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XLSX file - 45K, Genes containing breakpoint from translocation in mTNBC

Fig.S1 shows that SCCOHT cells are sensitive to HDAC inhibition. Fig. S2 shows that SCCOHT cells are sensitive to HDAC inhibition or depletion. Fig.S3 shows that SMARCA4/A2 dual deficiency is not associated with hypersensitivity to HDAC inhibitors in lung and pancreatic cancer cell lines. Fig.S4 shows that pan-HDAC inhibitors induce cell morphology changes in SCCOHT cells. Fig.S5 shows that SMARCA2 activation is partially required for the hypersensitivity of SCCOHT cells to HDAC inhibition. Fig. S6 shows the effect of quisinostat on mouse body weights in BIN67 mouse xenograft models. Fig.S7 shows the synergistic effects between HDAC inhibitors and EZH2 inhibitors in SWI/SNF deficiency-driven tumor cells. Fig. S8 shows that depletion of HDAC2 increased sensitivity of BIN67 cells to EPZ-6438 treatment. Fig.S9 shows the synergistic effects between HDAC inhibitors and EZH2 inhibitors in SCCOHT cells. Fig.S10 shows the effect of combined treatment of EPZ-6438 and quisinostat on mouse body weight and survival.

Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare but extremely lethal malignancy that mainly impacts young women. SCCOHT is characterized by a diploid genome with loss of SMARCA4 and lack of SMARCA2 expression, two mutually exclusive ATPases of the SWI/SNF chromatin-remodeling complex. We and others have identified the histone methyltransferase EZH2 as a promising therapeutic target for SCCOHT, suggesting that SCCOHT cells depend on the alternation of epigenetic pathways for survival. In this study, we found that SCCOHT cells were more sensitive to pan-HDAC inhibitors compared with other ovarian cancer lines or immortalized cell lines tested. Pan-HDAC inhibitors, such as quisinostat, reversed the expression of a group of proteins that were deregulated in SCCOHT cells due to SMARCA4 loss, leading to growth arrest, apoptosis, and differentiation in vitro and suppressed tumor growth of xenografted tumors of SCCOHT cells. Moreover, combined treatment of HDAC inhibitors and EZH2 inhibitors at sublethal doses synergistically induced histone H3K27 acetylation and target gene expression, leading to rapid induction of apoptosis and growth suppression of SCCOHT cells and xenografted tumors. Therefore, our preclinical study highlighted the therapeutic potential of combined treatment of HDAC inhibitors with EZH2 catalytic inhibitors to treat SCCOHT.

Supplementary Figure S1 from Loss of Inositol Polyphosphate 5-Phosphatase Is an Early Event in Development of Cutaneous Squamous Cell Carcinoma

XLSX file - 273K, Somatic genic focal copy number changes in mTNBC

XLSX file - 598K, edgeR differential expression results in mTNBC for select cancer related genes

Cutaneous squamous cell carcinoma (SCC) occurs commonly and can metastasize. Identification of specific molecular aberrations and mechanisms underlying the development and progression of cutaneous SCC may lead to better prognostic and therapeutic approaches and more effective chemoprevention strategies. To identify genetic changes associated with early stages of cutaneous SCC development, we analyzed a series of 40 archived skin tissues ranging from normal skin to invasive SCC. Using high-resolution array-based comparative genomic hybridization, we identified deletions of a region on chromosome 10q harboring the INPP5A gene in 24% of examined SCC tumors. Subsequent validation by immunohistochemistry on an independent sample set of 71 SCC tissues showed reduced INPP5A protein levels in 72% of primary SCC tumors. Decrease in INPP5A protein levels seems to be an early event in SCC development, as it also is observed in 9 of 26 (35%) examined actinic keratoses, the earliest stage in SCC development. Importantly, further reduction of INPP5A levels is seen in a subset of SCC patients as the tumor progresses from primary to metastatic stage. The observed frequency and pattern of loss indicate that INPP5A, a negative regulator of inositol signaling, may play a role in development and progression of cutaneous SCC tumors. Cancer Prev Res; 3(10); 1277–83. ©2010 AACR.

XLSX file - 607K, Outlier differential expression results in mTNBC for select cancer related genes

XLSX file - 61K, List of somatic point mutations in mTNBC detected by NGS sequencing analysis

XLSX file - 42K, Ingenuity Canonical Pathways results for mTNBC based on edgeR differential expression results

Table S1 shows the cell viability inhibitory rate (%) in SCCOHT cell lines vs other cell lines in the epigenetic drug screen. Table S2 shows the effects of Quisinostat on the proteome of BIN67 cells after treatment for 24 or 72 hours. Table S3 shows the significantly altered proteins by Quisinostat treatment for 24 hours in BIN67 cells. Table S4 shows the significantly altered proteins by Quisinostat treatment for 72 hours in BIN67 cells. Table S5 shows the biological functions that were significantly affected by Quisinostat treatment for 72 hours in BIN67 cells. Table S6 shows the proteins that were significantly regulated by SMARCA4 re-expression in BIN67 cells. Table S7 shows the biological functions that were significantly affected by SMARCA4 re-expression in BIN67 cells. Table S8 shows the proteins that were significantly regulated by both Quisinostat treatment (72 hr) and SMARCA4 re-expression in BIN67 cells. Table S9 shows the biological functions that were significantly affected by both Quisinostat and SMARCA4 re-expression in BIN67 cells.

Supplementary Tables 1-3, Figures 1-4 from High-throughput RNAi Screening Identifies a Role for TNK1 in Growth and Survival of Pancreatic Cancer Cells

XLSX file - 23K, Mapping statistics for genome sequencing of tumor and germline DNA from mTNBC

XLSX file - 40K, Characteristics of mTNBC study population

Supplementary Data from Loss-of-Function Fibroblast Growth Factor Receptor-2 Mutations in Melanoma

PDF file - 1635K, PET/CT images of mTNBC2 breast lesion before and after treatment on combination MEK and AKT inhibitors

XLSX file - 48K, Transcriptome sequencing (RNA-seq) run statistics for mTNBC

Background:Engaging diverse populations in cancer genomics research is of critical importance and is a fundamental goal of the NCI Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Established as part of the Cancer Moonshot, PE-CGS is a consortium of stakeholders including clinicians, scientists, genetic counselors, and representatives of potential study participants and their communities. Participant engagement is an ongoing, bidirectional, and mutually beneficial interaction between study participants and researchers. PE-CGS sought to set priorities in participant engagement for conducting the network's research.Methods:PE-CGS deliberatively engaged its stakeholders in the following four-phase process to set the network's research priorities in participant engagement: (i) a brainstorming exercise to elicit potential priorities; (ii) a 2-day virtual meeting to discuss priorities; (iii) recommendations from the PE-CGS External Advisory Panel to refine priorities; and (iv) a virtual meeting to set priorities.Results:Nearly 150 PE-CGS stakeholders engaged in the process. Five priorities were set: (i) tailor education and communication materials for participants throughout the research process; (ii) identify measures of participant engagement; (iii) identify optimal participant engagement strategies; (iv) understand cancer disparities in the context of cancer genomics research; and (v) personalize the return of genomics findings to participants.Conclusions:PE-CGS is pursuing these priorities to meaningfully engage diverse and underrepresented patients with cancer and posttreatment cancer survivors as participants in cancer genomics research and, subsequently, generate new discoveries.Impact:Data from PE-CGS will be shared with the broader scientific community in a manner consistent with participant informed consent and community agreement.

PDF file - 135K, Validation of RB1 39bp homozygous deletion in mTNBC1

PURPOSE Circulating tumor DNA (ctDNA) has been validated across multiple indications in the adjuvant and surveillance settings. We evaluated whether targeted digital sequencing (TARDIS) may distinguish a partial response (PR) from a complete response (CR) among patients with metastatic renal cell carcinoma (mRCC) receiving immune checkpoint inhibitor (ICI) therapy. MATERIALS AND METHODS Eligible patients had mRCC that yielded a PR or CR to ICI therapy. Peripheral blood was obtained at a single time point for ctDNA analysis. TARDIS was used for quantification of average variant allele fractions (VAFs). Our primary objective was to determine the association between VAFs and depth of response (PR v CR). A secondary objective was to determine whether VAFs were associated with disease progression. RESULTS Twelve patients were analyzed, nine of whom achieved a PR (75%). Patients received either nivolumab monotherapy (50%) or nivolumab plus ipilimumab (50%). ctDNA analysis incorporated an average of 30 patient-specific mutations (range, 19-35); average coverage depth was 103,342 reads per target. TARDIS quantified a significant difference in VAFs between PR and CR (median, 0.181% [IQR, 0.077%-0.420%] v 0.007% [IQR, 0.0%-0.028%], respectively [ P = .014]). Of the 12 patients in the series, six patients demonstrated radiographic progression subsequent to ctDNA assessment. Patients who progressed on subsequent scans had significantly higher ctDNA than those who maintained their response (median, 0.362% [IQR, 0.181%-2.71%] v 0.033% [IQR, 0.007%-0.077%], respectively [ P = .026]). CONCLUSION In this pilot study, TARDIS accurately differentiated PR from CR among patients with mRCC receiving immunotherapy, and also prospectively identified patients at risk for subsequent progression. Given these findings, we envision subsequent studies that validate these results and investigate the utility of this assay to discern appropriate candidates for discontinuation of immunotherapy.

HER2 cellular location and function in primary canine lung cancer. (A) Canine papillary adenocarcinoma with intense, complete, circumferential membrane (white arrow) and lateral cytoplasmic membrane (black arrow) anti-HER2 antibody positive staining (brown) in a patient with wild-type HER2. (B) Canine papillary adenocarcinoma with moderate cytoplasmic (black arrow) anti-HER2 antibody positive staining (light brown) in a patient with wild-type HER2. x 40; bar 50 µm. (C) Anti-HER2 immunohistochemistry of a Grade 1 canine papillary adenocarcinoma wild type for HER2. x 20. (D) Segmentation mark-up of the tumor from adjacent normal lung. Tumor is identified by green, whereas red is area within tumor that contains no tissue, and yellow represents areas of non-tumor such as necrosis or tumor stroma. x20.

IC50 curves for ADI-PEG20 in ovarian cancer cell lines. A, ASS1-deficient ovarian cancer cell lines and B, ASS1-proficient ovarian cancer cell lines.

Supplementary Figure 1. Confirmation of the recurrent C524, C541 and C544 SDHD promoter mutations in melanoma cell lines via Sanger sequencing. Supplementary Figure 2. Expression of SDHD in melanomas harboring promoter mutations compared to SDHD wild-type samples across TCGA samples. Supplementary Figure 3. Luciferase reporter assays for the C541T and C544T SDHD hotspot promoter mutations in multiple melanoma cell lines. Supplementary Figure 4. Prediction of the consequences of the C541T and C544T SDHD promoter mutations on transcription factor binding. Supplementary Figure 5. mRNA expression correlation between SDHD and multiple ETS transcription factors in TCGA SKCM samples harboring the SDHD C523T promoter mutation. Supplementary Figure 6. Band-shift analysis of recombinant human ELF1 binding to wild-type and C523T, C524T, C541T, and C544T SDHD promoter sequences. Supplementary Figure 7. Effect of siRNA-mediated knockdown of ELF1 on SDHD expression in melanoma cells. Supplementary Figure 8. Effect of siRNA-mediated knockdown of PRDM1 or IRF4 on SDHD expression and SDHD promoter activity in melanoma cells. Supplementary Table 1. SDHD promoter mutations identified in melanoma tumors datasets (TCGA, Broad and Yale) and melanoma cell lines. Supplementary Table 2. MotifBreakR results predicting the effects of recurrent SDHD promoter mutations (C523T, C524T, C541T, C544T, and C548T) on transcription factor binding sites. Supplementary Table 3. Oligonucleotide design for quantitative mass spectrometry.

IC50 summary of validated drug hits in SCCOHT cell lines.

Study Workflow Diagram. Key steps in the study are outlined, including the number of patients at each stage. BEV: bevacizumab.

Supplementary Figures (Fig.S1-S4) and Supplementary Materials and Methods. Supplementary Figure S1. Loss of Hace1 results in increased lung tumorigenesis independent of RIPK3. Supplementary Figure S2. Analysis of RAC, NRF2 and 4HNE expression. Supplementary Figure S3. Analysis of tumor microenvironment. Supplementary Figure S4. Treatment of KRasG12D;Hace1-/- mice with a ROS scavenger diminishes lung tumorigenesis and Hace1-deficient cells are sensitive to exogenous induction of oxidative stress.

Additional Longitudinal Analysis of Relapsed and Refractory Childhood Solid Tumors.

Supplementary Legend

Table S1. Extended Cohort Annotations. Table S2. Mutational Signatures. Table S3. GISTIC Copy Number Analysis. Table S4. Somatic Variants in Relapsed/Refractory Childhood Solid Tumors (n=184 Patients with T/N WES). Table S5. Clinvar Pathogenic and Likely Pathogenic Germline Variants in Relapsed/Refractory Childhood Solid Tumors(n=184 Patients with T/N WES). Table S6. Gene Lists. Table S7. Log2(TPM+1) Values for the 2,199 Most Variable Genes Expressed Across the Cohort of Relapsed/Refractory Childhood Solid Tumors with RNA-seq (n=245). Table S8. Differential Expression Analysis of 2,199 Most Variable Genes Among Clusters. Table S9. Genes Filtered for COSMIC, Transcription Factors and Potential Drug Targets from Table S8 with log2FC greater than or equal to 2. Table S10. Differential Expression Analysis Among C3a, C3b, and C3c Subclusters. Table S11. Samples Falling in Clusters C3a-C3c and Genes that are Uniformly Highly Expressed in the Clusters. Table S12. Longitudinal Samples.

Table containing proteins differentially expressed in at least two rarer ovarian cancer subtypes when compared to HGSC.

HACE1 is an E3 ubiquitin ligase with important roles in tumor biology and tissue homeostasis. Loss or mutation of HACE1 has been associated with the occurrence of a variety of neoplasms, but the underlying mechanisms have not been defined yet. Here, we report that HACE1 is frequently mutated in human lung cancer. In mice, loss of Hace1 led to enhanced progression of KRasG12D-driven lung tumors. Additional ablation of the oncogenic GTPase Rac1 partially reduced progression of Hace1−/− lung tumors. RAC2, a novel ubiquitylation target of HACE1, could compensate for the absence of its homolog RAC1 in Hace1-deficient, but not in HACE1-sufficient tumors. Accordingly, ablation of both Rac1 and Rac2 fully averted the increased progression of KRasG12D-driven lung tumors in Hace1−/− mice. In patients with lung cancer, increased expression of HACE1 correlated with reduced levels of RAC1 and RAC2 and prolonged survival, whereas elevated expression of RAC1 and RAC2 was associated with poor prognosis. This work defines HACE1 as a crucial regulator of the oncogenic activity of RAC-family GTPases in lung cancer development.Significance:These findings reveal that mutation of the tumor suppressor HACE1 disrupts its role as a regulator of the oncogenic activity of RAC-family GTPases in human and murine lung cancer.

Purpose: Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare, aggressive ovarian cancer in young women that is universally driven by loss of the SWI/SNF ATPase subunits SMARCA4 and SMARCA2. A great need exists for effective targeted therapies for SCCOHT.Experimental Design: To identify underlying therapeutic vulnerabilities in SCCOHT, we conducted high-throughput siRNA and drug screens. Complementary proteomics approaches profiled kinases inhibited by ponatinib. Ponatinib was tested for efficacy in two patient-derived xenograft (PDX) models and one cell-line xenograft model of SCCOHT.Results: The receptor tyrosine kinase (RTK) family was enriched in siRNA screen hits, with FGFRs and PDGFRs being overlapping hits between drug and siRNA screens. Of multiple potent drug classes in SCCOHT cell lines, RTK inhibitors were only one of two classes with selectivity in SCCOHT relative to three SWI/SNF wild-type ovarian cancer cell lines. We further identified ponatinib as the most effective clinically approved RTK inhibitor. Reexpression of SMARCA4 was shown to confer a 1.7-fold increase in resistance to ponatinib. Subsequent proteomic assessment of ponatinib target modulation in SCCOHT cell models confirmed inhibition of nine known ponatinib target kinases alongside 77 noncanonical ponatinib targets in SCCOHT. Finally, ponatinib delayed tumor doubling time 4-fold in SCCOHT-1 xenografts while reducing final tumor volumes in SCCOHT PDX models by 58.6% and 42.5%.Conclusions: Ponatinib is an effective agent for SMARCA4-mutant SCCOHT in both in vitro and in vivo preclinical models through its inhibition of multiple kinases. Clinical investigation of this FDA-approved oncology drug in SCCOHT is warranted. Clin Cancer Res; 24(8); 1932–43. ©2018 AACR.

Purpose:Many rare ovarian cancer subtypes, such as small-cell carcinoma of the ovary, hypercalcemic type (SCCOHT), have poor prognosis due to their aggressive nature and resistance to standard platinum- and taxane-based chemotherapy. The development of effective therapeutics has been hindered by the rarity of such tumors. We sought to identify targetable vulnerabilities in rare ovarian cancer subtypes.Experimental Design:We compared the global proteomic landscape of six cases each of endometrioid ovarian cancer (ENOC), clear cell ovarian cancer (CCOC), and SCCOHT to the most common subtype, high-grade serous ovarian cancer (HGSC), to identify potential therapeutic targets. IHC of tissue microarrays was used as validation of arginosuccinate synthase (ASS1) deficiency. The efficacy of arginine-depriving therapeutic ADI-PEG20 was assessed in vitro using cell lines and patient-derived xenograft mouse models representing SCCOHT.Results:Global proteomic analysis identified low ASS1 expression in ENOC, CCOC, and SCCOHT compared with HGSC. Low ASS1 levels were validated through IHC in large patient cohorts. The lowest levels of ASS1 were observed in SCCOHT, where ASS1 was absent in 12 of 31 cases, and expressed in less than 5% of the tumor cells in 9 of 31 cases. ASS1-deficient ovarian cancer cells were sensitive to ADI-PEG20 treatment regardless of subtype in vitro. Furthermore, in two cell line mouse xenograft models and one patient-derived mouse xenograft model of SCCOHT, once-a-week treatment with ADI-PEG20 (30 mg/kg and 15 mg/kg) inhibited tumor growth in vivo.Conclusions:Preclinical in vitro and in vivo studies identified ADI-PEG20 as a potential therapy for patients with rare ovarian cancers, including SCCOHT.

Supplemental Figure 1. COV434-pIND20-Brg1 SMARCA4 induction optimization; Supplemental Figure 2. Kinase hits from siRNA screen mapped to kinome dendrogram; Supplemental Figure 3. ClueGo analysis of validated siRNA screen hits.

Supplementary Table 1. Informatic tools utilized in primary canine lung cancer analysis Supplementary Table 2. Extended clinical and multiplatform annotation of primary canine lung cancer cases. Supplementary Table 3 : Sequencing metrics for primary canine lung cancer exome analysis. Supplementary Table 4. Somatic coding SNVs identified by exome sequencing of primary canine lung cancers. Supplementary Table 5. Somatic copy number variants identified by exome sequencing in primary canine lung cancers. Supplementary Table 6. Somatic coding structural variants identified by exome sequencing of primary canine lung cancers. Supplementary Table 7. Canine genomic regions covered by custom amplicon panel. Supplementary Table 8. Sequencing metrics for primary canine lung cancer amplicon analysis. Supplementary Table 9. Somatic coding SNVs identified by panel sequencing of primary canine lung cancers. Supplementary Table 10. Germline SNPs in COSMIC Tier 1 cancer genes identified by exome and panel sequencing in primary canine lung cancers. Supplementary Table 11. Multi-platform validation of HER2 mutations. Supplementary Table 12. Non-invasive detection of HER2V659E in the plasma of primary canine lung cancer patients. Supplementary Table 13. HER2 protein expression and quantification by immunohistochemistry.

Supplemental material and methods

Purpose:Naturally occurring primary canine lung cancers share clinicopathologic features with human lung cancers in never-smokers, but the genetic underpinnings of canine lung cancer are unknown. We have charted the genomic landscape of canine lung cancer and performed functional characterization of novel, recurrent HER2 (ERBB2) mutations occurring in canine pulmonary adenocarcinoma (cPAC).Experimental Design:We performed multiplatform genomic sequencing of 88 primary canine lung tumors or cell lines. Additionally, in cPAC cell lines, we performed functional characterization of HER2 signaling and evaluated mutation-dependent HER2 inhibitor drug dose-response.Results:We discovered somatic, coding HER2 point mutations in 38% of cPACs (28/74), but none in adenosquamous (cPASC, 0/11) or squamous cell (cPSCC, 0/3) carcinomas. The majority (93%) of HER2 mutations were hotspot V659E transmembrane domain (TMD) mutations comparable to activating mutations at this same site in human cancer. Other HER2 mutations were located in the extracellular domain and TMD. HER2V659E was detected in the plasma of 33% (2/6) of dogs with localized HER2V659E tumors. HER2V659E cPAC cell lines displayed constitutive phosphorylation of AKT and significantly higher sensitivity to the HER2 inhibitors lapatinib and neratinib relative to HER2-wild-type cell lines (IC50 < 200 nmol/L in HER2V659E vs. IC50 > 2,500 nmol/L in HER2WT).Conclusions:This study creates a foundation for molecular understanding of and drug development for canine lung cancer. These data also establish molecular contexts for comparative studies in dogs and humans of low mutation burden, never-smoker lung cancer, and mutant HER2 function and inhibition.

Supplemental Table 5. SCCOHT-1 ABPP data; Supplemental Table 6. BIN67 ABPP data.

SDHD encodes subunit D of the succinate dehydrogenase complex, an integral membrane protein. Across cancer types, recurrent SDHD promoter mutations were reported to occur exclusively in melanomas, at a frequency of 4% to 5%. These mutations are predicted to disrupt consensus ETS transcription factor–binding sites and are correlated with both reduced SDHD gene expression and poor prognosis. However, the consequence of these mutations on SDHD expression in melanoma is still unclear. Here, we found that expression of SDHD in melanoma correlated with the expression of multiple ETS transcription factors, particularly in SDHD promoter wild-type samples. Consistent with the predicted loss of ETS transcription factor binding, we observed that recurrent hotspot mutations resulted in decreased luciferase activity in reporter assays. Furthermore, we demonstrated specific GABPA and GABPB1 binding to probes containing the wild-type promoter sequences, with binding disrupted by the SDHD hotspot promoter mutations in both quantitative mass spectrometry and band-shift experiments. Finally, using siRNA-mediated knockdown across multiple melanoma cell lines, we determined that loss of GABPA resulted in reduced SDHD expression at both RNA and protein levels. These data are consistent with a key role for GABPA/B1 as the critical ETS transcription factors deregulating SDHD expression in the context of highly recurrent promoter mutations in melanoma and warrant a detailed search for other recurrent promoter mutations that create or disrupt GABPA consensus sequences. Cancer Res; 77(7); 1649–61. ©2017 AACR.