients with other either positive or negative LNs (non-sentinel).

Gene lists from these chronological steps of LN metastasis indicated that gene patterns reflecting deficiencies in dendritic cells and hyper-proliferation of B cells parallel to tumour promoting pathways, including cell adhesion, extracellular matrix remodelling, cell motility and DNA repair, play key roles in the changing microenvironment of a pro-metastatic to a metastatically involved LN. Similarities between uninvolved LNs and the residual uninvolved portion of involved LNs hinted that LN alterations expose systemic tumour-related immune responses in breast cancer patients. Despite the diverse settings, gene expression patterns at different stages of metastatic colonisation in LNs were recognised and may provide potential avenues for clinical interventions to counteract disease progression for breast cancer patients.

Lymph Nodes in Breast Cancer - What Can We Learn from Translational Research?

Clinical observations about lack of survival benefit after extensive axillary surgery and biological discordance between primary breast tumors and axillary lymph nodes raise the question of the actual metastatic potential of axillary nodal disease. The exploration of intratumoral heterogeneity and detection of genomic differences between the primary and lymph nodes indicate some similarity between the number of mutations in synchronous axillary node metastases and those in the primary lesion, suggesting a favorable prognosis. The hematogenous route of metastasis needs to be considered in findings of different subclones between nodal and distant metastases. Modern tools such as whole-genome sequencing applied in multiple tumor areas may guide more precisely the extent of axillary surgery.

Organotropism: new insights into molecular mechanisms of breast cancer metastasis

Metastasis accounts for 90% of breast cancer mortality. Despite the significant progress made over the past decade in cancer medicine our understanding of metastasis remains limited, therefore preventing and targeting metastasis is not yet possible. Breast cancer cells preferentially metastasize to specific organs, known as “organotropic metastasis”, which is regulated by subtypes of breast cancer, host organ microenvironment, and cancer cells-organ interactions. The cross-talk between cancer cells and host organs facilitates the formation of the premetastatic niche and is augmented by factors released from cancer cells prior to the cancer cells’ arrival at the host organ. Moreover, host microenvironment and specific organ structure influence metastatic niche formation and interactions between cancer cells and local resident cells, regulating the survival of cancer cells and formation of metastatic lesions. Understanding the molecular mechanisms of organotropic metastasis is essential for biomarker-based prediction and prognosis, development of innovative therapeutic strategy, and eventual improvement of patient outcomes. In this review, we summarize the molecular mechanisms of breast cancer organotropic metastasis by focusing on tumor cell molecular alterations, stemness features, and cross-talk with the host environment. In addition, we also update some new progresses on our understanding about genetic and epigenetic alterations, exosomes, microRNAs, circulating tumor cells and immune response in breast cancer organotropic metastasis.

Comprehensive molecular biomarker identification in breast cancer brain metastases

Background

Breast cancer brain metastases (BCBM) develop in about 20–30% of breast cancer (BC) patients. BCBM are associated with dismal prognosis not at least due to lack of valuable molecular therapeutic targets. The aim of the study was to identify new molecular biomarkers and targets in BCBM by using complementary state-of-the-art techniques.

Methods

We compared array expression profiles of three BCBM with 16 non-brain metastatic BC and 16 primary brain tumors (prBT) using a false discovery rate (FDR) p < 0.05 and fold change (FC) > 2. Biofunctional analysis was conducted on the differentially expressed probe sets. High-density arrays were employed to detect copy number variations (CNVs) and whole exome sequencing (WES) with paired-end reads of 150 bp was utilized to detect gene mutations in the three BCBM.

Results

The top 370 probe sets that were differentially expressed between BCBM and both BC and prBT were in the majority comparably overexpressed in BCBM and included, e.g. the coding genes BCL3, BNIP3, BNIP3P1, BRIP1, CASP14, CDC25A, DMBT1, IDH2, E2F1, MYCN, RAD51, RAD54L, and VDR. A number of small nucleolar RNAs (snoRNAs) were comparably overexpressed in BCBM and included SNORA1, SNORA2A, SNORA9, SNORA10, SNORA22, SNORA24, SNORA30, SNORA37, SNORA38, SNORA52, SNORA71A, SNORA71B, SNORA71C, SNORD13P2, SNORD15A, SNORD34, SNORD35A, SNORD41, SNORD53, and SCARNA22. The top canonical pathway was entitled, role of BRCA1 in DNA damage response. Network analysis revealed key nodes as Akt, ERK1/2, NFkB, and Ras in a predicted activation stage. Downregulated genes in a data set that was shared between BCBM and prBT comprised, e.g. BC cell line invasion markers JUN, MMP3, TFF1, and HAS2. Important cancer genes affected by CNVs included TP53, BRCA1, BRCA2, ERBB2, IDH1, and IDH2. WES detected numerous mutations, some of which affecting BC associated genes as CDH1, HEPACAM, and LOXHD1.

Conclusions

Using complementary molecular genetic techniques, this study identified shared and unshared molecular events in three highly aberrant BCBM emphasizing the challenge to detect new molecular biomarkers and targets with translational implications. Among new findings with the capacity to gain clinical relevance is the detection of overexpressed snoRNAs known to regulate some critical cellular functions as ribosome biogenesis.

Electronic supplementary material

The online version of this article (10.1186/s12967-017-1370-x) contains supplementary material, which is available to authorized users.

Prediction of Non-sentinel Node Status in Patients with Melanoma and Positive Sentinel Node Biopsy: An Italian Melanoma Intergroup (IMI) Study

BACKGROUND AND PURPOSE

Approximately 20% of melanoma patients harbor metastases in non-sentinel nodes (NSNs) after a positive sentinel node biopsy (SNB), and recent evidence questions the therapeutic benefit of completion lymph node dissection (CLND). We built a nomogram for prediction of NSN status in melanoma patients with positive SNB.

METHODS

Data on anthropometric and clinicopathological features of patients with cutaneous melanoma who underwent CLND after a positive SNB were collected from nine Italian centers. Multivariate logistic regression was utilized to identify predictors of NSN status in a training set, while model efficiency was validated in a validation set.

RESULTS

Data were available for 1220 patients treated from 2000 through 2016. In the training set (n = 810), the risk of NSN involvement was higher when (1) the primary melanoma is thicker or (2) sited in the trunk/head and neck; (3) fewer nodes are excised and (4) more nodes are involved; and (5) the lymph node metastasis is larger or (6) is deeply located. The model showed high discrimination (area under the receiver operating characteristic curve 0.74, 95% confidence interval [CI] 0.70-0.79) and calibration (Brier score 0.16, 95% CI 0.15-0.17) performance in the validation set (n = 410). The nomogram including these six clinicopathological variables performed significantly better than five other previously published models in terms of both discrimination and calibration.

CONCLUSIONS

Our nomogram could be useful for follow-up personalization in clinical practice, and for patient risk stratification while conducting clinical trials or analyzing their results.

snoRNA and piRNA expression levels modified by tobacco use in women with lung adenocarcinoma

Lung cancer is one of the most frequent types of cancer worldwide. Most patients are diagnosed at advanced stage and thus have poor prognosis. Smoking is a risk factor for lung cancer, however most smokers do not develop lung cancer while 20% of women with lung adenocarcinoma are non-smokers. Therefore, it is possible that these two groups present differences besides the smoking status, including differences in their gene expression signature. The altered expression patterns of non-coding RNAs in complex diseases make them potential biomarkers for diagnosis and treatment. We analyzed data from differentially and constitutively expressed PIWI-interacting RNAs and small nucleolar RNAs from publicly available small RNA high-throughput sequencing data in search of an expression pattern of non-coding RNA that could differentiate these two groups. Here, we report two sets of differentially expressed small non-coding RNAs identified in normal and tumoral tissues of women with lung adenocarcinoma, that discriminate between smokers and non-smokers. Our findings may offer new insights on metabolic alterations caused by tobacco and may be used for early diagnosis of lung cancer.

Transcriptome Analysis of Monozygotic Twin Brothers with Childhood Primary Myelofibrosis

Primary myelofibrosis (PMF) is a chronic myeloproliferative disorder in human bone marrow. Over 50% of patients with myelofibrosis have mutations in JAK2, MPL, or CALR. However, these mutations are rarely detected in children, suggesting a difference in the pathogenesis of childhood PMF. In this study, we investigated the response to drug treatment of a monozygotic twin pair with typical childhood PMF. The twin exhibited different clinical outcomes despite following the same treatment regimen. The transcriptomic profiles of patient samples after drug treatment (E2 and Y2) were significantly different between the twin pair, which is consistent with the observation that the drug treatment was effective only in the younger brother, despite the twin being genetically identical. Bioinformatics analysis of the drug-responsive genes showed that the JAK-STAT pathway was activated in the cured younger brother, which is opposite to the pathway inhibition observed in adult PMF cases following treatment. Moreover, apoptosis and cell cycle processes were both significantly influenced by drug treatment in the sample of younger brother (Y2), implying their potential association with the pathogenesis of childhood PMF. Gene mutations in JAK2, MPL, or CALR were not observed; however, mutations in genes including SRSF2 and SF3B1 occurred in this twin pair with childhood PMF. Gene fusion events were extensively screened in the twin pair samples and the occurrence of IGLV2-14-IGLL5 gene fusion was confirmed. The current study reported at transcriptomic level the different responses of monozygotic twin brothers with childhood PMF to the same androgen/prednisone treatment regimen providing new insights into the potential pathogenesis of childhood PMF for further research and clinical applications.