Systematic discovery of mutation-directed neo-protein-protein interactions in cancer.

Comprehensive sequencing of patient tumors reveals genomic mutations across tumor types that enable tumorigenesis and progression. A subset of oncogenic driver mutations results in neomorphic activity where the mutant protein mediates functions not engaged by the parental molecule. Here, we identify prevalent variant-enabled neomorph-protein-protein interactions (neoPPI) with a quantitative high-throughput differential screening (qHT-dS) platform. The coupling of highly sensitive BRET biosensors with miniaturized coexpression in an ultra-HTS format allows large-scale monitoring of the interactions of wild-type and mutant variant counterparts with a library of cancer-associated proteins in live cells. The screening of 17,792 interactions with 2,172,864 data points revealed a landscape of gain of interactions encompassing both oncogenic and tumor suppressor mutations. For example, the recurrent BRAF V600E lesion mediates KEAP1 neoPPI, rewiring a BRAFV600E/KEAP1 signaling axis and creating collateral vulnerability to NQO1 substrates, offering a combination therapeutic strategy. Thus, cancer genomic alterations can create neo-interactions, informing variant-directed therapeutic approaches for precision medicine.

An expanded universe of cancer targets.

The characterization of cancer genomes has provided insight into somatically altered genes across tumors, transformed our understanding of cancer biology, and enabled tailoring of therapeutic strategies. However, the function of most cancer alleles remains mysterious, and many cancer features transcend their genomes. Consequently, tumor genomic characterization does not influence therapy for most patients. Approaches to understand the function and circuitry of cancer genes provide complementary approaches to elucidate both oncogene and non-oncogene dependencies. Emerging work indicates that the diversity of therapeutic targets engendered by non-oncogene dependencies is much larger than the list of recurrently mutated genes. Here we describe a framework for this expanded list of cancer targets, providing novel opportunities for clinical translation.

Perspective on Oncogenic Processes at the End of the Beginning of Cancer Genomics.

The Cancer Genome Atlas (TCGA) has catalyzed systematic characterization of diverse genomic alterations underlying human cancers. At this historic junction marking the completion of genomic characterization of over 11,000 tumors from 33 cancer types, we present our current understanding of the molecular processes governing oncogenesis. We illustrate our insights into cancer through synthesis of the findings of the TCGA PanCancer Atlas project on three facets of oncogenesis: (1) somatic driver mutations, germline pathogenic variants, and their interactions in the tumor; (2) the influence of the tumor genome and epigenome on transcriptome and proteome; and (3) the relationship between tumor and the microenvironment, including implications for drugs targeting driver events and immunotherapies. These results will anchor future characterization of rare and common tumor types, primary and relapsed tumors, and cancers across ancestry groups and will guide the deployment of clinical genomic sequencing.

Comprehensive Characterization of Cancer Driver Genes and Mutations.

Identifying molecular cancer drivers is critical for precision oncology. Multiple advanced algorithms to identify drivers now exist, but systematic attempts to combine and optimize them on large datasets are few. We report a PanCancer and PanSoftware analysis spanning 9,423 tumor exomes (comprising all 33 of The Cancer Genome Atlas projects) and using 26 computational tools to catalog driver genes and mutations. We identify 299 driver genes with implications regarding their anatomical sites and cancer/cell types. Sequence- and structure-based analyses identified >3,400 putative missense driver mutations supported by multiple lines of evidence. Experimental validation confirmed 60%-85% of predicted mutations as likely drivers. We found that >300 MSI tumors are associated with high PD-1/PD-L1, and 57% of tumors analyzed harbor putative clinically actionable events. Our study represents the most comprehensive discovery of cancer genes and mutations to date and will serve as a blueprint for future biological and clinical endeavors.

Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer.

We report a comprehensive analysis of 412 muscle-invasive bladder cancers characterized by multiple TCGA analytical platforms. Fifty-eight genes were significantly mutated, and the overall mutational load was associated with APOBEC-signature mutagenesis. Clustering by mutation signature identified a high-mutation subset with 75% 5-year survival. mRNA expression clustering refined prior clustering analyses and identified a poor-survival "neuronal" subtype in which the majority of tumors lacked small cell or neuroendocrine histology. Clustering by mRNA, long non-coding RNA (lncRNA), and miRNA expression converged to identify subsets with differential epithelial-mesenchymal transition status, carcinoma in situ scores, histologic features, and survival. Our analyses identified 5 expression subtypes that may stratify response to different treatments.

Functional Genomic Landscape of Human Breast Cancer Drivers, Vulnerabilities, and Resistance.

Large-scale genomic studies have identified multiple somatic aberrations in breast cancer, including copy number alterations and point mutations. Still, identifying causal variants and emergent vulnerabilities that arise as a consequence of genetic alterations remain major challenges. We performed whole-genome small hairpin RNA (shRNA) "dropout screens" on 77 breast cancer cell lines. Using a hierarchical linear regression algorithm to score our screen results and integrate them with accompanying detailed genetic and proteomic information, we identify vulnerabilities in breast cancer, including candidate "drivers," and reveal general functional genomic properties of cancer cells. Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mechanisms, effects of existing anti-cancer drugs, and opportunities for combination therapy. Finally, we demonstrate the utility of this large dataset by identifying BRD4 as a potential target in luminal breast cancer and PIK3CA mutations as a resistance determinant for BET-inhibitors.

Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer.

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.

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.

Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies.

PKM2 isoform-specific deletion reveals a differential requirement for pyruvate kinase in tumor cells.

The pyruvate kinase M2 isoform (PKM2) is expressed in cancer and plays a role in regulating anabolic metabolism. To determine whether PKM2 is required for tumor formation or growth, we generated mice with a conditional allele that abolishes PKM2 expression without disrupting PKM1 expression. PKM2 deletion accelerated mammary tumor formation in a Brca1-loss-driven model of breast cancer. PKM2 null tumors displayed heterogeneous PKM1 expression, with PKM1 found in nonproliferating tumor cells and no detectable pyruvate kinase expression in proliferating cells. This suggests that PKM2 is not necessary for tumor cell proliferation and implies that the inactive state of PKM2 is associated with the proliferating cell population within tumors, whereas nonproliferating tumor cells require active pyruvate kinase. Consistent with these findings, variable PKM2 expression and heterozygous PKM2 mutations are found in human tumors. These data suggest that regulation of PKM2 activity supports the different metabolic requirements of proliferating and nonproliferating tumor cells.

The somatic genomic landscape of glioblastoma.

We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

Regulation of the Hippo-YAP pathway by G-protein-coupled receptor signaling.

The Hippo pathway is crucial in organ size control, and its dysregulation contributes to tumorigenesis. However, upstream signals that regulate the mammalian Hippo pathway have remained elusive. Here, we report that the Hippo pathway is regulated by G-protein-coupled receptor (GPCR) signaling. Serum-borne lysophosphatidic acid (LPA) and sphingosine 1-phosphophate (S1P) act through G12/13-coupled receptors to inhibit the Hippo pathway kinases Lats1/2, thereby activating YAP and TAZ transcription coactivators, which are oncoproteins repressed by Lats1/2. YAP and TAZ are involved in LPA-induced gene expression, cell migration, and proliferation. In contrast, stimulation of Gs-coupled receptors by glucagon or epinephrine activates Lats1/2 kinase activity, thereby inhibiting YAP function. Thus, GPCR signaling can either activate or inhibit the Hippo-YAP pathway depending on the coupled G protein. Our study identifies extracellular diffusible signals that modulate the Hippo pathway and also establishes the Hippo-YAP pathway as a critical signaling branch downstream of GPCR.

Protein Kinase C Quality Control by Phosphatase PHLPP1 Unveils Loss-of-Function Mechanism in Cancer.

Protein kinase C (PKC) isozymes function as tumor suppressors in increasing contexts. In contrast to oncogenic kinases, whose function is acutely regulated by transient phosphorylation, PKC is constitutively phosphorylated following biosynthesis to yield a stable, autoinhibited enzyme that is reversibly activated by second messengers. Here, we report that the phosphatase PHLPP1 opposes PKC phosphorylation during maturation, leading to the degradation of aberrantly active species that do not become autoinhibited. Cancer-associated hotspot mutations in the pseudosubstrate of PKCß that impair autoinhibition result in dephosphorylated and unstable enzymes. Protein-level analysis reveals that PKCα is fully phosphorylated at the PHLPP site in over 5,000 patient tumors, with higher PKC levels correlating (1) inversely with PHLPP1 levels and (2) positively with improved survival in pancreatic adenocarcinoma. Thus, PHLPP1 provides a proofreading step that maintains the fidelity of PKC autoinhibition and reveals a prominent loss-of-function mechanism in cancer by suppressing the steady-state levels of PKC.

PIK3CA variants selectively initiate brain hyperactivity during gliomagenesis.

Glioblastoma is a universally lethal form of brain cancer that exhibits an array of pathophysiological phenotypes, many of which are mediated by interactions with the neuronal microenvironment1,2. Recent studies have shown that increases in neuronal activity have an important role in the proliferation and progression of glioblastoma3,4. Whether there is reciprocal crosstalk between glioblastoma and neurons remains poorly defined, as the mechanisms that underlie how these tumours remodel the neuronal milieu towards increased activity are unknown. Here, using a native mouse model of glioblastoma, we develop a high-throughput in vivo screening platform and discover several driver variants of PIK3CA. We show that tumours driven by these variants have divergent molecular properties that manifest in selective initiation of brain hyperexcitability and remodelling of the synaptic constituency. Furthermore, secreted members of the glypican (GPC) family are selectively expressed in these tumours, and GPC3 drives gliomagenesis and hyperexcitability. Together, our studies illustrate the importance of functionally interrogating diverse tumour phenotypes driven by individual, yet related, variants and reveal how glioblastoma alters the neuronal microenvironment.

EGFR-Phosphorylated Platelet Isoform of Phosphofructokinase 1 Promotes PI3K Activation.

EGFR activates phosphatidylinositide 3-kinase (PI3K), but the mechanism underlying this activation is not completely understood. We demonstrated here that EGFR activation resulted in lysine acetyltransferase 5 (KAT5)-mediated K395 acetylation of the platelet isoform of phosphofructokinase 1 (PFKP) and subsequent translocation of PFKP to the plasma membrane, where the PFKP was phosphorylated at Y64 by EGFR. Phosphorylated PFKP binds to the N-terminal SH2 domain of p85α, which is distinct from binding of Gab1 to the C-terminal SH2 domain of p85α, and recruited p85α to the plasma membrane resulting in PI3K activation. PI3K-dependent AKT activation results in enhanced phosphofructokinase 2 (PFK2) phosphorylation and production of fructose-2,6-bisphosphate, which in turn promotes PFK1 activation. PFKP Y64 phosphorylation-enhanced PI3K/AKT-dependent PFK1 activation and GLUT1 expression promoted the Warburg effect, tumor cell proliferation, and brain tumorigenesis. These findings underscore the instrumental role of PFKP in PI3K activation and enhanced glycolysis through PI3K/AKT-dependent positive-feedback regulation.

Author Correction: PAK signalling drives acquired drug resistance to MAPK inhibitors in BRAF-mutant melanomas.

In this Letter, two relevant references were omitted; see the accompanying Amendment for details. The original Letter has not been corrected.

Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response.

Tumour cells evade immune surveillance by upregulating the surface expression of programmed death-ligand 1 (PD-L1), which interacts with programmed death-1 (PD-1) receptor on T cells to elicit the immune checkpoint response1,2. Anti-PD-1 antibodies have shown remarkable promise in treating tumours, including metastatic melanoma2-4. However, the patient response rate is low4,5. A better understanding of PD-L1-mediated immune evasion is needed to predict patient response and improve treatment efficacy. Here we report that metastatic melanomas release extracellular vesicles, mostly in the form of exosomes, that carry PD-L1 on their surface. Stimulation with interferon-γ (IFN-γ) increases the amount of PD-L1 on these vesicles, which suppresses the function of CD8 T cells and facilitates tumour growth. In patients with metastatic melanoma, the level of circulating exosomal PD-L1 positively correlates with that of IFN-γ, and varies during the course of anti-PD-1 therapy. The magnitudes of the increase in circulating exosomal PD-L1 during early stages of treatment, as an indicator of the adaptive response of the tumour cells to T cell reinvigoration, stratifies clinical responders from non-responders. Our study unveils a mechanism by which tumour cells systemically suppress the immune system, and provides a rationale for the application of exosomal PD-L1 as a predictor for anti-PD-1 therapy.

Identifying homologous recombination deficiency in breast cancer: genomic instability score distributions differ among breast cancer subtypes.

PURPOSE: A 3-biomarker homologous recombination deficiency (HRD) score is a key component of a currently FDA-approved companion diagnostic assay to identify HRD in patients with ovarian cancer using a threshold score of ≥ 42, though recent studies have explored the utility of a lower threshold (GIS ≥ 33). The present study evaluated whether the ovarian cancer thresholds may also be appropriate for major breast cancer subtypes by comparing the genomic instability score (GIS) distributions of BRCA1/2-deficient estrogen receptor-positive breast cancer (ER + BC) and triple-negative breast cancer (TNBC) to the GIS distribution of BRCA1/2-deficient ovarian cancer. METHODS: Ovarian cancer and breast cancer (ER + BC and TNBC) tumors from ten study cohorts were sequenced to identify pathogenic BRCA1/2 mutations, and GIS was calculated using a previously described algorithm. Pathologic complete response (pCR) to platinum therapy was evaluated in a subset of TNBC samples. For TNBC, a threshold was set and threshold validity was assessed relative to clinical outcomes. RESULTS: A total of 560 ovarian cancer, 805 ER + BC, and 443 TNBC tumors were included. Compared to ovarian cancer, the GIS distribution of BRCA1/2-deficient samples was shifted lower for ER + BC (p = 0.015), but not TNBC (p = 0.35). In the subset of TNBC samples, univariable logistic regression models revealed that GIS status using thresholds of ≥ 42 and ≥ 33 were significant predictors of response to platinum therapy. CONCLUSIONS: This study demonstrated that the GIS thresholds used for ovarian cancer may also be appropriate for TNBC, but not ER + BC. GIS thresholds in TNBC were validated using clinical response data to platinum therapy.