Leveraging Patient-Derived Organoids for Personalized Liver Cancer Treatment.

Primary liver cancer (PLC) is a primary cause of cancer-related death worldwide, and novel treatments are needed due to the limited options available for treatment and tumor heterogeneity. 66 surgically removed PLC samples were cultured using the self-developed 2:2 method, and the final success rate for organoid culture was 40.9%. Organoid performance has been evaluated using comprehensive molecular measurements, such as whole-exome and RNA sequencing, as well as anticancer drug testing. Multiple organoids and their corresponding tumor tissues contained several of the same mutations, with all pairs sharing conventional TP53 mutations. Regarding copy number variations and gene expression, significant correlations were observed between the organoids and their corresponding parental tumor tissues. Comparisons at the molecular level provided us with an assessment of organoid-to-tumor concordance, which, in combination with drug sensitivity testing provided direct guidance for treatment selection. Finally, we were able to determine an appropriate pharmacological regimen for a patient with ICC, demonstrating the clinical practicality in tailoring patient-specific drug regimens. Our study provides an organoid culture technology that can cultivate models that retain most of the molecular characteristics of tumors and can be used for drug sensitivity testing, demonstrating the broad potential application of organoid technology in precision medicine for liver cancer treatment.

Epidemiology of the non-head and neck sebaceous carcinoma and implications for distant metastasis screening.

Introduction: Extraocular sebaceous carcinoma (SC), particularly those outside the head and neck region, is rare and not well-described. Purpose: This study aimed to explore the epidemiology and identify the prognostic factors of non-head and neck SC, describe the possible relevant factors of distant metastasis, and provide implications for distant metastasis screening. Methods: Data from the 17 registries in the Surveillance, Epidemiology, and End Results database were retrospectively collected for patients with SC outside the head and neck from 2000 through 2020. Overall survival (OS) and disease-specific survival (DSS) were the primary endpoints. Survival analysis was conducted through Kaplan-Meier curves, and multivariate analysis was carried out using Cox proportional hazard models. Results: A total of 1,237 patients with SC outside the head and neck were identified. The mean age at diagnosis of the entire patient cohort was 67.7 years (30 to 90+ years), and the mean tumor size was 2.2 cm (0.1-16 cm). Patients with distant disease experienced the lowest OS (mean, 29.5 months) than those with localized disease and regional disease (p < 0.0001). Multivariate analysis revealed that age, tumor size, and stage were independent determinants of OS; age, stage, and primary site were independent determinants of DSS. Tumor grade and lymph node status had less prognostic value for survival. Undifferentiated tumors have a trend toward distant metastasis, especially those at the primary site of the trunk. Conclusion: The prognosis of the non-head and neck SC is excellent, while the survival of distant disease is very poor. Distant metastasis screening can be considered for undifferentiated tumors, especially those located in the trunk region with large tumor sizes.

Green preparation of CaO-based CO2 adsorbent by calcium-induced hydrogenation of shell wastes at room/moderate temperature.

Capturing CO2 using clamshell/eggshell-derived CaO adsorbent can not only reduce carbon emissions but also alleviate the impact of trash on the environment. However, organic acid was usually used, high-temperature calcination was often performed, and CO2 was inevitably released during preparing CaO adsorbents from shell wastes. In this work, CaO-based CO2 adsorbent was greenly prepared by calcium-induced hydrogenation of clamshell and eggshell wastes in one pot at room/moderate temperature. CO2 adsorption experiments were performed in a thermogravimetric analyzer (TGA). The adsorption performance of the adsorbents obtained from the mechanochemical reaction (BM-C/E-CaO) was superior to that of the adsorbents obtained from the thermochemical reaction (Cal-C/E-CaO). The CO2 adsorption capacity of BM-C-CaO at 650 °C is up to 36.82 wt%, but the adsorption decay rate of the sample after 20 carbonation/calcination cycles is only 30.17%. This study offers an alternative energy-saving method for greenly preparing CaO-based adsorbent from shell wastes.

Analytical Validation of a Telomerase Reverse Transcriptase (TERT) Promoter Mutation Assay.

CONTEXT: Telomerase reverse transcriptase (TERT) promoter-mutated thyroid cancers are associated with a decreased rate of disease-free and disease-specific survival. High-quality analytical validation of a diagnostic test promotes confidence in the results that inform clinical decision-making. OBJECTIVE: This work aimed to demonstrate the analytical validation of the Afirma TERT promoter mutation assay. METHODS: TERT promoter C228T and C250T variant detection in genomic DNA (gDNA) was analyzed by assessing variable DNA input and the limit of detection (LOD) of variant allele frequency (VAF). The negative and positive percentage agreement (NPA and PPA) of the Afirma TERT test was examined against a reference primer pair as was the analytical specificity from potential interfering substances (RNA and blood gDNA). Further, the intrarun, interrun, and interlaboratory reproducibility of the assay were tested. RESULTS: The Afirma TERT test is tolerant to variation in DNA input amount (7-13 ng) and can detect expected positive TERT promoter variants down to 5% VAF LOD at 7 ng DNA input with greater than 95% sensitivity. Both NPA and PPA were 100% against the reference primer pair. The test remains accurate in the presence of 20% RNA or 80% blood gDNA for an average patient sample that typically has 30% VAF. The test also demonstrated a 100% confirmation rate when compared with an external next-generation sequencing-based reference assay executed in a non-Veracyte laboratory. CONCLUSION: The analytical robustness and reproducibility of the Afirma TERT test support its routine clinical use among thyroid nodules with indeterminate cytology that are Afirma Genomic Sequencing Classifier suspicious or among Bethesda V/VI nodules.

Histopathology of telomerase reverse transcriptase promoter (TERT) mutated indeterminate thyroid nodules.

Objective: The objective of this study was to analyze the risk of malignancy and the histopathology of telomerase reverse transcriptase promoter (TERT) mutated cytologically indeterminate thyroid nodules (ITN). Methods: A PUBMED search of molecularly tested ITN was conducted and data on TERT mutated ITN with histopathology correlation were extracted. Results: Twenty-six manuscripts (published between 2014 and 2022) reported on 77 TERT mutated ITN. Sixty-five nodules were malignant (84 %), with 16 (25 %) described with high-risk histopathology, 5 (8 %) described as low-risk, and most without any description. Isolated TERT mutations were malignant in 26/30 ITNs (87 %) with 9 (35 %) described as high risk and none described as low risk. TERT + RAS mutated ITNs were malignant in 29/34 ITNs (85 %) with 3 (10 %) described as high risk and 4 (14 %) described as low risk. Finally, all 5 TERT + BRAFV600E mutated nodules were malignant and 3/5 (60 %) were described as high risk. Conclusion: TERT mutated ITNs have a high risk of malignancy (84 %), and the current data does not show a difference in malignancy rate between isolated TERT mutations and TERT + RAS co-mutated ITNs. When described, TERT + RAS co-mutated ITNs did not have a higher rate of high-risk histopathology as compared to isolated TERT mutated lesions. Most TERT mutated ITNs did not have a description of histopathology risk and the oncologic outcomes, including rate of recurrence, metastases, and disease specific survival, are unknown. Further data is needed to determine if TERT mutated ITNs should be subjected to aggressive initial treatment.

Characterization of tumour microenvironment reprogramming reveals invasion in epithelial ovarian carcinoma.

BACKGROUND: Patients with epithelial ovarian carcinoma (EOC) are usually diagnosed at an advanced stage with tumour cell invasion. However, identifying the underlying molecular mechanisms and biomarkers of EOC proliferation and invasion remains challenging. RESULTS: Herein, we explored the relationship between tumour microenvironment (TME) reprogramming and tissue invasion based on single-cell RNA sequencing (scRNA-seq) datasets. Interestingly, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis, which have biologically active trajectories during epithelial mesenchymal transition (EMT), were positively correlated. Moreover, energy metabolism and anti-apoptotic activity were found to be critical contributors to intratumor heterogeneity. In addition, HMGA1, EGR1 and RUNX1 were found to be critical drivers of the EMT process in EOC. Experimental validation revealed that suppressing EGR1 expression inhibited tumour cell invasion, significantly upregulated the expression of E-cadherin and decreased the expression of N-cadherin. In cell components analysis, cancer-associated fibroblasts (CAFs) were found to significantly contribute to immune infiltration and tumour invasion, and the accumulation of CAFs was associated with poorer patient survival. CONCLUSION: We revealed the molecular mechanism and biomarkers of tumour invasion and TME reprogramming in EOC, which provides effective targets for the suppression of tumour invasion.

Reversible promoter demethylation of PDGFD confers gemcitabine resistance through STAT3 activation and RRM1 upregulation.

Drug resistance is a major problem in cancer treatment with traditional or targeted therapeutics. Gemcitabine is approved for several human cancers and the first line treatment for locally advanced or metastatic pancreatic ductal adenocarcinoma (PDAC). However, gemcitabine resistance frequently occurs and is a major problem in successful treatments of these cancers and the mechanism of gemcitabine resistance remains largely unknown. In this study, we identified 65 genes that had reversible methylation changes in their promoters in gemcitabine resistant PDAC cells using whole genome Reduced Representation Bisulfite Sequencing analyses. One of these genes, PDGFD, was further studied in detail for its reversible epigenetic regulation in expression and shown to contribute to gemcitabine resistance in vitro and in vivo via stimulating STAT3 signaling in both autocrine and paracrine manners to upregulate RRM1 expression. Analyses of TCGA datasets showed that PDGFD positively associates with poor outcome of PDAC patients. Together, we conclude that the reversible epigenetic upregulation plays an important role in gemcitabine resistance development and targeting PDGFD signaling alleviates gemcitabine resistance for PDAC treatment.

Real-World Performance of the Afirma Genomic Sequencing Classifier (GSC)-A Meta-analysis.

CONTEXT: The Afirma® GSC aids in risk stratifying indeterminate thyroid nodule cytology (ITN). The 2018 GSC validation study (VS) reported a sensitivity (SN) of 91%, specificity (SP) of 68%, positive predictive value (PPV) of 47%, and negative predictive value (NPV) of 96%. Since then, 13 independent real-world (RW) postvalidation studies have been published. OBJECTIVE: This study's objective is to compare the RW GSC performance to the VS metrics. METHODS: Rules and assumptions applying to this analysis include: (1) At least 1 patient with molecular benign results must have surgery for that study to be included in SN, SP, and NPV analyses. (2) Molecular benign results without surgical histology are considered true negatives (TN) (as are molecular benign results with benign surgical histology). (3) Unoperated patients with suspicious results are either excluded from analysis (observed PPV [oPPV] and observed SP [oSP]) or assumed histology negatives (false positives; conservative PPV [cPPV] and conservative SP [cSP]) 4. Noninvasive follicular thyroid neoplasm with papillary-like nuclear features is considered malignant. RESULTS: In RW studies, the GSC demonstrates a SN, oSP, oPPV, and NPV of 97%, 88%, 65%, 99% respectively, and conservative RW performance showed cSP of 80% and cPPV of 49%, all significantly higher than the VS except for SN and cPPV. There was also a higher benign call rate (BCR) of 67% in RW studies compared to 54% in the VS (P < 0.05). CONCLUSION: RW data for the Afirma GSC demonstrates significantly better oSP and oPPV performance than the VS, indicating an increased yield of cancers for resected GSC suspicious nodules. The higher BCR likely increases the overall rate of clinical observation in lieu of surgery.

CellTracer: a comprehensive database to dissect the causative multilevel interplay contributing to cell development trajectories.

During the complex process of tumour development, the unique destiny of cells is driven by the fine-tuning of multilevel features such as gene expression, network regulation and pathway activation. The dynamic formation of the tumour microenvironment influences the therapeutic response and clinical outcome. Thus, characterizing the developmental landscape and identifying driver features at multiple levels will help us understand the pathological development of disease in individual cell populations and further contribute to precision medicine. Here, we describe a database, CellTracer (http://bio-bigdata.hrbmu.edu.cn/CellTracer), which aims to dissect the causative multilevel interplay contributing to cell development trajectories. CellTracer consists of the gene expression profiles of 1 941 552 cells from 222 single-cell datasets and provides the development trajectories of different cell populations exhibiting diverse behaviours. By using CellTracer, users can explore the significant alterations in molecular events and causative multilevel crosstalk among genes, biological contexts, cell characteristics and clinical treatments along distinct cell development trajectories. CellTracer also provides 12 flexible tools to retrieve and analyse gene expression, cell cluster distribution, cell development trajectories, cell-state variations and their relationship under different conditions. Collectively, CellTracer will provide comprehensive insights for investigating the causative multilevel interplay contributing to cell development trajectories and serve as a foundational resource for biomarker discovery and therapeutic exploration within the tumour microenvironment.

Integrating bioinformatic strategies in spatial life science research.

As space exploration programs progress, manned space missions will become more frequent and farther away from Earth, putting a greater emphasis on astronaut health. Through the collaborative efforts of researchers from various countries, the effect of the space environment factors on living systems is gradually being uncovered. Although a large number of interconnected research findings have been produced, their connection seems to be confused, and many unknown effects are left to be discovered. Simultaneously, several valuable data resources have emerged, accumulating data measuring biological effects in space that can be used to further investigate the unknown biological adaptations. In this review, the previous findings and their correlations are sorted out to facilitate the understanding of biological adaptations to space and the design of countermeasures. The biological effect measurement methods/data types are also organized to provide references for experimental design and data analysis. To aid deeper exploration of the data resources, we summarized common characteristics of the data generated from longitudinal experiments, outlined challenges or caveats in data analysis and provided corresponding solutions by recommending bioinformatics strategies and available models/tools.

Preoperative Identification of Medullary Thyroid Carcinoma (MTC): Clinical Validation of the Afirma MTC RNA-Sequencing Classifier.

Background: Cytopathological evaluation of thyroid fine-needle aspiration biopsy (FNAB) specimens can fail to raise preoperative suspicion of medullary thyroid carcinoma (MTC). The Afirma RNA-sequencing MTC classifier identifies MTC among FNA samples that are cytologically indeterminate, suspicious, or malignant (Bethesda categories III-VI). In this study we report the development and clinical performance of this MTC classifier. Methods: Algorithm training was performed with a set of 483 FNAB specimens (21 MTC and 462 non-MTC). A support vector machine classifier was developed using 108 differentially expressed genes, which includes the 5 genes in the prior Afirma microarray-based MTC cassette. Results: The final MTC classifier was blindly tested on 211 preoperative FNAB specimens with subsequent surgical pathology, including 21 MTC and 190 non-MTC specimens from benign and malignant thyroid nodules independent from those used in training. The classifier had 100% sensitivity (21/21 MTC FNAB specimens correctly called positive; 95% confidence interval [CI] = 83.9-100%) and 100% specificity (190/190 non-MTC FNAs correctly called negative; CI = 98.1-100%). All positive samples had pathological confirmation of MTC, while all negative samples were negative for MTC on surgical pathology. Conclusions: The RNA-sequencing MTC classifier accurately identified MTC from preoperative thyroid nodule FNAB specimens in an independent validation cohort. This identification may facilitate an MTC-specific preoperative evaluation and resulting treatment.

Identification and Characterization of Immunogene-Related Alternative Splicing Patterns and Tumor Microenvironment Infiltration Patterns in Breast Cancer.

Alternative splicing (AS) plays a crucial role in tumor development and tumor microenvironment (TME) formation. However, our current knowledge about AS, especially immunogene-related alternative splicing (IGAS) patterns in cancers, remains limited. Herein, we identified and characterized post-transcriptional mechanisms of breast cancer based on IGAS, TME, prognosis, and immuno/chemotherapy. We screened the differentially spliced IGAS events and constructed the IGAS prognostic model (p-values < 0.001, AUC = 0.939), which could be used as an independent prognostic factor. Besides, the AS regulatory network suggested a complex cooperative or competitive relationship between splicing factors and IGAS events, which explained the diversity of splice isoforms. In addition, more than half of the immune cells displayed varying degrees of infiltration in the IGAS risk groups, and the prognostic characteristics of IGAS demonstrated a remarkable and consistent trend correlation with the infiltration levels of immune cell types. The IGAS risk groups showed substantial differences in the sensitivity of immunotherapy and chemotherapy. Finally, IGAS clusters defined by unsupervised cluster analysis had distinct prognostic patterns, suggesting an essential heterogeneity of IGAS events. Significant differences in immune infiltration and unique prognostic capacity of immune cells were also detected in each IGAS cluster. In conclusion, our comprehensive analysis remarkably enhanced the understanding of IGAS patterns and TME in breast cancer, which may help clarify the underlying mechanisms of IGAS in neoplasia and provide clues to molecular mechanisms of oncogenesis and progression.

Maximizing Small Biopsy Patient Samples: Unified RNA-Seq Platform Assessment of over 120,000 Patient Biopsies.

Despite its wide-ranging benefits, whole-transcriptome or RNA exome profiling is challenging to implement in a clinical diagnostic setting. The Unified Assay is a comprehensive workflow wherein exome-enriched RNA-sequencing (RNA-Seq) assays are performed on clinical samples and analyzed by a series of advanced machine learning-based classifiers. Gene expression signatures and rare and/or novel genomic events, including fusions, mitochondrial variants, and loss of heterozygosity were assessed using RNA-Seq data generated from 120,313 clinical samples across three clinical indications (thyroid cancer, lung cancer, and interstitial lung disease). Since its implementation, the data derived from the Unified Assay have allowed significantly more patients to avoid unnecessary diagnostic surgery and have played an important role in guiding follow-up decisions regarding treatment. Collectively, data from the Unified Assay show the utility of RNA-Seq and RNA expression signatures in the clinical laboratory, and their importance to the future of precision medicine.

Risk of malignancy in cytologically indeterminate thyroid nodules harboring thyroid stimulating hormone receptor mutations.

Objectives: To evaluate the frequency and risk of malignancy of TSHRpI568T mutations discovered in indeterminate thyroid nodules (ITN) within the Veracyte CLIA laboratory undergoing Afirma® Genomic Sequencing Classifier (GSC) testing, and to evaluate a broader cohort of TSHR variants and their categorization as Afirma GSC benign (GSC-B) or suspicious (GSC-S). Finally, we seek to assess the risk of malignancy (ROM) of this group of TSHR mutated ITN in the GSC-S category. Methods: ITN submitted to Veracyte for Afirma GSC testing between October 2017 and February 2022 were analyzed for TSHR variants and rates of GSC-B and GSC-S were calculated based upon BIII or IV cytology, by TSHR variant codon amino acid (AA) substitution, age, and gender. For GSC-S samples, surgical pathology reports were requested, and the rate of malignancy was calculated. Results: Five percent of the ITN samples harbored an isolated TSHR variant and 5% of those were classified as GSC-S. Among TSHRpI568T samples, 96% were GSC-B and of the GSC-S samples, 21% were malignant. Among an unselected group of TSHR, absent TSHRpI568T mutations, 16.3% of GSC-S samples were malignant, all but one with codon mutations in the transmembrane subdomains of the TSHR. This prompted a dedicated evaluation of transmembrane codons which revealed a malignancy rate of 10.7% among GSC-S nodules. In total, 13/85 (15.3%) TSHR mutated ITN with Afirma GSC-S results were found to be malignant. Conclusions: TSHR variants are rare in ITN, and most are categorized as benign under Afirma GSC testing which carries a < 4% risk of malignancy. For GSC-S ITN with TSHR mutations, the risk of malignancy is ≥= 15%, which is clinically meaningful and may alter treatment or monitoring recommendations for patients.

LncACTdb 3.0: an updated database of experimentally supported ceRNA interactions and personalized networks contributing to precision medicine.

LncACTdb 3.0 is a comprehensive database of experimentally supported interactions among competing endogenous RNA (ceRNA) and the corresponding personalized networks contributing to precision medicine. LncACTdb 3.0 is freely available at http://bio-bigdata.hrbmu.edu.cn/LncACTdb or http://www.bio-bigdata.net/LncACTdb. We have updated the LncACTdb 3.0 database with several new features, including (i) 5669 experimentally validated ceRNA interactions across 25 species and 537 diseases/phenotypes through manual curation of published literature, (ii) personalized ceRNA interactions and networks for 16 228 patients from 62 datasets in TCGA and GEO, (iii) sub-cellular and extracellular vesicle locations of ceRNA manually curated from literature and data sources, (iv) more than 10 000 experimentally supported long noncoding RNA (lncRNA) biomarkers associated with tumor diagnosis and therapy, and (v) lncRNA/mRNA/miRNA expression profiles with clinical and pathological information of thousands of cancer patients. A panel of improved tools has been developed to explore the effects of ceRNA on individuals with specific pathological backgrounds. For example, a network tool provides a comprehensive view of lncRNA-related, patient-specific, and custom-designed ceRNA networks. LncACTdb 3.0 will provide novel insights for further studies of complex diseases at the individual level and will facilitate the development of precision medicine to treat such diseases.

Characterizing the Metabolic and Immune Landscape of Non-small Cell Lung Cancer Reveals Prognostic Biomarkers Through Omics Data Integration.

Non-small cell lung cancer (NSCLC) is one of the most common malignancies worldwide. The development of high-throughput single-cell RNA-sequencing (RNA-seq) technology and the advent of multi-omics have provided a solid basis for a systematic understanding of the heterogeneity in cancers. Although numerous studies have revealed the molecular features of NSCLC, it is important to identify and validate the molecular biomarkers related to specific NSCLC phenotypes at single-cell resolution. In this study, we analyzed and validated single-cell RNA-seq data by integrating multi-level omics data to identify key metabolic features and prognostic biomarkers in NSCLC. High-throughput single-cell RNA-seq data, including 4887 cellular gene expression profiles from NSCLC tissues, were analyzed. After pre-processing, the cells were clustered into 12 clusters using the t-SNE clustering algorithm, and the cell types were defined according to the marker genes. Malignant epithelial cells exhibit individual differences in molecular features and intra-tissue metabolic heterogeneity. We found that oxidative phosphorylation (OXPHOS) and glycolytic pathway activity are major contributors to intra-tissue metabolic heterogeneity of malignant epithelial cells and T cells. Furthermore, we constructed T-cell differentiation trajectories and identified several key genes that regulate the cellular phenotype. By screening for genes associated with T-cell differentiation using the Lasso algorithm and Cox risk regression, we identified four prognostic marker genes for NSCLC. In summary, our study revealed metabolic features and prognostic markers of NSCLC at single-cell resolution, which provides novel findings on molecular biomarkers and signatures of cancers.

TTSurv: Exploring the Multi-Gene Prognosis in Thousands of Tumors.

Thoracic malignancies are a common type of cancer and area major global health problem. These complex diseases, including lung cancer, esophageal cancer, and breast cancer, etc. have attracted considerable attention from researchers. Potential gene-cancer associations can be explored by demonstrating the association between clinical data and gene expression data. Emerging evidence suggests that the transcriptome plays a particularly critical role as a diagnostic biomarker in pathology and histology studies. Thus, there is an urgent need to develop a platform that allows users to perform a comprehensive prognostic analysis of thoracic cancers. Here, we developed TTSurv, which aims to correlate coding and noncoding genes with cancers by combining high-throughput data with clinical prognosis. TTSurv focuses on the application of high-throughput data to detect ncRNAs, such as lncRNAs and microRNAs, as novel diagnostic and prognostic biomarkers. For a more comprehensive analysis, a large amount of public expression profile data with clinical follow-up information have been integrated into TTSurv. TTSurv also provides flexible methods such as a minimum p-value algorithm and unsupervised clustering methods that can classify thoracic cancer samples into different risk groups. TTSurv will expand our understanding of ncRNAs in thoracic malignancies and provide new insights into their application as potential prognostic/diagnostic biomarkers.

Oncogenic Landscape of Somatic Mutations Perturbing Pan-Cancer lncRNA-ceRNA Regulation.

Competing endogenous RNAs (ceRNA) are transcripts that communicate with and co-regulate each other by competing for the binding of shared microRNAs (miRNAs). Long non-coding RNAs (lncRNAs) as a type of ceRNA constitute a competitive regulatory network determined by miRNA response elements (MREs). Mutations in lncRNA MREs destabilize their original regulatory pathways. Study of the effects of lncRNA somatic mutations on ceRNA mechanisms can clarify tumor mechanisms and contribute to the development of precision medicine. Here, we used somatic mutation profiles collected from TCGA to characterize the role of lncRNA somatic mutations in the ceRNA regulatory network in 33 cancers. The 31,560 mutation sites identified by TargetScan and miRanda affected the balance of 70,811 ceRNA regulatory pathways. Putative mutations were categorized as high or low based on mutation frequencies. Multivariate multiple regression revealed a significant effect of 162 high-frequency mutations in six cancer types on the expression levels of target mRNAs (ceMs) through the ceRNA mechanism. Low-frequency mutations in multiple cancers perturbing 1624 ceM have been verified by Student's t-test, indicating a significant mechanism of changes in the expression level of oncogenic genes. Oncogenic signaling pathway studies involving ceMs indicated functional heterogeneity of multiple cancers. Furthermore, we identified that lncRNA, perturbing ceMs associated with patient survival, have potential as biomarkers. Our collective findings revealed individual differences in somatic mutations perturbing ceM expression and impacting tumor heterogeneity.