Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies.
Estrogen receptor (ER)-negative cancers have a poor prognosis, and few targeted therapies are available for their treatment. Our previous analyses have identified potential kinase targets critical for the growth of ER-negative, progesterone receptor (PR)-negative and HER2-negative, or “triple-negative” breast cancer (TNBC). Because phosphatases regulate the function of kinase signaling pathways, in this study, we investigated whether phosphatases are also differentially expressed in ER-negative compared to those in ER-positive breast cancers. We compared RNA expression in 98 human breast cancers (56 ER-positive and 42 ER-negative) to identify phosphatases differentially expressed in ER-negative compared to those in ER-positive breast cancers. We then examined the effects of one selected phosphatase, dual specificity phosphatase 4 (DUSP4), on proliferation, cell growth, migration and invasion, and on signaling pathways using protein microarray analyses of 172 proteins, including phosphoproteins. We identified 48 phosphatase genes are significantly differentially expressed in ER-negative compared to those in ER-positive breast tumors. We discovered that 31 phosphatases were more highly expressed, while 11 were underexpressed specifically in ER-negative breast cancers. The DUSP4 gene is underexpressed in ER-negative breast cancer and is deleted in approximately 50 % of breast cancers. Induced DUSP4 expression suppresses both in vitro and in vivo growths of breast cancer cells. Our studies show that induced DUSP4 expression blocks the cell cycle at the G1/S checkpoint; inhibits ERK1/2, p38, JNK1, RB, and NFkB p65 phosphorylation; and inhibits invasiveness of TNBC cells. These results suggest that that DUSP4 is a critical regulator of the growth and invasion of triple-negative breast cancer cells.
Electronic supplementary material
The online version of this article (doi:10.1007/s10549-016-3892-y) contains supplementary material, which is available to authorized users.
TNBC; Phosphatase; Mouse xenograft; MAPK pathways
Large-scale sequencing efforts are uncovering the complexity of cancer genomes, which are comprised of causal “driver” mutations that promote tumor progression along with many more pathologically-neutral “passenger” events. The majority of mutations, both in known cancer drivers and uncharacterized genes, are generally of low occurrence, highlighting the need to functionally annotate the long tail of infrequent mutations present in heterogeneous cancers. Here we describe a mutation assessment pipeline enabled by high-throughput engineering of molecularly-barcoded gene variant expression clones identified by tumor sequencing. We first used this platform to functionally assess tail mutations observed in PIK3CA, which encodes the catalytic subunit alpha of the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K) frequently mutated in cancer. Orthogonal screening for PIK3CA variant activity using in vitro and in vivo cell growth and transformation assays differentiated driver from passenger mutations, revealing that PIK3CA variant activity correlates imperfectly with its mutation frequency across breast cancer populations. While PIK3CA mutations with frequencies above 5% were significantly more oncogenic than wild-type in all assays, mutations occurring at 0.07 – 5.0% included those with and without oncogenic activities that ranged from weak to strong in at least one assay. Proteomic profiling coupled with therapeutic sensitivity assays on PIK3CA variant-expressing cell models revealed variant-specific activation of PI3K signaling as well as other pathways that include the MEK1/2 module of Mitogen-Activated Protein (MAP) Kinase pathway. Our data indicate that cancer treatments will need to increasingly consider the functional relevance of specific mutations in driver genes rather than considering all mutations in drivers as equivalent.
Cancer genomics; functional screens; mutagenesis; molecular barcoding; breast cancer; PIK3CA
Amplification and over expression of erbB2/neu proto-oncogene is observed in 20–30% human breast cancer and is inversely correlated with the survival of the patient. Despite this, somatic activating mutations within erbB2 in human breast cancers are rare. However, we have previously reported that a splice isoform of erbB2, containing an in-frame deletion of exon 16 (herein referred to as ErbB2ΔEx16), results in oncogenic activation of erbB2 due to constitutive dimerization of the ErbB2 receptor. Here, we demonstrate that the ErbB2ΔEx16 is a major oncogenic driver in breast cancer that constitutively signals from the cell surface. We further show that inducible expression of the ErbB2Ex16 variant in mammary gland of transgenic mice results in the rapid development of metastatic multifocal mammary tumors. Genetic and biochemical characterization of the ErbB2ΔEx16 derived mammary tumors exhibit several unique features that distinguish it from the conventional ErbB2 models expressing the erbB2 proto-oncogene in mammary epithelium. Unlike the wild-type ErbB2 derived tumors that express luminal keratins, ErbB2ΔEx16 derived tumors exhibit high degree of intra-tumoral heterogeneity co-expressing both basal and luminal keratins. Consistent with these distinct pathological features, the ErbB2ΔEx16 tumors exhibited distinct signaling and gene expression profiles that correlated with activation of number of key transcription factors implicated in breast cancer metastasis and cancer stem cell renewal.
ErbB2; breast cancer; mouse model; splice variant
While clinical outcomes following immunotherapy have shown an association with tumor mutation load using whole exome sequencing (WES), its clinical applicability is currently limited by cost and bioinformatics requirements.
We developed a method to accurately derive the predicted total mutation load (PTML) within individual tumors from a small set of genes that can be used in clinical next generation sequencing (NGS) panels. PTML was derived from the actual total mutation load (ATML) of 575 distinct melanoma and lung cancer samples and validated using independent melanoma (n = 312) and lung cancer (n = 217) cohorts. The correlation of PTML status with clinical outcome, following distinct immunotherapies, was assessed using the Kaplan–Meier method.
PTML (derived from 170 genes) was highly correlated with ATML in cutaneous melanoma and lung adenocarcinoma validation cohorts (R2 = 0.73 and R2 = 0.82, respectively). PTML was strongly associated with clinical outcome to ipilimumab (anti-CTLA-4, three cohorts) and adoptive T-cell therapy (1 cohort) clinical outcome in melanoma. Clinical benefit from pembrolizumab (anti-PD-1) in lung cancer was also shown to significantly correlate with PTML status (log rank P value < 0.05 in all cohorts).
The approach of using small NGS gene panels, already applied to guide employment of targeted therapies, may have utility in the personalized use of immunotherapy in cancer.
Electronic supplementary material
The online version of this article (doi:10.1186/s12916-016-0705-4) contains supplementary material, which is available to authorized users.
Melanoma; Lung cancer; Total mutation load; CTLA-4; PD-1; Immunotherapy
Adenosine-to-inosine (A-to-I) RNA editing is a widespread post-transcriptional mechanism, but its genomic landscape and clinical relevance in cancer have not been investigated systematically. We characterized the global A-to-I RNA editing profiles of 6236 patient samples of 17 cancer types from The Cancer Genome Atlas and revealed a striking diversity of altered RNA-editing patterns in tumors relative to normal tissues. We identified an appreciable number of clinically relevant editing events, many of which are in noncoding regions. We experimentally demonstrated the effects of several cross-tumor nonsynonymous RNA editing events on cell viability and provide the evidence that RNA editing could selectively affect drug sensitivity. These results highlight RNA editing as an exciting theme for investigating cancer mechanisms, biomarkers and treatments.
The discovery of long non-coding RNA (lncRNA) has dramatically altered our understanding of cancer. Here, we describe a comprehensive analysis of lncRNA alterations at transcriptional, genomic, and epigenetic levels in 5,037 human tumor specimens across 13 cancer types from the Cancer Genome Atlas (TCGA). Our results suggest that the expression and dysregulation of lncRNAs are highly cancer-type specific compared to protein-coding genes. Using the integrative data generated by this analysis, we present a clinically guided small interfering RNA screening strategy and a co-expression analysis approach to identify cancer driver lncRNAs and predict their functions. This provides a resource for investigating lncRNAs in cancer and lays the groundwork for the development of new diagnostics and treatments.
Invasive lobular carcinoma (ILC) is the second most prevalent histologic subtype of invasive breast cancer. Here, we comprehensively profiled 817 breast tumors, including 127 ILC, 490 ductal (IDC), and 88 mixed IDC/ILC. Besides E-cadherin loss, the best known ILC genetic hallmark, we identified mutations targeting PTEN, TBX3 and FOXA1 as ILC enriched features. PTEN loss associated with increased AKT phosphorylation, which was highest in ILC among all breast cancer subtypes. Spatially clustered FOXA1 mutations correlated with increased FOXA1 expression and activity. Conversely, GATA3 mutations and high expression characterized Luminal A IDC, suggesting differential modulation of ER activity in ILC and IDC. Proliferation and immune-related signatures determined three ILC transcriptional subtypes associated with survival differences. Mixed IDC/ILC cases were molecularly classified as ILC-like and IDC-like revealing no true hybrid features. This multidimensional molecular atlas sheds new light on the genetic bases of ILC and provides potential clinical options.
3q26.2 amplification in high-grade serous ovarian cancer leads to increased expression of mature microRNA miR551b-3p, which is associated with poor clinical outcome. Importantly, miR551b-3p contributes to resistance to apoptosis and increased survival and proliferation of cancer cells in vitro and in vivo. miR551b-3p up-regulates STAT3 protein levels with STAT3 being required for the effects of miR551b-3p on cell proliferation. Rather than decreasing levels of target mRNA as expected, we demonstrate that miR551b-3p binds a complementary sequence on the STAT3 promoter recruiting RNA Polymerase II and the TWIST1 transcription factor to activate STAT3 transcription and thus directly upregulates STAT3 expression. Furthermore, anti-miR551b reduced STAT3 expression in ovarian cancer cells in vitro and in vivo and reduced ovarian cancer growth in vivo. Together our data demonstrates a role for miR551b-3p in transcriptional activation. Thus miR551b-3p represents a promising candidate biomarker and therapeutic target in ovarian cancer.
Endometrial cancer incidence is increasing, due in part to a strong association with obesity. Mutations in the phosphatidylinositol 3-kinase (PI3K) pathway, the central relay pathway of insulin signals, occur in the majority of endometrioid adenocarcinomas, the most common form of endometrial cancer. We sought to determine the impact of PI3K pathway alterations on progression free survival in a cohort of endometrioid endometrial cancers. Prognostic utility of PIK3CA, PIK3R1, and PTEN mutations, as well as PTEN protein loss by immunohistochemistry, was explored in the context of patient body mass index. Reverse-phase protein arrays were utilized to assess protein expression based on PTEN status. Among 187 endometrioid endometrial cancers, there were no statistically significant associations between PFS and PIK3CA, PIK3R1, PTEN mutation or loss. When stratified by body mass index, PTEN loss was associated with improved progression free survival (P<0.006) in obese (body mass index ≥ 30) patients. PTEN loss resulted in distinct protein changes: Canonical PI3K pathway activation was observed only in the non-obese population while decreased expression of β-CATENIN and phosphorylated FOXO3A was observed in obese patients. These data suggest the impact of PTEN loss on tumor biology and clinical outcomes must be interpreted in the context of body mass index, and provide a potential explanation for discrepant reports on the effect of PTEN status and obesity on prognosis in endometrial cancer. This reveals a clinically important interaction between metabolic state and tumor genetics that may unveil the biologic underpinning of obesity-related cancers and impact ongoing clinical trials with PI3K pathway inhibitors.
Endometrial Cancer; PTEN loss; obesity; survival; PI3K/AKT pathway
Higher intakes of the omega-3 eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) relative to the omega-6 arachidonic acid (AA) have been variably associated with reduced risk of premenopausal breast cancer. The purpose of this pilot trial was to assess feasibility and explore effects of high dose EPA and DHA on blood and benign breast tissue risk biomarkers prior to design of a placebo controlled Phase IIB trial. Premenopausal women with evidence of hyperplasia +/- atypia by baseline random periareolar fine needle aspiration (RPFNA) were given 1860 mg of EPA + 1500 mg of DHA ethyl esters daily for 6 months. Blood and benign breast tissue were sampled during the same menstrual cycle phase pre-study and a median of 3 weeks after last dose. Additional blood was obtained within 24 hours of last dose. Feasibility which was pre-defined as 50% uptake, 85% retention and 70% compliance, was demonstrated with 46% uptake, 94% completion, and 85% compliance. Cytologic atypia decreased from 77 to 38% (p=0.002), and Ki-67 from a median of 2.1 to 1.0 % (p=0.021) with an increase in the ratio of EPA + DHA to AA in erythrocyte phospholipids but no change in blood hormones, adipokines, or cytokines. Exploratory breast proteomics assessment showed decreases in several proteins involved in hormone and cytokine signaling with mixed effects on those in the AKT/mTOR pathways. Further investigation of EPA plus DHA for breast cancer prevention in a placebo controlled trial in premenopausal women is warranted.
Breast Cancer; Omega-3 Fatty Acids; Random Periareolar Fine Needle Aspiration
We report the experience with 2,000 consecutive patients with advanced cancer who underwent testing on a genomic testing protocol, including the frequency of actionable alterations across tumor types, subsequent enrollment onto clinical trials, and the challenges for trial enrollment.
Patients and Methods
Standardized hotspot mutation analysis was performed in 2,000 patients, using either an 11-gene (251 patients) or a 46- or 50-gene (1,749 patients) multiplex platform. Thirty-five genes were considered potentially actionable based on their potential to be targeted with approved or investigational therapies.
Seven hundred eighty-nine patients (39%) had at least one mutation in potentially actionable genes. Eighty-three patients (11%) with potentially actionable mutations went on genotype-matched trials targeting these alterations. Of 230 patients with PIK3CA/AKT1/PTEN/BRAF mutations that returned for therapy, 116 (50%) received a genotype-matched drug. Forty patients (17%) were treated on a genotype-selected trial requiring a mutation for eligibility, 16 (7%) were treated on a genotype-relevant trial targeting a genomic alteration without biomarker selection, and 40 (17%) received a genotype-relevant drug off trial. Challenges to trial accrual included patient preference of noninvestigational treatment or local treatment, poor performance status or other reasons for trial ineligibility, lack of trials/slots, and insurance denial.
Broad implementation of multiplex hotspot testing is feasible; however, only a small portion of patients with actionable alterations were actually enrolled onto genotype-matched trials. Increased awareness of therapeutic implications and access to novel therapeutics are needed to optimally leverage results from broad-based genomic testing.
Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks.
Targeting multiple components of the MAPK pathway can prolong the survival of patients with BRAFV600E melanoma. This approach is not curative, as some BRAF-mutated melanoma cells are intrinsically resistant to MAPK inhibitors (MAPKi). At the systemic level, our knowledge of how signaling pathways underlie drug resistance needs to be further expanded. Here, we have shown that intrinsically resistant BRAF-mutated melanoma cells with a low basal level of mitochondrial biogenesis depend on this process to survive MAPKi. Intrinsically resistant cells exploited an integrated stress response, exhibited an increase in mitochondrial DNA content, and required oxidative phosphorylation to meet their bioenergetic needs. We determined that intrinsically resistant cells rely on the genes encoding TFAM, which controls mitochondrial genome replication and transcription, and TRAP1, which regulates mitochondrial protein folding. Therefore, we targeted mitochondrial biogenesis with a mitochondrium-targeted, small-molecule HSP90 inhibitor (Gamitrinib), which eradicated intrinsically resistant cells and augmented the efficacy of MAPKi by inducing mitochondrial dysfunction and inhibiting tumor bioenergetics. A subset of tumor biopsies from patients with disease progression despite MAPKi treatment showed increased mitochondrial biogenesis and tumor bioenergetics. A subset of acquired drug-resistant melanoma cell lines was sensitive to Gamitrinib. Our study establishes mitochondrial biogenesis, coupled with aberrant tumor bioenergetics, as a potential therapy escape mechanism and paves the way for a rationale-based combinatorial strategy to improve the efficacy of MAPKi.
Thyroid transcription factor-1 (TTF1) immunohistochemistry (IHC) is used clinically to differentiate primary lung adenocarcinomas (LUAD) from squamous lung cancers and metastatic adenocarcinomas from other primary sites. However, a subset of LUAD (15-20%) does not express TTF1 and TTF1-negative patients have worse clinical outcomes. As there are no established targeted agents with activity in TTF1-negative LUAD, we performed an integrated molecular analysis to identify potential therapeutic targets.
Using two clinical LUAD cohorts (274 tumors), one from our institution (PROSPECT) and the TCGA, we interrogated proteomic profiles (by reverse-phase protein array (RPPA)), gene expression, and mutational data. Drug response data from 74 cell lines were used to validate potential therapeutic agents.
Strong correlations were observed between TTF1 IHC and TTF1 measurements by RPPA (Rho=0.57, p<0.001) and gene expression (NKX2-1, Rho=0.61, p<0.001). Established driver mutations (e.g. BRAF and EGFR) were associated with high TTF1 expression. In contrast, TTF1-negative LUAD had a higher frequency of inactivating KEAP1 mutations (p=0.001). Proteomic profiling identified increased expression of DNA repair proteins (e.g., Chk1 and the DNA repair score) and suppressed PI3K/MAPK signaling among TTF1-negative tumors, with differences in total proteins confirmed at the mRNA level. Cell line analysis showed drugs targeting DNA repair to be more active in TTF1-low cell lines.
Combined genomic and proteomic analyses demonstrated infrequent alteration of validated lung cancer targets (including the absence of BRAF mutations in TTF1-negative LUAD), but identified novel potential targets for TTF1-negative LUAD includingKEAP1/Nrf2 and DNA repair pathways.
TTF1; lung adenocarcinoma; molecular profiling; non-small cell lung cancer; DNA repair
The development of cost-effective technologies able to comprehensively assess DNA, RNA, protein, and metabolites in patient tumors has fueled efforts to tailor medical care. Indeed validated molecular tests assessing tumor tissue or patient germline DNA already drive therapeutic decision making. However, many theoretical and regulatory challenges must still be overcome before fully realizing the promise of personalized molecular medicine. The masses of data generated by high-throughput technologies are challenging to manage, visualize, and convert to the knowledge required to improve patient outcomes. Systems biology integrates engineering, physics, and mathematical approaches with biologic and medical insights in an iterative process to visualize the interconnected events within a cell that determine how inputs from the environment and the network rewiring that occurs due to the genomic aberrations acquired by patient tumors determines cellular behavior and patient outcomes. A cross-disciplinary systems biology effort will be necessary to convert the information contained in multidimensional data sets into useful biomarkers that can classify patient tumors by prognosis and response to therapeutic modalities and to identify the drivers of tumor behavior that are optimal targets for therapy. An understanding of the effects of targeted therapeutics on signaling networks and homeostatic regulatory loops will be necessary to prevent inadvertent effects as well as to develop rational combinatorial therapies. Systems biology approaches identifying molecular drivers and biomarkers will lead to the implementation of smaller, shorter, cheaper, and individualized clinical trials that will increase the success rate and hasten the implementation of effective therapies into the clinical armamentarium.
The phosphatidylinositol 3 kinase (PI3K)/AKT pathway is genetically targeted in more pathway components and in more tumor types than any other growth factor signaling pathway, and thus is frequently activated as a cancer driver. More importantly, the PI3K/AKT pathway is composed of multiple bifurcating and converging kinase cascades, providing many potential targets for cancer therapy. Renal cell carcinoma (RCC) is a high-risk and high-mortality cancer that is notoriously resistant to traditional chemotherapies or radiotherapies. The PI3K/AKT pathway is modestly mutated but highly activated in RCC, representing a promising drug target. Indeed, PI3K pathway inhibitors of the rapalog family are approved for use in RCC. Recent large-scale integrated analyses of a large number of patients have provided a molecular basis for RCC, reiterating the critical role of the PI3K/AKT pathway in this cancer. In this review, we summarizes the genetic alterations of the PI3K/AKT pathway in RCC as indicated in the latest large-scale genome sequencing data, as well as treatments for RCC that target the aberrant activated PI3K/AKT pathway.
PI3K; AKT; mTOR; Renal cell carcinoma; Targeted therapy
The canonical action of the p85α regulatory subunit of phosphatidylinositol 3-kinase (PI3K) is to associate with the p110α catalytic subunit to allow stimuli-dependent activation of the PI3K pathway. We elucidate a p110α-independent role of homodimerized p85α in the positive regulation of PTEN stability and activity. p110α-free p85α homodimerizes via two intermolecular interactions (SH3:proline-rich region and BH:BH) to selectively bind unphosphorylated activated PTEN. As a consequence, homodimeric but not monomeric p85α suppresses the PI3K pathway by protecting PTEN from E3 ligase WWP2-mediated proteasomal degradation. Further, the p85α homodimer enhances the lipid phosphatase activity and membrane association of PTEN. Strikingly, we identified cancer patient-derived oncogenic p85α mutations that target the homodimerization or PTEN interaction surface. Collectively, our data suggest the equilibrium of p85α monomer–dimers regulates the PI3K pathway and disrupting this equilibrium could lead to disease development.
Many cancers arise due to genetic mutations that allow cells to proliferate uncontrollably. Cell proliferation and many other cell processes can be regulated through a signaling pathway that involves an enzyme called PI3K. This ‘heterodimeric’ enzyme is made up of two protein subunits, one of which is called p85α and inhibits the other subunit of the enzyme (known as p110) to prevent uncontrolled cell proliferation. At the same time, p85α stabilizes p110 and allows the PI3K pathway to be briefly activated when appropriate. Many cancer cells contain mutations in the gene that encodes p85α that prevent the protein from inhibiting p110. This results in the activation of PI3K and promotes cancer formation. A protein called PTEN is a key inhibitor of the PI3K pathway. Common mutations to the PTEN gene in cancer cells stop the PTEN protein working efficiently, or prevent PTEN production.
Recent research has revealed that two molecules of p85α that are free from p110 can bind to each other to form a ‘homodimer’. Cheung et al. have now used biochemical, cell biological and computational methods to investigate the role of these p85α homodimers. This revealed that p85α homodimers stop PTEN being broken down by binding to it. As a consequence, there is enough PTEN in the cell to inhibit the PI3K pathway.
By examining the mutations present in cancer patients, Cheung et al. next identified mutations that prevent the p85α protein from forming homodimers, or that prevent the homodimers from interacting with PTEN. PTEN therefore degrades and cannot inhibit the PI3K pathway, which allows the cells to proliferate. Methods that increase p85α homodimer formation or enhance the ability of p85α homodimers to bind to PTEN may therefore provide new approaches for developing cancer treatments. More generally, it appears that maintaining the correct balance between the amount of p85α in the form of p110-bound heterodimers and p110-free homodimers in a cell may be important for preventing diseases involving the PI3K pathway.
PI3K; mutation; PTEN; cancer; p85; Human; mouse
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.
Papillary renal cell carcinoma, accounting for 15% of renal cell carcinoma, is a heterogeneous disease consisting of different types of renal cancer, including tumors with indolent, multifocal presentation and solitary tumors with an aggressive, highly lethal phenotype. Little is known about the genetic basis of sporadic papillary renal cell carcinoma; no effective forms of therapy for advanced disease exist.
We performed comprehensive molecular characterization utilizing whole-exome sequencing, copy number, mRNA, microRNA, methylation and proteomic analyses of 161 primary papillary renal cell carcinomas.
Type 1 and Type 2 papillary renal cell carcinomas were found to be different types of renal cancer characterized by specific genetic alterations, with Type 2 further classified into three individual subgroups based on molecular differences that influenced patient survival. MET alterations were associated with Type 1 tumors, whereas Type 2 tumors were characterized by CDKN2A silencing, SETD2 mutations, TFE3 fusions, and increased expression of the NRF2-ARE pathway. A CpG island methylator phenotype (CIMP) was found in a distinct subset of Type 2 papillary renal cell carcinoma characterized by poor survival and mutation of the fumarate hydratase (FH) gene.
Type 1 and Type 2 papillary renal cell carcinomas are clinically and biologically distinct. Alterations in the MET pathway are associated with Type 1 and activation of the NRF2-ARE pathway with Type 2; CDKN2A loss and CIMP in Type 2 convey a poor prognosis. Furthermore, Type 2 papillary renal cell carcinoma consists of at least 3 subtypes based upon molecular and phenotypic features.
Chemotherapy response in the majority of patients with ovarian cancer remains unpredictable.
To identify novel molecular markers for predicting chemotherapy response in patients with ovarian cancer.
DESIGN, SETTING, AND PARTICIPANTS
Observational study of genomics and clinical data of high-grade serous ovarian cancer cases with genomic and clinical data made public between 2009 and 2014 via the Cancer Genome Atlas project.
MAIN OUTCOMES AND MEASURES
Chemotherapy response (primary outcome) and overall survival (OS), progression-free survival (PFS), and platinum-free duration (secondary outcome).
In 512 patients with ovarian cancer with available whole-exome sequencing data, mutations from 8 members of the ADAMTS family (ADAMTS mutations) with an overall mutation rate of approximately 10.4% were associated with a significantly higher chemotherapy sensitivity (100% for ADAMTS-mutated vs 64% for ADAMTS wild-type cases; P < .001) and longer platinum-free duration (median platinum-free duration, 21.7 months for ADAMTS-mutated vs 10.1 months for ADAMTS wild-type cases; P = .001). Moreover, ADAMTS mutations were associated with significantly better OS (hazard ratio [HR], 0.54 [95% CI, 0.42–0.89]; P = .01 and median OS, 58.0 months for ADAMTS-mutated vs 41.3 months for ADAMTS wild-type cases) and PFS (HR, 0.42 [95% CI, 0.38–0.70]; P < .001 and median PFS, 31.8 for ADAMTS-mutated vs 15.3 months for ADAMTS wild-type cases). After adjustment by BRCA1 or BRCA2 mutation, surgical stage, residual tumor, and patient age, ADAMTS mutations were significantly associated with better OS (HR, 0.53 [95% CI, 0.32–0.87]; P = .01), PFS (HR, 0.40 [95% CI, 0.25–0.62]; P < .001), and platinum-free survival (HR, 0.45 [95% CI, 0.28–0.73]; P = .001). ADAMTS-mutated cases exhibited a distinct mutation spectrum and were significantly associated with tumors with a higher genome-wide mutation rate than ADAMTS wild-type cases across the whole exome (median mutation number per sample, 121 for ADAMTS-mutated vs 69 for ADAMTS wild-type cases; P < .001).
CONCLUSIONS AND RELEVANCE
ADAMTS mutations may contribute to outcomes in ovarian cancer cases without BRCA1 or BRCA2 mutations and may have important clinical implications.
Rapidly improving understanding of molecular oncology, emerging novel therapeutics, and increasingly available and affordable next-generation sequencing have created an opportunity for delivering genomically informed personalized cancer therapy. However, to implement genomically informed therapy requires that a clinician interpret the patient’s molecular profile, including molecular characterization of the tumor and the patient’s germline DNA. In this Commentary, we review existing data and tools for precision oncology and present a framework for reviewing the available biomedical literature on therapeutic implications of genomic alterations. Genomic alterations, including mutations, insertions/deletions, fusions, and copy number changes, need to be curated in terms of the likelihood that they alter the function of a “cancer gene” at the level of a specific variant in order to discriminate so-called “drivers” from “passengers.” Alterations that are targetable either directly or indirectly with approved or investigational therapies are potentially “actionable.” At this time, evidence linking predictive biomarkers to therapies is strong for only a few genomic markers in the context of specific cancer types. For these genomic alterations in other diseases and for other genomic alterations, the clinical data are either absent or insufficient to support routine clinical implementation of biomarker-based therapy. However, there is great interest in optimally matching patients to early-phase clinical trials. Thus, we need accessible, comprehensive, and frequently updated knowledge bases that describe genomic changes and their clinical implications, as well as continued education of clinicians and patients.
The Rab GTPases regulate vesicular trafficking machinery that transports and delivers a diverse pool of cargo, including growth factor receptors, integrins, nutrient receptors and junction proteins to specific intracellular sites. The trafficking machinery is indeed a major posttranslational modifier and is critical for cellular homeostasis. Deregulation of this stringently controlled system leads to a wide spectrum of disorders including cancer. Herein we demonstrate that Rab25, a key GTPase, mostly decorating the apical recycling endosome, is a dichotomous variable in breast cancer cell lines with higher mRNA and protein expression in Estrogen Receptor positive (ER+ve) lines. Rab25 and its effector, Rab Coupling Protein (RCP) are frequently coamplified and coordinately elevated in ER+ve breast cancers. In contrast, Rab25 levels are decreased in basal-like and almost completely lost in claudin-low tumors. This dichotomy exists despite the presence of the 1q amplicon that hosts Rab25 across breast cancer subtypes and is likely due to differential methylation of the Rab25 promoter. Functionally, elevated levels of Rab25 drive major hallmarks of cancer including indefinite growth and metastasis but in case of luminal B breast cancer only. Importantly, in such ER+ve tumors, coexpression of Rab25 and its effector, RCP is significantly associated with a markedly worsened clinical outcome. Importantly, in claudin-low cell lines, exogenous Rab25 markedly inhibits cell migration. Similarly, during Snail-induced epithelial to mesenchymal transition (EMT) exogenous Rab25 potently reverses Snail-driven invasion. Overall, this study substantiates a striking context dependent role of Rab25 in breast cancer where Rab25 is amplified and enhances aggressiveness in luminal B cancers while in claudin-low tumors, Rab25 is lost indicating possible anti-tumor functions.
Rab25; Rab coupling protein; breast cancer; luminal B; claudin low
The heterogeneous biology of breast cancer leads to high diversity in prognosis and response to treatment, even for patients with similar clinical diagnosis, histology, and stage of disease. Identifying mechanisms contributing to this heterogeneity may reveal new cancer targets or clinically relevant subgroups for treatment stratification. In this study, we have merged metabolite, protein, and gene expression data from breast cancer patients to examine the heterogeneity at a molecular level.
The study included primary tumor samples from 228 non-treated breast cancer patients. High-resolution magic-angle spinning magnetic resonance spectroscopy (HR MAS MRS) was performed to extract the tumors metabolic profiles further used for hierarchical cluster analysis resulting in three significantly different metabolic clusters (Mc1, Mc2, and Mc3). The clusters were further combined with gene and protein expression data.
Our result revealed distinct differences in the metabolic profile of the three metabolic clusters. Among the most interesting differences, Mc1 had the highest levels of glycerophosphocholine (GPC) and phosphocholine (PCho), Mc2 had the highest levels of glucose, and Mc3 had the highest levels of lactate and alanine. Integrated pathway analysis of metabolite and gene expression data uncovered differences in glycolysis/gluconeogenesis and glycerophospholipid metabolism between the clusters. All three clusters had significant differences in the distribution of protein subtypes classified by the expression of breast cancer-related proteins. Genes related to collagens and extracellular matrix were downregulated in Mc1 and consequently upregulated in Mc2 and Mc3, underpinning the differences in protein subtypes within the metabolic clusters. Genetic subtypes were evenly distributed among the three metabolic clusters and could therefore contribute to additional explanation of breast cancer heterogeneity.
Three naturally occurring metabolic clusters of breast cancer were detected among primary tumors from non-treated breast cancer patients. The clusters expressed differences in breast cancer-related protein as well as genes related to extracellular matrix and metabolic pathways known to be aberrant in cancer. Analyses of metabolic activity combined with gene and protein expression provide new information about the heterogeneity of breast tumors and, importantly, the metabolic differences infer that the clusters may be susceptible to different metabolically targeted drugs.
Electronic supplementary material
The online version of this article (doi:10.1186/s40170-016-0152-x) contains supplementary material, which is available to authorized users.
Metabolomics; HR MAS MRS; Breast cancer subgroups; Metabolic cluster; Extracellular matrix
An important step towards personalizing cancer treatment is to integrate heterogeneous evidences to catalog mutational hotspots that are biologically and therapeutically relevant and thus represent where targeted therapy would likely be beneficial. However, existing methods do not sufficiently delineate varying functionality of individual mutations within the same genes.
We observed a large discordancy of mutation rates across different mutation subtypes and tumor types, and nominated 702 hotspot mutations in 549 genes in the Catalog of Somatic Mutations in Cancer (COSMIC) by considering context specific mutation characteristics such as genes, cancer types, mutation rates, mutation subtypes and sequence contexts. We observed that hotspot mutations were highly prevalent in Non CpG-island C/G transition and transversion sequence contexts in 10 tumor types, and specific insertion hotspot mutations were enriched in breast cancer and deletion hotspot mutations in colorectal cancer. We found that the hotspot mutations nominated by our approach were significantly more conserved than non-hotspot mutations in the corresponding cancer genes. We also examined the biological significance and pharmacogenomics properties of these hotspot mutations using data in the Cancer Genome Atlas (TCGA) and the Cancer Cell-Line Encyclopedia (CCLE), and found that 53 hotspot mutations are independently associated with diverse functional evidences in 1) mRNA and protein expression, 2) pathway activity, or 3) drug sensitivity and 82 were highly enriched in specific tumor types. We highlighted the distinct functional indications of hotspot mutations under different contexts and nominated novel hotspot mutations such as MAP3K4 A1199 deletion, NR1H2 Q175 insertion, and GATA3 P409 insertion as potential biomarkers or drug targets.
We identified a set of hotspot mutations across 17 tumor types by considering the background mutation rate variations among genes, tumor subtypes, mutation subtypes, and sequence contexts. We illustrated the common and distinct mutational signatures of hotspot mutations among different tumor types and investigated their variable functional relevance under different contexts, which could potentially serve as a resource for explicitly selecting targets for diagnosis, drug development, and patient management.
Electronic supplementary material
The online version of this article (doi:10.1186/s12864-016-2727-x) contains supplementary material, which is available to authorized users.