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Supplementary Figure S1. Computed Tomographic (CT) findings in patient CGLU116. Supplementary Figure S2. CT findings in patient CGLU127. Supplementary Figure S3. CT findings in patient CGLU161. Supplementary Figure S4. Tumor burden kinetics. Supplementary Figure S5. Neoantigen-specific TCR expansion in stimulated T cell cultures for patient CGLU127. Supplementary Figure S6. Neoantigen-specific TCR expansion in stimulated T cell cultures for patient CGLU161. Supplementary Figure S7. Loss of heterozygosity analyses for patient CGLU116. Supplementary Figure S8. Loss of heterozygosity analyses for patient CGLU117. Supplementary Figure S9. Loss of heterozygosity analyses for patient CGLU127. Supplementary Figure S10. Loss of heterozygosity analyses for patient CGLU161. Supplementary Figure S11. TCR clonality analyses for patients CGLU127 and CGLU161. Supplementary Figure S12. TCR clonality analyses for a responder and a non-responder to PD-1 blockade. Supplementary Figure S13. PD-L1 expression in responsive and resistant tumors. Supplementary Figure S14. Eliminated mutations for case CGHN2. Supplementary Figure S15. Comparison of five methods for estimation of tumor purity. Supplementary Figure S16. CD8+ T cell density in resistant tumors.

Supplementary Table S1. Summary of Patient and Sample Characteristics. Supplementary Table S2. Summary of Next-Generation Sequencing Analyses. Supplementary Table S3. Somatic Sequence Alterations*. Supplementary Table S4. Somatic Copy Number Alterations. Supplementary Table S5. Neoantigen Predictions. Supplementary Table S6. Characteristics of a Subset of Eliminated Candidate Neoantigens in the NSCLC patients*. Supplementary Table S7. Summary of Functionally Validated Eliminated, Gained, and Retained cMANAs. Supplementary Table S8. Eliminated MANA-specific T Cell Clonotypes in CGLU116, CGLU127 and CGLU161. Supplementary Table S9. Retained and Gained MANA-specific T Cell Clonotypes in CGLU116. Supplementary Table S10. Allelic Imbalance Analysis and Cellularity Estimates for CGLU116. Supplementary Table S11. Allelic Imbalance Analysis and Cellularity Estimates for CGLU117. Supplementary Table S12. Allelic Imbalance Analysis and Cellularity Estimates for CGLU127. Supplementary Table S13. Allelic Imbalance Analysis and Cellularity Estimates for CGLU161. Supplementary Table S14. Summary of Eliminated Neoantigens in NSCLC Cases. Supplementary Table S15. TCR-beta Sequencing Analysis. Supplementary Table S16. PD-L1 and CD8 Immunohistochemistry. Supplementary Table S17. Regions of Allelic Imbalance. Supplementary Table S18. Tumor Purity and Ploidy Estimates.

Supplementary Figure Legends

Despite the initial successes of immunotherapy, there is an urgent clinical need for molecular assays that identify patients more likely to respond. Here, we report that ultrasensitive measures of circulating tumor DNA (ctDNA) and T-cell expansion can be used to assess responses to immune checkpoint blockade in metastatic lung cancer patients (N = 24). Patients with clinical response to therapy had a complete reduction in ctDNA levels after initiation of therapy, whereas nonresponders had no significant changes or an increase in ctDNA levels. Patients with initial response followed by acquired resistance to therapy had an initial drop followed by recrudescence in ctDNA levels. Patients without a molecular response had shorter progression-free and overall survival compared with molecular responders [5.2 vs. 14.5 and 8.4 vs. 18.7 months; HR 5.36; 95% confidence interval (CI), 1.57–18.35; P = 0.007 and HR 6.91; 95% CI, 1.37–34.97; P = 0.02, respectively], which was detected on average 8.7 weeks earlier and was more predictive of clinical benefit than CT imaging. Expansion of T cells, measured through increases of T-cell receptor productive frequencies, mirrored ctDNA reduction in response to therapy. We validated this approach in an independent cohort of patients with early-stage non–small cell lung cancer (N = 14), where the therapeutic effect was measured by pathologic assessment of residual tumor after anti-PD1 therapy. Consistent with our initial findings, early ctDNA dynamics predicted pathologic response to immune checkpoint blockade. These analyses provide an approach for rapid determination of therapeutic outcomes for patients treated with immune checkpoint inhibitors and have important implications for the development of personalized immune targeted strategies.Significance: Rapid and sensitive detection of circulating tumor DNA dynamic changes and T-cell expansion can be used to guide immune targeted therapy for patients with lung cancer.See related commentary by Zou and Meyerson, p. 1038

Supplementary Table S1. Summary of patient characteristics Supplementary Table S2. Summary of plasma samples analyzed Supplementary Table S3. Summary of peripheral blood lymphocytes and tumor infiltrating lymphocytes samples analyzed Supplementary Table S4. Genes analyzed by TEC-Seq Supplementary Table S5. Summary of TEC-Seq Characteristics Supplementary Table S6. Somatic sequence alterations detected in cfDNA Supplementary Table S7. Mutation Cellularity Analysis for tumor-specific cfDNA variants Supplementary Table S8. TCR-beta sequencing analysis Supplementary Table S9. Differentially abundant clones for CGLU111 Supplementary Table S10. Differentially abundant clones for CGLU117 Supplementary Table S11. Differentially abundant clones for CGLU127 Supplementary Table S12. Differentially abundant clones for CGLU212 Supplementary Table S13. Differentially abundant clones for CGLU135 Supplementary Table S14. Differentially abundant clones for CGLU161 Supplementary Table S15. Differentially abundant clones for CGLU159 Supplementary Table S16. Differentially abundant clones for CGLU162 Supplementary Table S17. Differentially abundant clones for CGLU203 Supplementary Table S18. Differentially abundant clones for CGLU243

Supplementary Figure S1. ctDNA clonal dynamics during anti-PD1 for patients with a clinical response. Supplementary Figure S2. ctDNA clonal dynamics during anti-PD1 for patients with molecular primary resistance. Supplementary Figure S3. ctDNA molecular responses precede radiologic responses. Supplementary Figure S4. Molecular responses correlate with a favorable prognosis. Supplementary Figure S5. Duration of molecular response correlates with progression-free and overall survival. Supplementary Figure S6. Disease prognostication by radiologic imaging at first assessment. Supplementary Figure S7. Differential clinical outcome by molecular responses in patients with radiologically stable disease. Supplementary Figure S8. Disease prognostication by tumor mutation burden. Supplementary Figure S9. ctDNA molecular response more accurately distinguish clinical responders from non-responders compared to clonal tumor mutation burden. Supplementary Figure S10. Molecular responses mirror pathologic responses to anti-PD1 therapy in early stage operable NSCLC. Supplementary Figure S11. TCR clonal dynamics during response and acquired resistance to anti-PD1. Supplementary Figure S12. TCR clonal dynamics for patients with clinical primary resistance. Supplementary Figure S13. Differential VJ gene usage for a patient with clinical response compared to a patient with clinical primary resistance. Supplementary Figure S14. Dynamic changes in pro-inflammatory and immunosuppressive cytokines in early stage NSCLC patients with differential responses to anti-PD1 therapy.

Supplementary Table and Figure Legends

Supplemental Table 1. Clinical and pathologic characteristics of patients included in tissue microarrays Supplementary Figure 1. B7-H4 expression is low in human and mouse lung cancer cell lines in vitro Supplementary Figure 2. B7-H1 expression does not change with MAPK or proliferation inhibition Supplementary Figure 3. Scoring of PD-L1 and pS6 staining in lung adenocarcinoma and squamous cell carcinoma TMAs Supplementary Figure 4. Co-expression of pS6 and PD-L1 staining in TMAs Supplemental Figure 5. The combination of rapamycin and anti-PD-1 antibody decreases KRAS-driven lung tumor growth Supplementary Figure 6. The combination of rapamycin and αPD-1 blockade decreases NNK-derived syngeneic lung tumor growth.

Alterations in EGFR, KRAS, and ALK are oncogenic drivers in lung cancer, but how oncogenic signaling influences immunity in the tumor microenvironment is just beginning to be understood. Immunosuppression likely contributes to lung cancer, because drugs that inhibit immune checkpoints like PD-1 and PD-L1 have clinical benefit. Here, we show that activation of the AKT–mTOR pathway tightly regulates PD-L1 expression in vitro and in vivo. Both oncogenic and IFNγ-mediated induction of PD-L1 was dependent on mTOR. In human lung adenocarcinomas and squamous cell carcinomas, membranous expression of PD-L1 was significantly associated with mTOR activation. These data suggest that oncogenic activation of the AKT–mTOR pathway promotes immune escape by driving expression of PD-L1, which was confirmed in syngeneic and genetically engineered mouse models of lung cancer where an mTOR inhibitor combined with a PD-1 antibody decreased tumor growth, increased tumor-infiltrating T cells, and decreased regulatory T cells. Cancer Res; 76(2); 227–38. ©2015 AACR.

Serum PSA, together with digital rectal examination and imaging of the prostate gland, have remained the gold standard in urological practices for the management of and intervention for prostate cancer. Based on these adopted practices, the limitations of serum PSA in identifying aggressive prostate cancer has led us to evaluate whether urinary PSA levels might have any clinical utility in prostate cancer diagnosis. Utilizing the Access Hybritech PSA assay, we evaluated a total of n = 437 urine specimens from post-DRE prostate cancer patients. In our initial cohort, PSA tests from a total of one hundred and forty-six (n = 146) urine specimens were obtained from patients with aggressive (Gleason Score ≥ 8, n = 76) and non-aggressive (Gleason Score = 6, n = 70) prostate cancer. A second cohort, with a larger set of n = 291 urine samples from patients with aggressive (GS ≥ 7, n = 168) and non-aggressive (GS = 6, n = 123) prostate cancer, was also utilized in our study. Our data demonstrated that patients with aggressive disease had lower levels of urinary PSA compared to the non-aggressive patients, while the serum PSA levels were higher in patients with aggressive prostate disease. The discordance between serum and urine PSA levels was further validated by immuno-histochemistry (IHC) assay in biopsied tumors and in metastatic lesions (n = 62). Our data demonstrated that aggressive prostate cancer was negatively correlated with the PSA in prostate cancer tissues, and, unlike serum PSA, urinary PSA might serve a better surrogate for capitulating tissue milieus to detect aggressive prostate cancer. We further explored the utility of urine PSA as a cancer biomarker, either alone and in combination with serum PSA, and their ratio (serum to urine PSA) to predict disease status. Comparing the AUCs for the urine and serum PSA alone, we found that urinary PSA had a higher predictive power (AUC= 0.732) in detecting aggressive disease. Furthermore, combining the ratios between serum to urine PSA with urine and serum assay enhanced the performance (AUC = 0.811) in predicting aggressive prostate disease. These studies support the role of urinary PSA in combination with serum for detecting aggressive prostate cancer.

BackgroundDespite treatment advancements with immunotherapy, our understanding of response relies on tissue-based, static tumor features such as tumor mutation burden (TMB) and programmed death-ligand 1 (PD-L1) expression. These approaches are limited in capturing the plasticity of tumor–immune system interactions under selective pressure of immune checkpoint blockade and predicting therapeutic response and long-term outcomes. Here, we investigate the relationship between serial assessment of peripheral blood cell counts and tumor burden dynamics in the context of an evolving tumor ecosystem during immune checkpoint blockade.MethodsUsing machine learning, we integrated dynamics in peripheral blood immune cell subsets, including neutrophil-lymphocyte ratio (NLR), from 239 patients with metastatic non-small cell lung cancer (NSCLC) and predicted clinical outcome with immune checkpoint blockade. We then sought to interpret NLR dynamics in the context of transcriptomic and T cell repertoire trajectories for 26 patients with early stage NSCLC who received neoadjuvant immune checkpoint blockade. We further determined the relationship between NLR dynamics, pathologic response and circulating tumor DNA (ctDNA) clearance.ResultsIntegrated dynamics of peripheral blood cell counts, predominantly NLR dynamics and changes in eosinophil levels, predicted clinical outcome, outperforming both TMB and PD-L1 expression. As early changes in NLR were a key predictor of response, we linked NLR dynamics with serial RNA sequencing deconvolution and T cell receptor sequencing to investigate differential tumor microenvironment reshaping during therapy for patients with reduction in peripheral NLR. Reductions in NLR were associated with induction of interferon-γ responses driving the expression of antigen presentation and proinflammatory gene sets coupled with reshaping of the intratumoral T cell repertoire. In addition, NLR dynamics reflected tumor regression assessed by pathological responses and complemented ctDNA kinetics in predicting long-term outcome. Elevated peripheral eosinophil levels during immune checkpoint blockade were correlated with therapeutic response in both metastatic and early stage cohorts.ConclusionsOur findings suggest that early dynamics in peripheral blood immune cell subsets reflect changes in the tumor microenvironment and capture antitumor immune responses, ultimately reflecting clinical outcomes with immune checkpoint blockade.

Background The identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed. In this study, we assessed the protein and KRAS mutation changes associated with samples obtained by these enrichment techniques and evaluated the fraction of neoplastic cells in PDAC for proteomic and genomic analyses. Methods Three fresh frozen PDAC tumors and their tumor-matched normal adjacent tissues (NATs) were obtained from three sampling techniques using bulk, coring, and LMD; and analyzed by TMT-based quantitative proteomics. The protein profiles and characterizations of differentially expressed proteins in three sampling groups were determined. These three PDACs and samples of five additional PDACs obtained by the same three sampling techniques were also subjected to genomic analysis to characterize KRAS mutations. Results The neoplastic cellularity of eight PDACs ranged from less than 10% to over 80% based on morphological review. Distinctive proteomic patterns and abundances of certain tumor-associated proteins were revealed when comparing the tumors and NATs by different sampling techniques. Coring and bulk tissues had comparable proteome profiles, while LMD samples had the most distinct proteome composition compared to bulk tissues. Further genomic analysis of bulk, cored, or LMD samples demonstrated that KRAS mutations were significantly enriched in LMD samples while coring was less effective in enriching for KRAS mutations when bulk tissues contained a relatively low neoplastic cellularity. Conclusions In addition to bulk tissues, samples from LMD and coring techniques can be used for proteogenomic studies. The greatest enrichment of neoplastic cellularity is obtained with the LMD technique.

Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in nonresponding tumors in three immunotherapy treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature and human leukocyte antigen status provided an improved predictor of response to immunotherapy that was independently validated.

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

Background Prostate cancer (PCa) is a heterogeneous group of tumors, including non-aggressive (NAG) and aggressive (AG) subtypes, with variable clinical outcomes. We assessed the diagnostic utility of selected protein markers to identify AG tumors. Methods The TMA was constructed, including NAG and AG. 12 protein markers were evaluated using the TMA by IHC stains. The makers were also evaluated for their potential utility as single or panels for distinguishing AG from NAG tumors. Results The higher expressions of four protein markers, including prostate specific membrane antigen (PSMA), phospho-EGFR, androgen receptor (AR), and P16, were identified in AG tumors of Gleason score 4 and 5. In contrast, Galectin-3, DPP4 and MAN1B1 revealed stronger staining patterns in NAG tumors. Sensitivity and specificity of individual marker varied widely. In tow-marker panels, especially in the panel of DPP4 and PSMA, the specificity was 38.46% at 95% sensitivity. To further improve the detection ability, we combined DPP4 and PSMA with either Galectin-3 or phospho-EGFR into three-marker panels. The specificity achieved >46% at 95% sensitivity and AUC was >0.85. Conclusions Our panels can be used to improve the separation of AG from NAG tumor and to add in the optimization of the treatment strategy for patients.

Prostate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. In order to improve patient outcomes, it is critical to clinically separate aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with aggressive PCa, it is still challenging to separate AG from NAG. To better understand the functional consequences of PCa progression and the unique features of the AG subtype, we studied the proteomic signatures of primary AG, NAG and metastatic PCa. 39 PCa and 10 benign prostate controls in a discovery cohort and 57 PCa in a validation cohort were analyzed using a data-independent acquisition (DIA) SWATH–MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using a validation cohort; and was also compared with a TCGA mRNA expression dataset and confirmed by immunohistochemistry (IHC) using PCa tissue microarray (TMA). 4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed reduced expressions of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates and the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using an independently-collected tumor cohort, correlated with a TCGA mRNA dataset, and confirmed by immunohistochemical stains of PCa tumor microarray (TMA). Our study is the first large-scale proteomics analysis of PCa tissue using a DIA SWATH-MS platform. It provides not only an interrogative proteomic signature of PCa subtypes, but also indicates the critical roles played by certain proteinases during tumor progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in PCa and for the development of a clinical assay to distinguish aggressive from indolent PCa.

Summary Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer, comprising approximately 75% of all kidney tumors. Recent the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) studies have significantly advanced the molecular characterization of RCC and facilitated the development of targeted therapies. Such advances have improved the median survival of patients with advanced disease from less than 10 months prior to 2004 to 30 months by 2011. However, approximately 30% of localized ccRCC patients will nevertheless develop recurrence or metastasis after surgical resection of their tumor. Therefore, it is critical to further analyze potential tumor-associated proteins and their profiles during disease progression. Over the past decade, tremendous effort has been focused on the study of molecular pathways, including genomics, transcriptomics, and proteomics in order to identify potential molecular biomarkers, as well as to facilitate early detection, monitor tumor progression and uncover potentially therapeutic targets. In this review, we focus on recent advances in the proteomic analysis of ccRCC, current strategies and challenges, and perspectives in the field. This insight will highlight the discovery of tumor-associated proteins, and their potential clinical impact on personalized precision-based care in ccRCC.

Despite the initial successes of immunotherapy, there is an urgent clinical need for molecular assays that identify patients more likely to respond. Here, we report that ultrasensitive measures of circulating tumor DNA (ctDNA) and T-cell expansion can be used to assess responses to immune checkpoint blockade in metastatic lung cancer patients (N = 24). Patients with clinical response to therapy had a complete reduction in ctDNA levels after initiation of therapy, whereas nonresponders had no significant changes or an increase in ctDNA levels. Patients with initial response followed by acquired resistance to therapy had an initial drop followed by recrudescence in ctDNA levels. Patients without a molecular response had shorter progression-free and overall survival compared with molecular responders [5.2 vs. 14.5 and 8.4 vs. 18.7 months; HR 5.36; 95% confidence interval (CI), 1.57–18.35; P = 0.007 and HR 6.91; 95% CI, 1.37–34.97; P = 0.02, respectively], which was detected on average 8.7 weeks earlier and was more predictive of clinical benefit than CT imaging. Expansion of T cells, measured through increases of T-cell receptor productive frequencies, mirrored ctDNA reduction in response to therapy. We validated this approach in an independent cohort of patients with early-stage non–small cell lung cancer (N = 14), where the therapeutic effect was measured by pathologic assessment of residual tumor after anti-PD1 therapy. Consistent with our initial findings, early ctDNA dynamics predicted pathologic response to immune checkpoint blockade. These analyses provide an approach for rapid determination of therapeutic outcomes for patients treated with immune checkpoint inhibitors and have important implications for the development of personalized immune targeted strategies. Significance: Rapid and sensitive detection of circulating tumor DNA dynamic changes and T-cell expansion can be used to guide immune targeted therapy for patients with lung cancer. See related commentary by Zou and Meyerson, p. 1038

Purpose To describe a notable response to chemoradiation in a patient with locally advanced squamous cell cancer of the urethra. Materials and Methods Records reviewed of 60-year-old man with 15.3cm squamous cell cancer of the urethra. Treatment response assessed radiographically and pathologically, and post-treatment clinical status determined. Results Patient received 73.8 Gy plus concurrent cisplatin and 5-FU, followed by consolidative surgery. Patient had pathological complete response and remains radiographically disease-free at 28 months. Conclusion Consolidative surgery may be unnecessary even for large squamous cell carcinomas of the urethra following chemoradiation.

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment. Wang et al. perform integrated proteogenomic analysis of adult glioblastoma (GBM), including metabolomics, lipidomics, and single nuclei RNA-Seq, revealing insights into the immune landscape of GBM, cell-specific nature of EMT signatures, histone acetylation in classical GBM, and the existence of signaling hubs which could provide therapeutic vulnerabilities.

Background Proteomic characterization of cancers is essential for a comprehensive understanding of key molecular aberrations. However, proteomic profiling of a large cohort of cancer tissues is often limited by the conventional approaches. Methods We present a proteomic landscape of 16 major types of human cancer, based on the analysis of 126 treatment-naïve primary tumor tissues, 94 tumor-matched normal adjacent tissues, and 12 normal tissues, using mass spectrometry-based data-independent acquisition approach. Results In our study, a total of 8527 proteins were mapped to brain, head and neck, breast, lung (both small cell and non-small cell lung cancers), esophagus, stomach, pancreas, liver, colon, kidney, bladder, prostate, uterus and ovary cancers, including 2458 tissue-enriched proteins. Our DIA-based proteomic approach has characterized major human cancers and identified universally expressed proteins as well as tissue-type-specific and cancer-type-specific proteins. In addition, 1139 therapeutic targetable proteins and 21 cancer/testis (CT) antigens were observed. Conclusions Our discoveries not only advance our understanding of human cancers, but also have implications for the design of future large-scale cancer proteomic studies to assist the development of diagnostic and/or therapeutic targets in multiple cancers.

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

SUMMARY: Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potential roles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters. IN BRIEF: Hu et al. provide an integrated proteomic and glycoproteomic characterization of high-grade serous ovarian carcinomas and relevant non-tumor tissues, which reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes correlated with glycosylation alterations.

Heterotopic pancreas is pancreatic tissue present outside of the normal location of the pancreas. In the presence of cystic degeneration, heterotopic pancreas is clinically significant because of the symptoms it causes and its physical resemblance to cancerous growth. A diagnosis of heterotopic pancreas is achieved with the aid of various endoscopic techniques for tissue removal. Submucosal tunneling endoscopic resection has proven successful for the resection of gastric subepithelial masses. We present a 53-year-old woman undergoing submucosal tunneling endoscopic resection for the resection of a subepithelial gastric cyst caused by heterotopic pancreas with cystic degeneration.

The emergence of castration-resistance is one of the major challenges in the management of patients with advanced prostate cancer. Although the spectrum of systemic therapies that are available for use alongside androgen deprivation for treatment of castration-resistant prostate cancer (CRPC) is expanding, none of these regimens are curative. Therefore, it is imperative to apply systems approaches to identify and understand the mechanisms that contribute to the development of CRPC. Using comprehensive proteomic approaches, we show that a glycosylation-related enzyme, alpha (1,6) fucosyltransferase (FUT8), which is upregulated in CRPC, might be responsible for resistance to androgen deprivation. Mechanistically, we demonstrated that overexpression of FUT8 resulted in upregulation of the cell surface epidermal growth factor receptor (EGFR) and corresponding downstream signaling, leading to increased cell survival in androgen-depleted conditions. We studied the coregulatory mechanisms of EGFR and FUT8 expression in CRPC xenograft models and found that castration induced FUT8 overexpression associated with increased expression of EGFR. Taken together, our findings suggest a crucial role played by FUT8 as a mediator in switching prostate cancer cells from nuclear receptor signaling (androgen receptor) to the cell surface receptor (EGFR) mechanisms in escaping castration-induced cell death. These findings have clinical implication in understanding the role of FUT8 as a master regulator of cell surface receptors in cancer-resistant phenotypes.

Recently, the rapid development and application of mass spectrometry (MS)-based technologies have markedly improved the comprehensive proteomic characterization of global proteome and protein post-translational modifications (PTMs). However, the current conventional approach for global proteomic analysis is often carried out separately from PTM analysis. In our study, we developed an integrated workflow for multiplex analysis of global, glyco-, and phosphor-proteomics using breast cancer patient-derived xenograft (PDX) tumor samples. Our approach included the following steps: trypsin-digested tumor samples were enriched for phosphopeptides through immobilized metal ion affinity chromatography (IMAC), followed by enrichment of glycopeptides through mixed anion exchange (MAX) method, and then the flow-through peptides were analyzed for global proteomics. Our workflow demonstrated an increased identification of peptides and associated proteins in global proteome, as compared to those using the peptides without PTM depletion. In addition to global proteome, the workflow identified phosphopeptides and glycopeptides from the PTM enrichment. We also found a subset of glycans with unique distribution profiles in the IMAC flow-through, as compared to those enriched directly using the MAX method. Our integrated workflow provided an effective platform for simultaneous global proteomic and PTM analysis of biospecimens.

Purpose: To explore the advantages of differentiating inflammatory from malignant thoracic lymph nodes by integrating their features on positron emission tomography (PET) and computed tomography (CT). Material and method: Following institutional review board approval, PET and CT parameters of thoracic lymph nodes were examined based on their pathologic diagnosis via endobronchial ultrasound-guided transbronchial needle aspiration. The standardized uptake value (SUV) of PET and CT findings of the long- and short-axis diameters, axial short to long diameter ratios (S/L), and measured nodal CT values of the lymph nodes were compared and analyzed statistically. Results: A total of 124 lymph nodes from 70 patients were studied. The inflammatory and malignant lymph nodes differed significantly in their SUV (P = 0.008), short-axis diameters (SAD, p

Given the success of immunotherapy (IO), multiple IO-based options exist for advanced non-small cell lung cancer (NSCLC). Currently used biomarkers do not fully predict clinical outcomes and response assessment remains limited to radiological evaluation. Dynamic biomarkers that evaluate both tumor and host immune responses to IO are needed. We studied patients with NSCLC that received IO and chemo-IO to identify predictive and longitudinal biomarkers of clinical response using circulating tumor DNA (ctDNA) and plasma proteomic dynamics. We conducted deep targeted error-correction sequencing (TEC-Seq) of plasma cell-free DNA (cfDNA) and matched white blood cell (WBC) genomic DNA (gDNA) to identify ctDNA variants. We performed multiplexed antibody-based proximity extension assays of serial plasma samples to detect immune-related proteins. From separate training (n=31) and validation (n=29) cohorts, a total of 288 plasma cfDNA and 52 WBC gDNA specimens underwent TEC-Seq. A total of 260 variants were detected in plasma cfDNA and 78 variants in WBC gDNA. Almost a third of the plasma cfDNA variants (32%, n=61 of 188) were also found in WBC gDNA and filtered out. ctDNA variants were identified in 82% of patients (n=50). In the training cohort, longitudinal decreases in ctDNA variant levels were observed in patients with durable clinical benefit (DCB). Molecular response, defined as the loss of detectable ctDNA, was associated with longer progression-free (PFS; p=0.0004, log-rank) and overall survival (OS; p=0.017, log-rank). We incorporated on-treatment ctDNA dynamics including molecular response, recrudescence, and emergence of new variants into a logistic regression model to predict clinical benefit. This integrative model predicted DCB at a sensitivity of 84%, specificity of 76%, and with an area under the curve (AUC) of 0.90, better than baseline tumor PD-L1 expression alone (AUC 0.70, p=0.044, bootstrap method). In the validation cohort, molecular response was associated with longer PFS (p=0.00098, log-rank) and OS (p=0.0037, log-rank) and the integrative model predicted DCB at a sensitivity of 100%, specificity of 78%, and AUC of 0.89. In a subset (n=28 of 31) of the training cohort, plasma proteomics analysis revealed that increased baseline levels of IL15 and DCN were independently associated with DCB (p Citation Format: Joseph C. Murray, Karlijn Hummelink, Lamia Rhymee, Alessandro Leal, Leonardo Ferreira, Mara Lanis, James R. White, Noushin Niknafs, Kristen Marrone, Jarushka Naidoo, Benjamin Levy, Samuel Rosner, Christine Hann, Josephine Feliciano, Vincent Lam, David Ettinger, Qing K. Li, Peter Illei, Kim Monkhorst, Hatim Husain, Julie R. Brahmer, Victor Velculescu, Patrick Forde, Robert B. Scharpf, Valsamo Anagnostou. Longitudinal dynamics of circulating tumor DNA and plasma proteomics predict clinical outcomes to immunotherapy in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1668.

Background In diabetic patients, subcutaneous insulin injection may cause several types of injection site-related lesions, such as lipoatrophy, insulin-induced cutaneous lipohypertrophy (IICL), allergic reaction, and iatrogenic localized insulin-derived amyloidosis (LIDA). Among these complications, both IICL and LIDA present as tumor-like and slow growing lesions; and they may be confused with one another. The clinical implication and management of IICL and LIDA are different. LIDA causes poor blood glycemic controls due to inadequate absorption of the insulin. Thus, accurate diagnosis of the lesion is critical in diabetic patients. Review of literature LIDA is an extremely rare complication and often overlooked, it is managed by a surgical intervention. Whereas, IICL is a common side effect and can be managed by a non-surgical approach. Furthermore, in long-standing diabetics, patients may develop hypertrophic cardiomyopathy, proteinuria, peripheral, and autonomic neuropathy; these symptoms can be mistaken for a systemic amyloidosis. It is also necessary to distinguish LIDA from the systemic amyloidosis, which requires a more aggressive systemic therapy. LIDA should also be distinguished from primary cutaneous amyloidosis, with high risk of progression to a systemic amyloidosis. In this effort we reviewed 25 published manuscripts, including case reports and case series studies. We also summarized the literature and discussed differential diagnosis, including the approach to diagnose LIDA. Conclusion The identification of amyloid material and immunoreactivity with anti-insulin antibodies are key diagnostic features of LIDA. Although several clinical and animal studies were made in recent years, the lesion is still under-diagnosed and underreported. The clinical suspicion and knowledge of the lesion play a crucial role for the accurate diagnosis of LIDA. Surgical excision of the lesion can dramatically decrease insulin requirement and improve glycemic control.

Background: In evaluating patients with suspected lung cancer, it is important to not only obtain a tissue diagnosis, but also to obtain enough tissue for both histologic and molecular analysis in order to appropriately stage the patient with a safe and efficient strategy. The diagnostic approach may often be dependent on local resources and practice patterns rather than current guidelines. We Describe lung cancer staging at two large academic medical centers to identify the impact different procedural approaches have on patient outcomes. Methods: We conducted a retrospective cohort study of all patients undergoing a lung cancer diagnostic evaluation at two multidisciplinary centers during a 1-year period. Identifying complication rates and the need for multiple biopsies as our primary outcomes, we developed a multivariate regression model to determine features associated with complications and need for multiple biopsies. Results: Of 830 patients, 285 patients were diagnosed with lung cancers during the study period. Those staged at the institution without an endobronchial ultrasound (EBUS) program were more likely to require multiple biopsies (OR 3.62, 95% CI: 1.71–7.67, P=0.001) and suffer complications associated with the diagnostic procedure (OR 10.2, 95% CI: 3.08–33.58, P Conclusions: Lung cancer evaluation at centers with a dedicated EBUS program results in fewer biopsies and complications than at multidisciplinary counterparts without an EBUS program.

Immune checkpoint inhibitors have shown significant therapeutic responses against tumors containing increased mutation-associated neoantigen load. We have examined the evolving landscape of tumor neoantigens during the emergence of acquired resistance in patients with non–small cell lung cancer after initial response to immune checkpoint blockade with anti–PD-1 or anti–PD-1/anti–CTLA-4 antibodies. Analyses of matched pretreatment and resistant tumors identified genomic changes resulting in loss of 7 to 18 putative mutation-associated neoantigens in resistant clones. Peptides generated from the eliminated neoantigens elicited clonal T-cell expansion in autologous T-cell cultures, suggesting that they generated functional immune responses. Neoantigen loss occurred through elimination of tumor subclones or through deletion of chromosomal regions containing truncal alterations, and was associated with changes in T-cell receptor clonality. These analyses provide insight into the dynamics of mutational landscapes during immune checkpoint blockade and have implications for the development of immune therapies that target tumor neoantigens. Significance: Acquired resistance to immune checkpoint therapy is being recognized more commonly. This work demonstrates for the first time that acquired resistance to immune checkpoint blockade can arise in association with the evolving landscape of mutations, some of which encode tumor neoantigens recognizable by T cells. These observations imply that widening the breadth of neoantigen reactivity may mitigate the development of acquired resistance. Cancer Discov; 7(3); 264–76. ©2017 AACR. See related commentary by Yang, p. 250. This article is highlighted in the In This Issue feature, p. 235

Intranuclear inclusions are important diagnostic features in many benign and malignant neoplasms. It has also been identifi ed in major epithelial subtypes of renal cell carcinomas (RCCs), particularly in the chromophobe RCC.

Intranuclear inclusions are important diagnostic features in many benign and malignant neoplasms. It has also been identified in major epithelial subtypes of renal cell carcinomas (RCCs), particularly in the chromophobe RCC. However, the finding in ccRCC has not been well studied. The finding of intranuclear inclusions may cause diagnostic difficulty, particularly in metastatic lesions. Herein, we reported a case of ccRCC with prominent intranuclear inclusions. The tumor also metastasized to local lymph nodes. Furthermore, in contrast to previous publications, we also found that intranuclear inclusions were immunoreactive with anti-PAX8 (paired box8) antibody. The potential diagnostic and clinical implications of intranuclear inclusions in ccRCC need to be addressed.

Aim: p16 and p53 are frequently altered intracellular pathways in cancers. We investigated the aberrant expression of p16 and its relationship with p53 and HPV status in primary non-small-cell lung carcinoma. Patients & methods: Lung tumor tissue microarray (n = 163), immunohistochemical study of p16 and p53, and HPV in-situ hybridization were analyzed. Results: p16 and p53 were detected in 50.7 and 57.3% of adenocarcinoma (ADCs; n = 75), and 35.2 and 63.6% of squamous cell carcinoma (n = 88). HPV was detected in 16 and 10.2% of ADC and squamous cell carcinoma. In ADCs, p16 positive tumors demonstrated a favorable median overall survival time of 60.9 months, compared with p16 negative tumors of 46.9 months (p

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Personalized treatment of lung cancer requires an accurate subclassification of non-small cell lung carcinoma (NSCLC) into adenocarcinoma (ADC), squamous cell carcinoma (SqCC), and other subtypes. In poorly differentiated tumors especially on small fine-needle aspirate specimens, the subclassification could be difficult in certain cases. Our previous study using resected tumor tissue has shown that the combination of commonly used individual markers (thyroid transcription factor 1 [TTF-1], P40, and Napsin A) into a novel triple marker has high sensitivity and specificity in subclassification of NSCLC and also the advantage of using minimal tumor tissue. In this study, we further evaluated the utility of this novel triple marker using fine-needle aspirate cases. We included primary NSCLC, consisting of 37 SqCCs (primary, 35; metastasis, 2) and 50 ADCs (primary, 29; metastasis, 21), 12 metastatic ADCs of nonpulmonary primary, and 10 small cell lung carcinomas. The immunohistochemical patterns were semiquantitatively scored. In lung SqCCs and ADCs, the sensitivity and specificity of the triple marker were 100% and 97.1% and 86.0% and 100%, respectively. The triple marker showed no immunoreactivity in 12 metastatic nonpulmonary ADCs. In 10 small cell lung carcinomas, TTF-1 had focal positivity in 40% of cases. The limitations of the triple marker include staining of alveolar macrophages (by TTF-1 and Napsin A), basal layer of bronchial epithelial cells (by P40), and nonspecific cytoplasmic staining of TTF-1. Our study not only supports our previous finding using resected tumor specimens but also provides evidence that the triple marker can be used for cytological material and preserving tumor tissue for molecular testing.