scholarly journals Differential expression patterns of housekeeping genes increase diagnostic and prognostic value in lung cancer

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4719 ◽  
Author(s):  
Yu-Chun Chang ◽  
Yan Ding ◽  
Lingsheng Dong ◽  
Lang-Jing Zhu ◽  
Roderick V. Jensen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Overall Survival ◽  
Differential Expression ◽  
Expression Pattern ◽  
Expression Patterns ◽  
Housekeeping Genes ◽  
Normal Lung ◽  
Rna Seq ◽  
Lung Cancers

Background Using DNA microarrays, we previously identified 451 genes expressed in 19 different human tissues. Although ubiquitously expressed, the variable expression patterns of these “housekeeping genes” (HKGs) could separate one normal human tissue type from another. Current focus on identifying “specific disease markers” is problematic as single gene expression in a given sample represents the specific cellular states of the sample at the time of collection. In this study, we examine the diagnostic and prognostic potential of the variable expressions of HKGs in lung cancers. Methods Microarray and RNA-seq data for normal lungs, lung adenocarcinomas (AD), squamous cell carcinomas of the lung (SQCLC), and small cell carcinomas of the lung (SCLC) were collected from online databases. Using 374 of 451 HKGs, differentially expressed genes between pairs of sample types were determined via two-sided, homoscedastic t-test. Principal component analysis and hierarchical clustering classified normal lung and lung cancers subtypes according to relative gene expression variations. We used uni- and multi-variate cox-regressions to identify significant predictors of overall survival in AD patients. Classifying genes were selected using a set of training samples and then validated using an independent test set. Gene Ontology was examined by PANTHER. Results This study showed that the differential expression patterns of 242, 245, and 99 HKGs were able to distinguish normal lung from AD, SCLC, and SQCLC, respectively. From these, 70 HKGs were common across the three lung cancer subtypes. These HKGs have low expression variation compared to current lung cancer markers (e.g., EGFR, KRAS) and were involved in the most common biological processes (e.g., metabolism, stress response). In addition, the expression pattern of 106 HKGs alone was a significant classifier of AD versus SQCLC. We further highlighted that a panel of 13 HKGs was an independent predictor of overall survival and cumulative risk in AD patients. Discussion Here we report HKG expression patterns may be an effective tool for evaluation of lung cancer states. For example, the differential expression pattern of 70 HKGs alone can separate normal lung tissue from various lung cancers while a panel of 106 HKGs was a capable class predictor of subtypes of non-small cell carcinomas. We also reported that HKGs have significantly lower variance compared to traditional cancer markers across samples, highlighting the robustness of a panel of genes over any one specific biomarker. Using RNA-seq data, we showed that the expression pattern of 13 HKGs is a significant, independent predictor of overall survival for AD patients. This reinforces the predictive power of a HKG panel across different gene expression measurement platforms. Thus, we propose the expression patterns of HKGs alone may be sufficient for the diagnosis and prognosis of individuals with lung cancer.

scholarly journals Meta-analysis of RNA-seq studies reveals genes responsible for life stage-dominant functions in Schistosoma mansoni

2018 ◽  
Author(s):  
Zhigang Lu ◽  
Matthew Berriman
Keyword(s):  
Gene Expression ◽  
Schistosoma Mansoni ◽  
Differential Expression ◽  
Meta Analysis ◽  
Life Stage ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
Housekeeping Genes ◽  
Life Stages ◽  
Rna Seq

AbstractBackgroundSince the genome of the parasitic flatworm Schistosoma mansoni was sequenced in 2009, various RNA-seq studies have been conducted to investigate differential gene expression between certain life stages. Based on these studies, the overview of gene expression in all life stages can improve our understanding of S. mansoni genome biology.Methodspublicly available RNA-seq data covering all life stages and gonads were mapped to the latest S. mansoni genome. Read counts were normalised across all samples and differential expression analysis was preformed using the generalized linear model (GLM) approach.Resultswe revealed for the first time the dissimilarities among all life stages. Genes that are abundantly-expressed in all life stages, as well as those preferentially-expressed in certain stage(s), were determined. The latter reveals genes responsible for stage-dominant functions of the parasite, which can be a guidance for the investigation and annotation of gene functions. In addition, distinct differential expression patterns were observed between adjacent life stages, which not only correlate well with original individual studies, but also provide additional information on changes in gene expression during parasite transitions. Furthermore, thirteen novel housekeeping genes across all life stages were identified, which is valuable for quantitative studies (e.g., qPCR).Conclusionsthe metaanalysis provides valuable information on the expression and potential functions of S. mansoni genes across all life stages, and can facilitate basic as well as applied research for the community.

scholarly journals Selection and Validation of Reference Genes for RT-qPCR Analysis in Spinacia oleracea under Abiotic Stress

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hao Xie ◽  
Bo Li ◽  
Yu Chang ◽  
Xiaoyan Hou ◽  
Yue Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Reference Genes ◽  
18S Rrna ◽  
Spinacia Oleracea ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Housekeeping Genes ◽  
Qpcr Analysis ◽  
The Stability

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is an accurate and convenient method for mRNA quantification. Selection of optimal reference gene(s) is an important step in RT-qPCR experiments. However, the stability of housekeeping genes in spinach (Spinacia oleracea) under various abiotic stresses is unclear. Evaluating the stability of candidate genes and determining the optimal gene(s) for normalization of gene expression in spinach are necessary to investigate the gene expression patterns during development and stress response. In this study, ten housekeeping genes, 18S ribosomal RNA (18S rRNA), actin, ADP ribosylation factor (ARF), cytochrome c oxidase subunit 5C (COX), cyclophilin (CYP), elongation factor 1-alpha (EF1α), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), histone H3 (H3), 50S ribosomal protein L2 (RPL2), and tubulin alpha chain (TUBα) from spinach, were selected as candidates in roots, stems, leaves, flowers, and seedlings in response to high temperature, CdCl2, NaCl, NaHCO3, and Na2CO3 stresses. The expression of these genes was quantified by RT-qPCR and evaluated by NormFinder, BestKeeper, and geNorm. 18S rRNA, actin, ARF, COX, CYP, EF1α, GAPDH, H3, and RPL2 were detected as optimal reference genes for gene expression analysis of different organs and stress responses. The results were further confirmed by the expression pattern normalized with different reference genes of two heat-responsive genes. Here, we optimized the detection method of the gene expression pattern in spinach. Our results provide the optimal candidate reference genes which were crucial for RT-qPCR analysis.

Integrative, normalization-insusceptible statistical analysis of RNA-Seq data, with improved differential expression and unbiased downstream functional analysis

2020 ◽  
Author(s):  
Dionysios Fanidis ◽  
Panagiotis Moulos
Keyword(s):  
Gene Expression ◽  
Statistical Analysis ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Expression Patterns ◽  
Superior Performance ◽  
P Value ◽  
Rna Seq ◽  
Daily Lives ◽  
Differential Gene

Abstract The study of differential gene expression patterns through RNA-Seq comprises a routine task in the daily lives of molecular bioscientists, who produce vast amounts of data requiring proper management and analysis. Despite widespread use, there are still no widely accepted golden standards for the normalization and statistical analysis of RNA-Seq data, and critical biases, such as gene lengths and problems in the detection of certain types of molecules, remain largely unaddressed. Stimulated by these unmet needs and the lack of in-depth research into the potential of combinatorial methods to enhance the analysis of differential gene expression, we had previously introduced the PANDORA P-value combination algorithm while presenting evidence for PANDORA’s superior performance in optimizing the tradeoff between precision and sensitivity. In this article, we present the next generation of the algorithm along with a more in-depth investigation of its capabilities to effectively analyze RNA-Seq data. In particular, we show that PANDORA-reported lists of differentially expressed genes are unaffected by biases introduced by different normalization methods, while, at the same time, they comprise a reliable input option for downstream pathway analysis. Additionally, PANDORA outperforms other methods in detecting differential expression patterns in certain transcript types, including long non-coding RNAs.

144 DOSAGE COMPENSATION AND X-LINKED GENE EXPRESSION IN BOVINE IN VIVO AND IN VITRO EMBRYOS

2016 ◽  
Vol 28 (2) ◽  
pp. 202 ◽  
Author(s):  
J. E. Duan ◽  
N. K. Jue ◽  
Z. Jiang ◽  
R. O'Neill ◽  
E. Wolf ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Dosage Compensation ◽  
Expression Patterns ◽  
Autosomal Gene ◽  
Rna Seq ◽  
X Gene ◽  
Diploid Cells

In human and mouse diploid cells and gametes, expression levels of X-linked genes are hypothesised to balance with those of autosomal genes (Ohno’s “dosage compensation”). Such a phenomenon, however, has not been systematically studied in cattle or compared between in vivo and in vitro embryos. Using RNA-seq data, we compared dosage compensation and expression differences of X-linked genes in bovine in vitro and in vivo oocytes and embryos. RNA-seq datasets GSE59186 and GSE52415 were non-uniquely (paralogs included) mapped to the bovine reference genome assembly UMD3.1 using tophat2. Cufflinks v1.0.3 was used to estimate fragments per kb of exon per million fragments (FPKM), which were then log2-transformed. In order to assess overall patterns of chromosomal gene expression without bias, statistical outliers were removed. A total of 12 928 X-linked transcripts were used to calculate the relative X to autosomal gene (A) expression (RXE): log2 (X expression) – log2 (A expression) for dosage compensation. Values ≥0 indicate dosage compensation (or X : A ratio ≥ 1); values <0 indicate incomplete dosage compensation; value = –1 indicates no dosage compensation (or X : A ratio = 0.5). Cuffdiff was used to identify differentially expressed genes between stages and the 2 datasets. Cuffnorm normalized FPKM for expression patterns, which were further clustered and graphed in R. Expression pattern distributions across regions on X were calculated by merging Cuffnorm output genes.attr_table to the expression pattern lists. The RXE values were higher than –1 in all embryonic stages studied, with in vitro embryos having higher RXE, suggesting some but incomplete dosage compensation and in vitro embryos exhibiting higher levels of X-gene expression. In vitro-produced immature oocytes and 4-cell embryos had RXE of 0, suggesting that both may be completely compensated. Additionally, embryos of the 2 sources exhibited significant differences in levels of X-gene expression at 4-cell to 8-cell and 16-cell to blastocyst stages. All expressed X-linked genes fell in 5 groups (patterns 1–5): increased, decreased, increased and then decreased, constant, decreased and then increased. Patterns 1 to 4 were seen in both datasets, whereas pattern 5 was only present in vitro, which may be why in vitro embryos had higher dosage of X. We further found that these expression patterns correlated with the genes’ proximity to the X inactivation centre (Xic: ~82 Mb): the highly dynamic patterns 3 and 5 were associated with proximity to Xic, supporting the notion that the Xist RNA spreads along the X through the Xic. In vivo and in vitro bovine oocytes and embryos have undergone some degree but incomplete dosage compensation. Expression of X-linked genes is correlated with their proximity to Xic. Globally, in vivo and in vitro embryos exhibit major differences in levels of X-gene expression.

scholarly journals IL-1-conferred gene expression pattern in ERα+ BCa and AR+ PCa cells is intrinsic to ERα- BCa and AR- PCa cells and promotes cell survival

2020 ◽  
Author(s):  
Afshan F. Nawas ◽  
Mohammed Kanchwala ◽  
Shayna E. Thomas-Jardin ◽  
Haley Dahl ◽  
Kelly Daescu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Cell Lines ◽  
Hormone Receptor ◽  
Interleukin 1 ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Treatment Resistance ◽  
Rna Seq ◽  
Data Set

Abstract Background: Breast (BCa) and prostate (PCa) cancers are hormone receptor (HR)-driven cancers. Thus, BCa and PCa patients are given therapies that reduce hormone levels or directly block HR activity; but most patients eventually develop treatment resistance. We have previously reported that interleukin-1 (IL-1) inflammatory cytokine downregulates ERα and AR mRNA in HR-positive (HR+) BCa and PCa cell lines, yet the cells can remain viable. Additionally, we identified pro-survival proteins and processes upregulated by IL-1 in HR+ BCa and PCa cells, that are basally high in HR- BCa and PCa cells. Therefore, we hypothesize that IL-1 confers a conserved gene expression pattern in HR+ BCa and PCa cells that mimics conserved basal gene expression patterns in HR- BCa and PCa cells to promote HR-independent survival and tumorigenicity. Methods: We performed RNA sequencing (RNA-seq) for HR+ BCa and PCa cell lines exposed to IL-1 and for untreated HR- BCa and PCa cell lines. We confirmed expression patterns of select genes by RT-qPCR and used siRNA and/or drug inhibition to silence select genes in the BCa and PCa cell lines. Finally, we performed Ingenuity Pathway Analysis (IPA) and used the gene ontology web-based tool, GOrilla, to identify signaling pathways encoded by our RNA-seq data set. Results: We identified 350 genes in common between BCa and PCa cells that are induced or repressed by IL-1 in HR+ cells that are, respectively, basally high or low in HR- cells. Among these genes, we identified Sequestome-1 (SQSTM1/p62) and SRY (Sex-Determining Region Y)-Box 9 (SOX9) to be essential for survival of HR- BCa and PCa cell lines. Analysis of publicly available data indicates that p62 and SOX9 expression are elevated in HR-independent BCa and PCa sublines generated in vitro, suggesting that p62 and SOX9 have a role in acquired hormone receptor independence and treatment resistance. We also assessed HR- cell line viability in response to the p62-targeting drug, verteporfin, and found that verteporfin is cytotoxic for HR- cell lines. Conclusions: Our 350 gene set can be used to identify novel therapeutic targets and/or biomarkers conserved among acquired (e.g. due to inflammation) or intrinsic HR-independent BCa and PCa.

scholarly journals IL-1-conferred gene expression pattern in ERα+ BCa and AR+ PCa cells is intrinsic to ERα- BCa and AR- PCa cells and promotes cell survival

2019 ◽  
Author(s):  
Afshan F. Nawas ◽  
Mohammed Kanchwala ◽  
Shayna E. Thomas-Jardin ◽  
Haley Dahl ◽  
Kelly Daescu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Cell Lines ◽  
Interleukin 1 ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Treatment Resistance ◽  
Rna Seq ◽  
Drug Inhibition

Abstract Background: Breast (BCa) and prostate (PCa) cancers are hormone receptor (HR)-driven cancers. Thus, BCa and PCa patients are given therapies that reduce hormone levels or directly blocks HR activity; but most patients eventually develop treatment resistance. We have previously reported that interleukin-1 (IL-1) inflammatory cytokine downregulates ER𝛼 and AR mRNA in HR-positive (HR+) BCa and PCa cell lines, yet the cells can remain viable. Additionally, we identified pro-survival proteins and processes upregulated by IL-1 in HR+ BCa and PCa cells, that are basally high in HR- BCa and PCa cells. Therefore, we hypothesize that IL-1 confers a conserved gene expression pattern in HR+ BCa and PCa cells that mimics conserved basal gene expression patterns in HR- BCa and PCa cells to promote HR-independent survival and tumorigenicity.Methods: We performed RNA sequencing (RNA-seq) for HR+ BCa and PCa cell lines exposed to IL-1 and for untreated HR- BCa and PCa cell lines. We confirmed expression patterns of select genes by RT-qPCR and used siRNA and/or drug inhibition to silence select genes in HR- BCa cell lines. Finally, we performed Ingenuity Pathway Analysis (IPA) to identify signaling pathways encoded by our RNA-seq data set.Results: We identified 350 genes in common between BCa and PCa cells that are induced or repressed by IL-1 in HR+ cells that are, respectively, basally high or low in HR- cells. Among these genes, we identified Sequestome-1 (SQSTM1/p62) and SRY (Sex-Determining Region Y)-Box 9 (SOX9) to be essential for survival of HR- BCa and PCa cell lines. Analysis of publicly available data indicates that p62 and SOX9 expression are elevated in HR-independent BCa and PCa sublines generated in vitro, suggesting that p62 and SOX9 have a role in acquired treatment resistance. We also assessed HR- cell line viability in response to the p62-targeting drug, verteporfin, and found that verteporfin is cytotoxic for HR- cell lines. Conclusions: Our 350 gene set can be used to identify novel therapeutic targets and/or biomarkers conserved among acquired (e.g. due to inflammation) or intrinsic HR-independent BCa and PCa.

scholarly journals IL-1-conferred gene expression pattern in ERα+ BCa and AR+ PCa cells is intrinsic to ERα− BCa and AR− PCa cells and promotes cell survival

2019 ◽  
Author(s):  
Afshan F. Nawas ◽  
Mohammed Kanchwala ◽  
Shayna E. Thomas-Jardin ◽  
Haley Dahl ◽  
Kelly Daescu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Cell Lines ◽  
Interleukin 1 ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Treatment Resistance ◽  
Rna Seq ◽  
Data Set

ABSTRACTBackgroundBreast (BCa) and prostate (PCa) cancers are hormone receptor (HR)-driven cancers. Thus, BCa and PCa patients are given therapies that reduce hormone levels or directly blocks HR activity; but most patients eventually develop treatment resistance. We have previously reported that interleukin-1 (IL-1) inflammatory cytokine downregulates ERα and AR mRNA in HR-positive (HR+) BCa and PCa cell lines, yet the cells can remain viable. Additionally, we identified pro-survival proteins and processes upregulated by IL-1 in HR+ BCa and PCa cells, that are basally high in HR− BCa and PCa cells. Therefore, we hypothesize that IL-1 confers a conserved gene expression pattern in HR+ BCa and PCa cells that mimics conserved basal gene expression patterns in HR− BCa and PCa cells to promote HR-independent survival and tumorigenicity.MethodsWe performed RNA sequencing (RNA-seq) for HR+ BCa and PCa cell lines exposed to IL-1 and for untreated HR− BCa and PCa cell lines. We confirmed expression patterns of select genes by RT-qPCR and used siRNA and/or drug inhibition to silence select genes in HR− BCa cell lines. Finally, we performed Ingenuity Pathway Analysis (IPA) to identify signaling pathways encoded by our RNA-seq data set.ResultsWe identified 350 genes in common between BCa and PCa cells that are induced or repressed by IL-1 in HR+ cells that are, respectively, basally high or low in HR− cells. Among these genes, we identified Sequestome-1 (SQSTM1/p62) and SRY (Sex-Determining Region Y)-Box 9 (SOX9) to be essential for survival of HR− BCa and PCa cell lines. Analysis of publicly available data indicates that p62 and SOX9 expression are elevated in HR-independent BCa and PCa sublines generated in vitro, suggesting that p62 and SOX9 have a role in acquired treatment resistance. We also assessed HR− cell line viability in response to the p62-targeting drug, verteporfin, and found that verteporfin is cytotoxic for HR− cell lines.ConclusionsOur 350 gene set can be used to identify novel therapeutic targets and/or biomarkers conserved among acquired (e.g. due to inflammation) or intrinsic HR-independent BCa and PCa.

scholarly journals RNA-Seq-Based Gene Expression Pattern and Morphological Alterations in Chick Thymus during Postnatal Development

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Zhouyiyuan Xue ◽  
Abdur Rahman Ansari ◽  
Xing Zhao ◽  
Kun Zang ◽  
Yu Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Postnatal Development ◽  
Expression Pattern ◽  
Expression Patterns ◽  
Critical Role ◽  
Gene Expression Pattern ◽  
Receptor Interaction ◽  
Rna Seq ◽  
Morphological Alterations

The thymus is a lobulated unique lymphoid immune organ that plays a critical role in the selection, development, proliferation, and differentiation of T cells. The thymus of developing chickens undergoes continued morphological alterations; however, the biomolecular and transcriptional dynamics of the postnatal thymus in avian species is not clear yet. Therefore, the thymuses from chickens at different stages of development (at weeks 0, 1, 5, 9, 18, and 27) were used in the present study. The RNA-seq method was used to study the gene expression patterns. On average, 24120819 clean reads were mapped, differentially expressed genes (DEGs) were identified on the basis of log values (fold change), including 744 upregulated and 425 downregulated genes. The expression pattern revealed by RNA-seq was validated by quantitative real-time PCR (qPCR) analysis of four important genes, which are PCNA, CCNA2, CCNB2, and CDK1. Thus, the current study revealed that during postnatal development, the thymus undergoes severe atrophy. Thymus structure was damaged and gene expression changed dramatically, especially at the 27th week of age. Moreover, we found significant changes of several signaling pathways such as the cytokine-cytokine receptor interaction and cell cycle signaling pathways. Hence, it may be inferred that those signaling pathways might be closely related to the postnatal chicken thymus development.

scholarly journals RNA-Seq Analyses Identify Additivity as the Predominant Gene Expression Pattern in F1 Chicken Embryonic Brain and Liver

Genes ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 27 ◽  
Author(s):  
Zhu Zhuo ◽  
Susan J. Lamont ◽  
Behnam Abasht
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Pairwise Comparison ◽  
Intermediate Phenotype ◽  
Superior Performance ◽  
Rna Seq ◽  
Specific Expression ◽  
Parental Lines

The superior performance of hybrids to parents, termed heterosis, has been widely utilized in animal and plant breeding programs, but the molecular mechanism underlying heterosis remains an enigma. RNA-Seq provides a novel way to investigate heterosis at the transcriptome-wide level, because gene expression functions as an intermediate phenotype that contributes to observable traits. Here we compared embryonic gene expression between chicken hybrids and their inbred parental lines to identify inheritance patterns of gene expression. Inbred Fayoumi and Leghorn were crossed reciprocally to obtain F1 fertile eggs. RNA-Seq was carried out using 24 brain and liver samples taken from day 12 embryos, and the differentially expressed (DE) genes were identified by pairwise comparison among the hybrids, parental lines, and mid-parent expression values. Our results indicated the expression levels of the majority of the genes in the F1 cross are not significantly different from the mid-parental values, suggesting additivity as the predominant gene expression pattern in the F1. The second and third prevalent gene expression patterns are dominance and over-dominance. Additionally, we found only 7–20% of the DE genes exhibit allele-specific expression in the F1, suggesting that trans regulation is the main driver for differential gene expression and thus contributes to heterosis effect in the F1 crosses.

scholarly journals Characterization of cancer omics and drug perturbations in panels of lung cancer cells

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ayako Suzuki ◽  
Keiichi Onodera ◽  
Ken Matsui ◽  
Masahide Seki ◽  
Hiroyasu Esumi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Stress Response ◽  
Cancer Cells ◽  
Chemical Compounds ◽  
Lung Cancer Cells ◽  
New Combinations ◽  
Rna Seq ◽  
Lung Cancers

AbstractTo better understand the disruptions of transcriptional regulations and gene expression in lung cancers, we constructed a multi-omics catalogue of the responses of lung cancer cells to a series of chemical compounds. We generated and analyzed 3,240 RNA-seq and 3,393 ATAC-seq libraries obtained from 23 cell lines treated with 95 well-annotated compounds. To demonstrate the power of the created multi-omics resource, we attempted to identify drugs that could induce the designated changes alone or in combination. The basal multi-omics information was first integrated into co-expression modules. Among these modules, we identified a stress response module that may be a promising drug intervention target, as new combinations of compounds that could be used to regulate this module and the consequent phenotypic appearance of cancer cells have been identified. We believe that the multi-omics profiles generated in this study and the strategy used to stratify them will lead to more rational and efficient development of anticancer drugs.

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