RRM2 Is a CTNNB1 Transport Regulator Promoting Colon Cancer Progression.

BACKGROUND/AIM: The cytoplasmic retention and stabilization of CTNNB1 (ß-catenin) in response to Wnt is well documented in playing a role in tumor growth. Here, through the utilization of a multiplex siRNA library screening strategy, we investigated the modulation of CTNNB1 function in tumor cell progression by ribonucleoside-diphosphate reductase subunit M2 (RRM2). MATERIALS AND METHODS: We conducted a multiplex siRNA screening assay to identify targets involved in CTNNB1 nuclear translocation. In order to examine the effect of inhibition of RRM2, selected from the siRNA screening results, we performed RRM2 knockdown and assayed for colon cancer cell viability, sphere formation assay, and invasion assay. The interaction of RRM2 with CTNNB1 and its impact on oncogenesis was examined using immunoprecipitation, immunoblotting, immunocytochemistry, and RT-qPCR. RESULTS: After a series of screening and filtration steps, we identified 26 genes that were potentially involved in CTNNB1 nuclear translocation. All candidate genes were validated in various cell lines. The results revealed that siRNA-mediated knockdown of RRM2 reduces the nuclear translocation of CTNNB1. This reduction was accompanied by a decrease in cell count, resulting in a suppressive effect on tumor cell growth. CONCLUSION: High throughput siRNA screening is an attractive strategy for identifying gene functions in cancers and the interaction between RRM2 and CTNNB1 is an attractive drug target for regulating RRM2-CTNNB1-related pathways in cancers.

Current advances in comprehensive omics data mining for oncology and cancer research.

The availability of a large amount of multiomics data enables data-driven discovery studies on cancers. High-throughput data on mutations, gene/protein expression, immune scores (tumor-infiltrating cells), drug screening, and RNAi (shRNAs and CRISPRs) screening are major integrated components of patient samples and cell line datasets. Improvements in data access and user interfaces make it easy for general scientists to carry out their data mining practices on integrated multiomics data platforms without computational expertise. Here, we summarize the extent of data integration and functionality of several portals and software that provide integrated multiomics data mining platforms for all cancer studies. Recent progress includes programming interfaces (APIs) for customized data mining. Precalculated datasets assist noncomputational users in quickly browsing data associations. Furthermore, stand-alone software provides fast calculations and smart functions, guiding optimal sampling and filtering options for the easy discovery of significant data associations. These efforts improve the utility of cancer omics big data for noncomputational users at all levels of cancer research. In the present review, we aim to provide analytical information guiding general scientists to find and utilize data mining tools for their research.

Oncogenic Impact of TONSL, a Homologous Recombination Repair Protein at the Replication Fork, in Cancer Stem Cells.

We investigated the role of TONSL, a mediator of homologous recombination repair (HRR), in stalled replication fork double-strand breaks (DSBs) in cancer. Publicly available clinical data (tumors from the ovary, breast, stomach and lung) were analyzed through KM Plotter, cBioPortal and Qomics. Cancer stem cell (CSC)-enriched cultures and bulk/general mixed cell cultures (BCCs) with RNAi were employed to determine the effect of TONSL loss in cancer cell lines from the ovary, breast, stomach, lung, colon and brain. Limited dilution assays and ALDH assays were used to quantify the loss of CSCs. Western blotting and cell-based homologous recombination assays were used to identify DNA damage derived from TONSL loss. TONSL was expressed at higher levels in cancer tissues than in normal tissues, and higher expression was an unfavorable prognostic marker for lung, stomach, breast and ovarian cancers. Higher expression of TONSL is partly associated with the coamplification of TONSL and MYC, suggesting its oncogenic role. The suppression of TONSL using RNAi revealed that it is required in the survival of CSCs in cancer cells, while BCCs could frequently survive without TONSL. TONSL dependency occurs through accumulated DNA damage-induced senescence and apoptosis in TONSL-suppressed CSCs. The expression of several other major mediators of HRR was also associated with worse prognosis, whereas the expression of error-prone nonhomologous end joining molecules was associated with better survival in lung adenocarcinoma. Collectively, these results suggest that TONSL-mediated HRR at the replication fork is critical for CSC survival; targeting TONSL may lead to the effective eradication of CSCs.

Screening of the siGPCR library in combination with cisplatin against lung cancers.

The screening of siRNAs targeting 390 human G protein-coupled receptors (GPCRs) was multiplexed in combination with cisplatin against lung cancer cells. While the cell viability measure hardly captured the anticancer effect of siGPCRs, the direct cell count revealed the anticancer potential of diverse GPCRs (46 hits with > twofold growth inhibition, p-value < 0.01). In combined treatment with cisplatin, siRNAs against five genes (ADRA2A, F2RL3, NPSR1, NPY and TACR3) enhanced the anti-proliferation efficacy on cancer cells and reduced the self-recovery ability of surviving cells after the removal of the combined treatment. Further on-target validation confirmed that the knockdown of TACR3 expression exhibited anticancer efficacy under both single and combined treatment with cisplatin. Q-omics ( http://qomics.io ) analysis showed that high expression of TACR3 was unfavorable for patient survival, particularly with mutations in GPCR signaling pathways. The present screening data provide a useful resource for GPCR targets and biomarkers for improving the efficacy of cisplatin treatment.

MicroRNA-dependent inhibition of WEE1 controls cancer stem-like characteristics and malignant behavior in ovarian cancer.

Cancer stem-like cells (CSCs) have been suggested to be responsible for chemoresistance and tumor recurrence owing to their self-renewal capacity and differentiation potential. Although WEE1 is a strong candidate target for anticancer therapies, its role in ovarian CSCs is yet to be elucidated. Here, we show that WEE1 plays a key role in regulating CSC properties and tumor resistance to carboplatin via a microRNA-dependent mechanism. We found that WEE1 expression is upregulated in ovarian cancer spheroids because of the decreased expression of miR-424 and miR-503, which directly target WEE1. The overexpression of miR-424/503 suppressed CSC activity by inhibiting WEE1 expression, but this effect was reversed on the restoration of WEE1 expression. Furthermore, we demonstrated that NANOG modulates the miR-424/503-WEE1 axis that regulates the properties of CSCs. We also demonstrated the pharmacological restoration of the NANOG-miR-424/503-WEE1 axis and attenuation of ovarian CSC characteristics in response to atorvastatin treatment. Lastly, miR-424/503-mediated WEE1 inhibition re-sensitized chemoresistant ovarian cancer cells to carboplatin. Additionally, combined treatment with atorvastatin and carboplatin synergistically reduced tumor growth, chemoresistance, and peritoneal seeding in the intraperitoneal mouse models of ovarian cancer. We identified a novel NANOG-miR-424/503-WEE1 pathway for regulating ovarian CSCs, which has potential therapeutic utility in ovarian cancer treatment.

ARL2 is required for homologous recombination repair and colon cancer stem cell survival.

ARL2 regulates the dynamics of cytological components and is highly expressed in colon cancer tissues. Here, we report novel roles of ARL2 in the cell nucleus and colon cancer stem cells (CSCs). ARL2 is expressed at relatively low levels in K-RAS active colon cancer cells, but its expression is induced in CSCs. Depletion of ARL2 results in M phase arrest exclusively in non-CSC cultured cells; in addition, DNA break stress accumulates in CSCs leading to apoptosis. ARL2 expression is positively associated with the expression of all six RAD51 family genes, which are essential for homologous recombination repair (HRR). Furthermore, ARL2 is required for HRR and detected within chromatin compartments. These results demonstrate the requirement of ARL2 in colon CSC maintenance, which possibly occurs through mediating double-strand break DNA repair in the nucleus.

Q-omics: Smart Software for Assisting Oncology and Cancer Research.

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.

Targeting a Lipid Desaturation Enzyme, SCD1, Selectively Eliminates Colon Cancer Stem Cells through the Suppression of Wnt and NOTCH Signaling.

The elimination of the cancer stem cell (CSC) population may be required to achieve better outcomes of cancer therapy. We evaluated stearoyl-CoA desaturase 1 (SCD1) as a novel target for CSC-selective elimination in colon cancer. CSCs expressed more SCD1 than bulk cultured cells (BCCs), and blocking SCD1 expression or function revealed an essential role for SCD1 in the survival of CSCs, but not BCCs. The CSC potential selectively decreased after treatment with the SCD1 inhibitor in vitro and in vivo. The CSC-selective suppression was mediated through the induction of apoptosis. The mechanism leading to selective CSC death was investigated by performing a quantitative RT-PCR analysis of 14 CSC-specific signaling and marker genes after 24 and 48 h of treatment with two concentrations of an inhibitor. The decrease in the expression of Notch1 and AXIN2 preceded changes in the expression of all other genes, at 24 h of treatment in a dose-dependent manner, followed by the downregulation of most Wnt- and NOTCH-signaling genes. Collectively, we showed that not only Wnt but also NOTCH signaling is a primary target of suppression by SCD1 inhibition in CSCs, suggesting the possibility of targeting SCD1 against colon cancer in clinical settings.

MicroRNA 34a-AXL Axis Regulates Vasculogenic Mimicry Formation in Breast Cancer Cells.

Targeting the tumor vasculature is an attractive strategy for cancer treatment. However, the tumor vasculature is heterogeneous, and the mechanisms involved in the neovascularization of tumors are highly complex. Vasculogenic mimicry (VM) refers to the formation of vessel-like structures by tumor cells, which can contribute to tumor neovascularization, and is closely related to metastasis and a poor prognosis. Here, we report a novel function of AXL receptor tyrosine kinase (AXL) in the regulation of VM formation in breast cancer cells. MDA-MB-231 cells exhibited VM formation on Matrigel cultures, whereas MCF-7 cells did not. Moreover, AXL expression was positively correlated with VM formation. Pharmacological inhibition or AXL knockdown strongly suppressed VM formation in MDA-MB-231 cells, whereas the overexpression of AXL in MCF-7 cells promoted VM formation. In addition, AXL knockdown regulated epithelial-mesenchymal transition (EMT) features, increasing cell invasion and migration in MDA-MB-231 cells. Finally, the overexpression of microRNA-34a (miR-34a), which is a well-described EMT-inhibiting miRNA and targets AXL, inhibited VM formation, migration, and invasion in MDA-MB 231 cells. These results identify a miR-34a-AXL axis that is critical for the regulation of VM formation and may serve as a therapeutic target to inhibit tumor neovascularization.

Analysis of Cross-Association between mRNA Expression and RNAi Efficacy for Predictive Target Discovery in Colon Cancers.

The availability of large-scale, collateral mRNA expression and RNAi data from diverse cancer cell types provides useful resources for the discovery of anticancer targets for which inhibitory efficacy can be predicted from gene expression. Here, we calculated bidirectional cross-association scores (predictivity and descriptivity) for each of approximately 18,000 genes identified from mRNA and RNAi (i.e., shRNA and sgRNA) data from colon cancer cell lines. The predictivity score measures the difference in RNAi efficacy between cell lines with high vs. low expression of the target gene, while the descriptivity score measures the differential mRNA expression between groups of cell lines exhibiting high vs. low RNAi efficacy. The mRNA expression of 90 and 74 genes showed significant (p < 0.01) cross-association scores with the shRNA and sgRNA data, respectively. The genes were found to be from diverse molecular classes and have different functions. Cross-association scores for the mRNA expression of six genes (CHAF1B, HNF1B, HTATSF1, IRS2, POLR2B and SATB2) with both shRNA and sgRNA efficacy were significant. These genes were interconnected in cancer-related transcriptional networks. Additional experimental validation confirmed that siHNF1B efficacy is correlated with HNF1B mRNA expression levels in diverse colon cancer cell lines. Furthermore, KIF26A and ZIC2 gene expression, with which shRNA efficacy displayed significant scores, were found to correlate with the survival rate from colon cancer patient data. This study demonstrates that bidirectional predictivity and descriptivity calculations between mRNA and RNAi data serve as useful resources for the discovery of predictive anticancer targets.

Overexpression and Selective Anticancer Efficacy of ENO3 in STK11 Mutant Lung Cancers.

Oncogenic gain-of-function mutations are clinical biomarkers for most targeted therapies, as well as represent direct targets for drug treatment. Although loss-of-function mutations involving the tumor suppressor gene, STK11 (LKB1) are important in lung cancer progression, STK11 is not the direct target for anticancer agents. We attempted to identify cancer transcriptome signatures associated with STK11 loss-offunction mutations. Several new sensitive and specific gene expression markers (ENO3, TTC39C, LGALS3, and MAML2) were identified using two orthogonal measures, i.e., fold change and odds ratio analyses of transcriptome data from cell lines and tissue samples. Among the markers identified, the ENO3 gene over-expression was found to be the direct consequence of STK11 loss-of-function. Furthermore, the knockdown of ENO3 expression exhibited selective anticancer effect in STK11 mutant cells compared with STK11 wild type (or recovered) cells. These findings suggest that ENO3 -based targeted therapy might be promising for patients with lung cancer harboring STK11 mutations.

Clinical and biochemical relevance of monounsaturated fatty acid metabolism targeting strategy for cancer stem cell elimination in colon cancer.

Lipid metabolism is associated with colon cancer prognosis and incidence. Stearoyl-CoA desaturase 1 (SCD1), which converts fully saturated fatty acids (SFAs) to monounsaturated fatty acids (MUFAs), has been suggested as a vulnerable target for selective elimination of cancer stem cells (CSCs). However, the clinical significance and physiological role of SCD1 in CSCs has not been well demonstrated. Here, we showed the clinical and biochemical relevance of blocking SCD1 to target CSCs by analyzing human colon cancer data from TCGA and through lipidomic profiling of CSCs with or without SCD1 inhibition using mass spectrometry. Positive associations between SCD1 expression and colorectal cancer patient clinical status and the expression of CSC-related genes (WNT and NOTCH signaling) were found based on TCGA data analysis. Lipidomic profiling of CSCs and bulk cancer cells (BCCs) using mass spectrometry revealed that colon CSCs contained a distinctive lipid profile, with higher free MUFA and lower free SFA levels than in BCCs, suggesting that enhanced SCD1 activity generates MUFAs that may support WNT signaling in CSCs. In addition, all identified phosphatidyl-ethanolamine-containing MUFAs were found at higher levels in CSCs. Interestingly, we observed lower phosphatidyl-serine (18:1/18:0), phosphatidyl-choline (PC; p-18:0/18:1)), and sphingomyelin (SM; d18:1/20:0 or d16:1/22:0) levels in CSCs than in BCCs. Of those, SCD1 inhibition, which efficiently diminished free MUFA levels, increased those specific PC and SM and MUFAs in CSCs promptly. These results suggest that these specific lipid composition is critical for CSC stem cell maintenance. In addition, not only free MUFAs, which are known to be required for WNT signaling, but also other phospholipids, such as SM, which are important for lipid raft formation, may mediate other cell signaling pathways that support CSC maintenance. Comparison of the lipidomic profiles of colon cancer cells with those of previously reported for glioma cells further demonstrated the tissue specific characteristics of lipid metabolism in CSCs.

Dissecting phenotypic responses of the druggable targetome in cancers.

Although a large amount of screening data comprising target genes and/or drugs tested against cancer cell line panels are available, different assay conditions and readouts limit the integrated analysis and batch-to-batch comparison of these data. Here, we systematically produced and analyzed the anticancer effect of the druggable targetome to understand the varied phenotypic outcomes of diverse functional classes of target genes. A library of siRNAs targeting ~4,800 druggable genes was screened against cancer cell lines under 2D and/or 3D assay conditions. The anticancer effect was simultaneously measured by quantifying cell proliferation and/or viability. Hit rates varied significantly depending on assay conditions and/or phenotypic readouts. Functional classes of hit genes were correlated with the microenvironment difference between the 2D monolayer cell proliferation and 3D sphere formation assays. Furthermore, multiplexing of cell proliferation and viability measures enabled us to compare the sensitivity and resistance responses to the gene knockdown. Many target genes that inhibited cell proliferation increased the single-cell-level viability of surviving cells, leading to an increase in self-renewal potential. In this study, combinations of parallel 2D/3D assays and multiplexing of cell proliferation and viability measures provided functional insights into the varied phenotypic outcomes of the cancer targetome.

ß-catenin/TCF activity regulates IGF-1R tyrosine kinase inhibitor sensitivity in colon cancer.

The availability of large-scale drug screening data on cell line panels provides a unique opportunity to identify predictive biomarkers for targeted drug efficacy. Analysis of diverse drug data on ~990 cancer cell lines revealed enhanced sensitivity of insulin-like growth factor 1 receptor/ Insulin Receptor (IGF-1R/IR) tyrosine kinase inhibitors (TKIs) in colon cancer cells. Interestingly, ß-catenin/TCF(T cell factor)-responsive promoter activity exhibited a significant positive association with IGF-1R/IR TKI response, while the mutational status of direct upstream genes, such as CTNNB1 and APC, was not significantly associated with the response. The ß-catenin/TCF activity high cell lines express components of IGF-1R/IR signaling more than the low cell lines explaining their enhanced sensitivity against IGF-1R/IR TKI. Reinforcing ß-catenin/TCF responsive promoter activity by introducing CTNNB1 gain-of-function mutations into IGF-1R/IR TKI-resistant cells increased the expression and activity of IGF-1R/IR signaling components and also sensitized the cells to IGF-1R/IR TKIs in vitro and in vivo. Analysis of TCGA data revealed that the stronger ß-catenin/TCF responsive promoter activity was associated with higher IGF-1R and IGF2 transcription in human colon cancer specimens as well. Collectively, compared to the mutational status of upstream genes, ß-catenin/TCF responsive promoter activity has potential to be a stronger predictive positive biomarker for IGF-1R/IR TKI responses in colon cancer cells. The present study highlights the potential of transcriptional activity as therapeutic biomarkers for targeted therapies, overcoming the limited ability of upstream genetic mutations to predict responses.

QSurface: fast identification of surface expression markers in cancers.

BACKGROUND: Cell surface proteins have provided useful targets and biomarkers for advanced cancer therapies. The recent clinical success of antibody-drug conjugates (ADCs) highlights the importance of finding selective surface antigens for given cancer subtypes. We thus attempted to develop stand-alone software for the analysis of the cell surface transcriptome of patient cancer samples and to prioritize lineage- and/or mutation-specific over-expression markers in cancer cells. RESULTS: A total of 519 genes were selected as surface proteins, and their expression was profiled in 14 cancer subtypes using patient sample transcriptome data. Lineage/mutation-oriented analysis was used to identify subtype-specific surface markers with statistical confidence. Experimental validation confirmed the unique over-expression of predicted surface markers (MUC4, MSLN, and SLC7A11) in lung cancer cells at the protein level. The differential cell surface gene expression of cell lines may differ from that of tissue samples due to the absence of the tumor microenvironment. CONCLUSIONS: In the present study, advanced 3D models of lung cell lines successfully reproduced the predicted patterns, demonstrating the physiological relevance of cell line-based 3D models in validating surface markers from patient tumor data. Also QSurface software is freely available at http://compbio.sookmyung.ac.kr/~qsurface .

Transcriptome modeling and phenotypic assays for cancer precision medicine.

Cancer precision medicine requires clinically actionable biomarkers for patient stratification and a better prediction of clinical outcome. Although thousands of cancer-enriched mutated genes have been reported by global sequencing projects, to date, only a few oncogenic mutations have been confirmed as effective biomarkers in cancer therapies. The low frequency and varied profile (i.e., allele frequency, mutation position) of mutant genes among cancer types limit the utility of predictive biomarkers. The recent explosion of cancer transcriptome and phenotypic screening data provides another opportunity for finding transcript-level biomarkers and targets, thus overcoming the limitation of cancer mutation analyses. Technological developments enable the rapid and extensive discovery of potential target-biomarker combinations from large-scale transcriptome-level screening combined with physiologically relevant phenotypic assays. Here, we summarized recent progress as well as discussed the outlook of transcriptome-oriented data mining strategies and phenotypic assays for the identification of non-genetic biomarkers and targets in cancer drug discovery.

Patient sample-oriented analysis of gene expression highlights extracellular signatures in breast cancer progression.

Although a large collection of cancer cell lines are useful surrogates for patient samples, the physiological relevance of observed molecular phenotypes in cell lines remains controversial. Because transcriptome data are a representative set of molecular phenotypes in cancers, we systematically analyzed the discrepancy of global gene expression profiles between patient samples and cell lines in breast cancers. While the majority of genes exhibited general consistency between patient samples and cell lines, the expression of genes in the categories of extracellular matrix, collagen trimers, receptor activity, catalytic activity and transporter activity were significantly up-regulated only in tissue samples. Genes in the extracellular matrix, particularly collagen trimers, showed a wide variation of expression in tissue, but minimal expression and variation in cell lines. Further analysis of tissue samples exclusively revealed that collagen genes exhibited a cancer stage-dependent expressional variation based on their supramolecular structure. Prognostic collagen biomarkers associated with survival rate were also readily predicted from tissue-oriented transcriptome analysis. This study presents the limitations of cell lines and the exclusive features of tissue samples in terms of functional categories of the cancer transcriptome.

Loss-of-function screens of druggable targetome against cancer stem-like cells.

Cancer stem-like cells (CSLCs) contribute to the initiation and recurrence of tumors and to their resistance to conventional therapies. In this study, small interfering RNA (siRNA)-based screening of ∼4800 druggable genes in 3-dimensional CSLC cultures in comparison to 2-dimensional bulk cultures of U87 glioma cells revealed 3 groups of genes essential for the following: survival of the CSLC population only, bulk-cultured population only, or both populations. While diverse biologic processes were associated with siRNAs reducing the bulk-cultured population, CSLC-eliminating siRNAs were enriched in a few functional categories, such as lipid metabolism, protein metabolism, and gene expression. Interestingly, siRNAs that selectively reduced CSLC only were found to target genes for cholesterol and unsaturated fatty acid synthesis. The lipidomic profile of CSLCs revealed increased levels of monounsaturated lipids. Pharmacologic blockage of these target pathways reduced CSLCs, and this effect was eliminated by addition of downstream metabolite products. The present CSLC-sensitive target categories provide a useful resource that can be exploited for the selective elimination of CSLCs.-Song, M., Lee, H., Nam, M.-H., Jeong, E., Kim, S., Hong, Y., Kim, N., Yim, H. Y., Yoo, Y.-J., Kim, J. S., Kim, J.-S., Cho, Y.-Y., Mills, G. B., Kim, W.-Y., Yoon, S. Loss-of-function screens of druggable targetome against cancer stem-like cells.

Cardiac glycosides display selective efficacy for STK11 mutant lung cancer.

Although STK11 (LKB1) mutation is a major mediator of lung cancer progression, targeted therapy has not been implemented due to STK11 mutations being loss-of-function. Here, we report that targeting the Na(+)/K(+)-ATPase (ATP1A1) is synthetic lethal with STK11 mutations in lung cancer. The cardiac glycosides (CGs) digoxin, digitoxin and ouabain, which directly inhibit ATP1A1 function, exhibited selective anticancer effects on STK11 mutant lung cancer cell lines. Restoring STK11 function reduced the efficacy of CGs. Clinically relevant doses of digoxin decreased the growth of STK11 mutant xenografts compared to wild type STK11 xenografts. Increased cellular stress was associated with the STK11-specific efficacy of CGs. Inhibiting ROS production attenuated the efficacy of CGs, and STK11-AMPK signaling was important in overcoming the stress induced by CGs. Taken together, these results show that STK11 mutation is a novel biomarker for responsiveness to CGs. Inhibition of ATP1A1 using CGs warrants exploration as a targeted therapy for STK11 mutant lung cancer.

Differential regulation and synthetic lethality of exclusive RB1 and CDKN2A mutations in lung cancer.

Genetic alterations in lung cancer are distinctly represented in non-small cell lung carcinoma (NSCLC) and small cell lung carcinoma (SCLC). Mutation of the RB1 and CDKN2A genes, which are tightly associated with cell cycle regulation, is exclusive to SCLC and NSCLC cells, respectively. Through the systematic analysis of transcriptome and proteome datasets for 318 cancer cell lines, we characterized differential gene expression and protein regulation in RB1-mutant SCLC and CDKN2A-mutant NSCLC. Many of the genes and proteins associated with RB1-mutant SCLC cell lines belong to functional categories of gene expression and transcription, whereas those associated with CDKN2A-mutant NSCLC cell lines were enriched in gene sets of the extracellular matrix and focal adhesion. These results indicate that the loss of RB1 and CDKN2A function induces distinctively different signaling cascades in SCLC and NSCLC cells. In addition, knockdown of the RB1 gene in CKDN2A-mutant cell lines (and vice versa) synergistically inhibits cancer cell proliferation. The present study on the exclusive role of RB1 and CDKN2A mutations in lung cancer subtypes demonstrates a synthetic lethal strategy for cancer regulation.