Proteogenomic characterization of primary colorectal cancer and metastatic progression identifies proteome-based subtypes and signatures.

Metastatic progression of colorectal adenocarcinoma (CRC) remains poorly understood and poses significant challenges for treatment. To overcome these challenges, we performed multiomics analyses of primary CRC and liver metastases. Genomic alterations, such as structural variants or copy number alterations, were enriched in oncogenes and tumor suppressor genes and increased in metastases. Unsupervised mass spectrometry-based proteomics of 135 primary and 123 metastatic CRCs uncovered distinct proteomic subtypes, three each for primary and metastatic CRCs, respectively. Integrated analyses revealed that hypoxia, stemness, and immune signatures characterize these 6 subtypes. Hypoxic CRC harbors high epithelial-to-mesenchymal transition features and metabolic adaptation. CRC with a stemness signature shows high oncogenic pathway activation and alternative telomere lengthening (ALT) phenotype, especially in metastatic lesions. Tumor microenvironment analysis shows immune evasion via modulation of major histocompatibility complex (MHC) class I/II and antigen processing pathways. This study characterizes both primary and metastatic CRCs and provides a large proteogenomics dataset of metastatic progression.

Technical report: The clinically useful selection of proteins protocol: An approach to identify clinically useful proteins for validation.

Clinical proteomics studies aiming to develop markers of clinical outcome or disease typically involve distinct discovery and validation stages, neither of which focus on the clinical applicability of the candidate markers studied. Our clinically useful selection of proteins (CUSP) protocol proposes a rational approach, with statistical and non-statistical components, to identify proteins for the validation phase of studies that could be most effective markers of disease or clinical outcome. Additionally, this protocol considers commercially available analysis methods for each selected protein to ensure that use of this prospective marker is easily translated into clinical practice. SIGNIFICANCE: When developing proteomic markers of clinical outcomes, there is currently no consideration at the validation stage of how to implement such markers into a clinical setting. This has been identified by several studies as a limitation to the progression of research findings from proteomics studies. When integrated into a proteomic workflow, the CUSP protocol allows for a strategically designed validation study that improves researchers' abilities to translate research findings from discovery-based proteomics into clinical practice.

Reliability and Variability of Ki-67 Digital Image Analysis Methods for Clinical Diagnostics in Breast Cancer.

Ki-67 is a nuclear protein associated with proliferation, and a strong potential biomarker in breast cancer, but is not routinely measured in current clinical management owing to a lack of standardization. Digital image analysis (DIA) is a promising technology that could allow high-throughput analysis and standardization. There is a dearth of data on the clinical reliability as well as intra- and interalgorithmic variability of different DIA methods. In this study, we scored and compared a set of breast cancer cases in which manually counted Ki-67 has already been demonstrated to have prognostic value (n = 278) to 5 DIA methods, namely Aperio ePathology (Lieca Biosystems), Definiens Tissue Studio (Definiens AG), Qupath, an unsupervised immunohistochemical color histogram algorithm, and a deep-learning pipeline piNET. The piNET system achieved high agreement (interclass correlation coefficient: 0.850) and correlation (R = 0.85) with the reference score. The Qupath algorithm exhibited a high degree of reproducibility among all rater instances (interclass correlation coefficient: 0.889). Although piNET performed well against absolute manual counts, none of the tested DIA methods classified common Ki-67 cutoffs with high agreement or reached the clinically relevant Cohen's κ of at least 0.8. The highest agreement achieved was a Cohen's κ statistic of 0.73 for cutoffs 20% and 25% by the piNET system. The main contributors to interalgorithmic variation and poor cutoff characterization included heterogeneous tumor biology, varying algorithm implementation, and setting assignments. It appears that image segmentation is the primary explanation for semiautomated intra-algorithmic variation, which involves significant manual intervention to correct. Automated pipelines, such as piNET, may be crucial in developing robust and reproducible unbiased DIA approaches to accurately quantify Ki-67 for clinical diagnosis in the future.

The 2023 Report on the Proteome from the HUPO Human Proteome Project.

Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.

Multicenter International Study of the Consensus Immunoscore for the Prediction of Relapse and Survival in Early-Stage Colon Cancer.

Background: The prognostic value of Immunoscore was evaluated in Stage II/III colon cancer (CC) patients, but it remains unclear in Stage I/II, and in early-stage subgroups at risk. An international Society for Immunotherapy of Cancer (SITC) study evaluated the pre-defined consensus Immunoscore in tumors from 1885 AJCC/UICC-TNM Stage I/II CC patients from Canada/USA (Cohort 1) and Europe/Asia (Cohort 2). METHODS: Digital-pathology is used to quantify the densities of CD3+ and CD8+ T-lymphocyte in the center of tumor (CT) and the invasive margin (IM). The time to recurrence (TTR) was the primary endpoint. Secondary endpoints were disease-free survival (DFS), overall survival (OS), prognosis in Stage I, Stage II, Stage II-high-risk, and microsatellite-stable (MSS) patients. RESULTS: High-Immunoscore presented with the lowest risk of recurrence in both cohorts. In Stage I/II, recurrence-free rates at 5 years were 78.4% (95%-CI, 74.4−82.6), 88.1% (95%-CI, 85.7−90.4), 93.4% (95%-CI, 91.1−95.8) in low, intermediate and high Immunoscore, respectively (HR (Hi vs. Lo) = 0.27 (95%-CI, 0.18−0.41); p < 0.0001). In Cox multivariable analysis, the association of Immunoscore to outcome was independent (TTR: HR (Hi vs. Lo) = 0.29, (95%-CI, 0.17−0.50); p < 0.0001) of the patient's gender, T-stage, sidedness, and microsatellite instability-status (MSI). A significant association of Immunoscore with survival was found for Stage II, high-risk Stage II, T4N0 and MSS patients. The Immunoscore also showed significant association with TTR in Stage-I (HR (Hi vs. Lo) = 0.07 (95%-CI, 0.01−0.61); P = 0.016). The Immunoscore had the strongest (69.5%) contribution χ2 for influencing survival. Patients with a high Immunoscore had prolonged TTR in T4N0 tumors even for patients not receiving chemotherapy, and the Immunoscore remained the only significant parameter in multivariable analysis. CONCLUSION: In early CC, low Immunoscore reliably identifies patients at risk of relapse for whom a more intensive surveillance program or adjuvant treatment should be considered.

The 2022 Report on the Human Proteome from the HUPO Human Proteome Project.

The 2022 Metrics of the Human Proteome from the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 407 (93.2%) of the 19 750 predicted proteins coded in the human genome, a net gain of 50 since 2021 from data sets generated around the world and reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 78 from 1421 to 1343. This represents continuing experimental progress on the human proteome parts list across all the chromosomes, as well as significant reclassifications. Meanwhile, applying proteomics in a vast array of biological and clinical studies continues to yield significant findings and growing integration with other omics platforms. We present highlights from the Chromosome-Centric HPP, Biology and Disease-driven HPP, and HPP Resource Pillars, compare features of mass spectrometry and Olink and Somalogic platforms, note the emergence of translation products from ribosome profiling of small open reading frames, and discuss the launch of the initial HPP Grand Challenge Project, "A Function for Each Protein".

Clinical Performance of the Consensus Immunoscore in Colon Cancer in the Asian Population from the Multicenter International SITC Study.

BACKGROUND: In this study, we evaluated the prognostic value of Immunoscore in patients with stage I−III colon cancer (CC) in the Asian population. These patients were originally included in an international study led by the Society for Immunotherapy of Cancer (SITC) on 2681 patients with AJCC/UICC-TNM stages I−III CC. METHODS: CD3+ and cytotoxic CD8+ T-lymphocyte densities were quantified in the tumor and invasive margin by digital pathology. The association of Immunoscore with prognosis was evaluated for time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS). RESULTS: Immunoscore stratified Asian patients (n = 423) into different risk categories and was not impacted by age. Recurrence-free rates at 3 years were 78.5%, 85.2%, and 98.3% for a Low, Intermediate, and High Immunoscore, respectively (HR[Low-vs-High] = 7.26 (95% CI 1.75−30.19); p = 0.0064). A High Immunoscore showed a significant association with prolonged TTR, OS, and DFS (p < 0.05). In Cox multivariable analysis stratified by center, Immunoscore association with TTR was independent (HR[Low-vs-Int+High] = 2.22 (95% CI 1.10−4.55) p = 0.0269) of the patient's gender, T-stage, N-stage, sidedness, and MSI status. A significant association of a High Immunoscore with prolonged TTR was also found among MSS (HR[Low-vs-Int+High] = 4.58 (95% CI 2.27−9.23); p ≤ 0.0001), stage II (HR[Low-vs-Int+High] = 2.72 (95% CI 1.35−5.51); p = 0.0052), low-risk stage-II (HR[Low-vs-Int+High] = 2.62 (95% CI 1.21−5.68); p = 0.0146), and high-risk stage II patients (HR[Low-vs-Int+High] = 3.11 (95% CI 1.39−6.91); p = 0.0055). CONCLUSION: A High Immunoscore is significantly associated with the prolonged survival of CC patients within the Asian population.

Tumor stromal nicotinamide N-methyltransferase overexpression as a prognostic biomarker for poor clinical outcome in early-stage colorectal cancer.

In a quest for prognostic biomarkers in early-stage colorectal cancer, we investigated NNMT (nicotinamide N-methyltransferase) in large cohorts of patients. Immunohistochemical examination of 679 patients illustrates that NNMT protein is predominantly expressed in the cancer stroma at varying levels, and about 20% of cancer tissues overexpress NNMT when compared to levels observed in normal colorectal mucosa. Clinical correlation analyses of 572 patients with early-stage cancers reveal that NNMT protein overexpression is significantly associated with shorter overall and disease-free survival, but no such correlation is found in late-stage colorectal cancer. Analyses of TCGA and CPTAC colorectal cancer cohorts show that NNMT mRNA expression is positively correlated with protein levels, is significantly higher in CIMP-high or MSI subtypes than in CIMP-low or MSS subtypes, and is positively correlated with its paralog INMT but not with its interaction partners such as PNMT, ADK, APP, ATF6, BMF, BRD4, CDC37, or CRYZ. In early-stage cancers, NNMT expression is higher in BRAF-mutated than in BRAF wild type tumors but is not affected by KRAS or PIK3CA mutation status. As a cancer stromal protein with important roles in metabolism and cancer epigenetics, NNMT is emerging as a promising biomarker for risk stratification of early-stage cancers.

Pancreatoblastomas and mixed and pure acinar cell carcinomas share epigenetic signatures distinct from other neoplasms of the pancreas.

Pancreatic neoplasms are heterogenous and have traditionally been classified by assessing their lines of cellular differentiation using histopathologic methods, particularly morphologic and immunohistochemical evaluation. These methods frequently identify overlapping differentiation along ductal, acinar, and neuroendocrine lines, raising diagnostic challenges as well as questions regarding the relationship of these neoplasms. Neoplasms with acinar differentiation, in particular, frequently show more than one line of differentiation based on immunolabeling. Genome methylation signatures, in contrast, are better conserved within cellular lineages, and are increasingly used to support the classification of neoplasms. We characterized the epigenetic relationships between pancreatoblastomas, acinar cell carcinomas (including mixed variants), pancreatic neuroendocrine tumors, solid pseudopapillary neoplasms, and pancreatic ductal adenocarcinomas using a genome-wide array platform. Using unsupervised learning approaches, pancreatic neuroendocrine tumors, solid pseudopapillary neoplasms, ductal adenocarcinomas, and normal pancreatic tissue samples all localized to distinct clusters based on their methylation profiles, whereas all neoplasms with acinar differentiation occupied a broad overlapping region located between the predominantly acinar normal pancreatic tissue and ductal adenocarcinoma clusters. Our data provide evidence to suggest that acinar cell carcinomas and pancreatoblastomas are similar at the epigenetic level. These findings are consistent with genomic and clinical observations that mixed acinar neoplasms are closely related to pure acinar cell carcinomas rather than to neuroendocrine tumors or ductal adenocarcinomas.

Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project.

The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center.

OBJECTIVE: Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes. MATERIALS AND METHODS: We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent. RESULTS: The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence-driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases. CONCLUSIONS: We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.

Multicenter International Society for Immunotherapy of Cancer Study of the Consensus Immunoscore for the Prediction of Survival and Response to Chemotherapy in Stage III Colon Cancer.

PURPOSE: The purpose of this study was to evaluate the prognostic value of Immunoscore in patients with stage III colon cancer (CC) and to analyze its association with the effect of chemotherapy on time to recurrence (TTR). METHODS: An international study led by the Society for Immunotherapy of Cancer evaluated the predefined consensus Immunoscore in 763 patients with American Joint Committee on Cancer/Union for International Cancer Control TNM stage III CC from cohort 1 (Canada/United States) and cohort 2 (Europe/Asia). CD3+ and cytotoxic CD8+ T lymphocyte densities were quantified in the tumor and invasive margin by digital pathology. The primary end point was TTR. Secondary end points were overall survival (OS), disease-free survival (DFS), prognosis in microsatellite stable (MSS) status, and predictive value of efficacy of chemotherapy. RESULTS: Patients with a high Immunoscore presented with the lowest risk of recurrence, in both cohorts. Recurrence-free rates at 3 years were 56.9% (95% CI, 50.3% to 64.4%), 65.9% (95% CI, 60.8% to 71.4%), and 76.4% (95% CI, 69.3% to 84.3%) in patients with low, intermediate, and high immunoscores, respectively (hazard ratio [HR; high v low], 0.48; 95% CI, 0.32 to 0.71; P = .0003). Patients with high Immunoscore showed significant association with prolonged TTR, OS, and DFS (all P < .001). In Cox multivariable analysis stratified by participating center, Immunoscore association with TTR was independent (HR [high v low], 0.41; 95% CI, 0.25 to 0.67; P = .0003) of patient's sex, T stage, N stage, sidedness, and microsatellite instability status. Significant association of a high Immunoscore with prolonged TTR was also found among MSS patients (HR [high v low], 0.36; 95% CI, 0.21 to 0.62; P = .0003). Immunoscore had the strongest contribution χ2 proportion for influencing survival (TTR and OS). Chemotherapy was significantly associated with survival in the high-Immunoscore group for both low-risk (HR [chemotherapy v no chemotherapy], 0.42; 95% CI, 0.25 to 0.71; P = .0011) and high-risk (HR [chemotherapy v no chemotherapy], 0.5; 95% CI, 0.33 to 0.77; P = .0015) patients, in contrast to the low-Immunoscore group (P > .12). CONCLUSION: This study shows that a high Immunoscore significantly associated with prolonged survival in stage III CC. Our findings suggest that patients with a high Immunoscore will benefit the most from chemotherapy in terms of recurrence risk.

A combined FAK, c-MET, and MST1R three-protein panel risk-stratifies colorectal cancer patients.

Focal adhesion kinase (FAK) is a key tyrosine kinase downstream of c-MET (or hepatocyte growth factor receptor, HGFR) and MST1R (macrophage-stimulating protein receptor or recepteur d'origine Nantais, RON) membrane receptors. The pathway plays an important role in cancer survival and invasion. In this study, we examined the protein expression of FAK, c-MET, and MST1R levels in a well-annotated cohort of 330 colorectal cancer patients. We found FAK to be overexpressed in colorectal adenocarcinomas (p = 0.0002), and FAK levels correlated positively with phospho-FAK levels (R2 = 0.81). In comparison, MST1R levels were not significantly different, and c-MET levels were slightly higher in the normal samples. We then developed a combined 3-protein panel of FAK, c-MET, and MST1R expression signatures that can robustly risk-stratify colorectal cancer across all stages into three clusters that differ in progression-free survival. The colorectal cancer subgroup with high FAK, low c-MET, and low MST1R protein levels showed the worst progression-free survival with particularly early progression of disease (p = 0.0053). Combined FAK, c-MET, and MST1R were independently prognostic for progression-free survival in stage II colorectal cancers in a multivariate model. The 3-protein panel provides a potentially clinically attractive method for risk-stratification and adjuvant therapy guidance, especially in stage II disease.

An Investigation Into the Prognostic Significance of High Proteasome PSB7 Protein Expression in Colorectal Cancer.

Using unbiased proteomics, we had previously discovered that the catalytic proteasome subunit ß type 7 (PSB7) protein is frequently overexpressed in colorectal adenocarcinomas. In this paper, we validate this finding and derive a prognostic significance for PSB7 by examining an expanded, well-annotated clinical cohort of 318 colorectal cancer patients. We found PSB7 protein levels to be similarly increased in both advanced stage primary disease and metastatic lesions. We then examined the prognostic value of PSB7 protein expression. Elevated PSB7 protein as well as PSMB7 mRNA levels showed associations with lower overall survival, particularly in female patients. The prognostic value of elevated PSB7 protein levels was highest for female patients who were older (>60 years of age at diagnosis) or who had received adjuvant chemotherapy. While high PSB7 did not retain its prognostic significance on multivariate analysis, we discuss the potential significance of PSB7 as a biomarker, considering its differential prognostic strength in different colorectal cancer patient groups and given its role as a subunit of the immunoproteasome for antigen presentation.

Mass spectrometry-based absolute quantification of amyloid proteins in pathology tissue specimens: Merits and limitations.

To clarify the significance of quantitative analyses of amyloid proteins in clinical practice and in research relating to systemic amyloidoses, we applied mass spectrometry-based quantification by isotope-labeled cell-free products (MS-QBIC) to formalin-fixed, paraffin-embedded (FFPE) tissues. The technique was applied to amyloid tissues collected by laser microdissection of Congo red-stained lesions of FFPE specimens. Twelve of 13 amyloid precursor proteins were successfully quantified, including serum amyloid A (SAA), transthyretin (TTR), immunoglobulin kappa light chain (IGK), immunoglobulin lambda light chain (IGL), beta-2-microglobulin (B2M), apolipoprotein (Apo) A1, Apo A4, Apo E, lysozyme, Apo A2, gelsolin, and fibrinogen alpha chain; leukocyte cell-derived chemotaxin-2 was not detected. The quantification of SAA, TTR, IGK, IGL, and B2M confirmed the responsible proteins, even when the immunohistochemical results were not decisive. Considerable amounts of Apo A1, Apo A4, and Apo E were deposited in parallel amounts with the responsible proteins. Quantification of amyloid protein by MS-QBIC is feasible and useful for the classification of and research on systemic amyloidoses.

Maspin as a Prognostic Marker for Early Stage Colorectal Cancer With Microsatellite Instability.

Colorectal cancers are among the most common cancers and a leading cause of cancer death. In our pursuit to discover molecular markers for better characterization and precision theranostics of these cancers, we first conducted global deep proteome analyses and identified maspin (serpin B5, peptidase inhibitor 5) as an upregulated protein in tumor tissue. We then validated its expression in a large cohort of 743 patients with colorectal cancers of all stages and found that both cytoplasmic and nuclear expression varied widely between different patients. Comparison with clinicopathological features revealed that maspin expression levels correlate significantly only with mismatch repair (MMR) status but not with other features. To elucidate the prognostic significance of maspin, we analyzed two outcome-annotated cohorts, one of 572 early stage cancer patients and another of 93 late stage cancer patients. Kaplan-Meier survival, univariate, and multivariate analyses revealed that maspin overexpression predicts longer overall and disease-free survival for early stage microsatellite instability (MSI) subtype colorectal cancer, but there is no correlation with survival for patients with early stage cancer of the microsatellite stability (MSS) subtype or late stage cancer. Our study identifies maspin expression as an independent prognostic marker for risk stratification of early stage MSI subtype colorectal cancer and may provide guidance for improved therapeutic management.

Latency and interval therapy affect the evolution in metastatic colorectal cancer.

While comparison of primary tumor and metastases has highlighted genomic heterogeneity in colorectal cancer (CRC), previous studies have focused on a single metastatic site or limited genomic testing. Combining data from whole exome and ultra-deep targeted sequencing, we explored possible evolutionary trajectories beyond the status of these mutations, particularly among patient-matched metastatic tumors. Our findings confirm the persistence of known clinically-relevant mutations (e.g., those of RAS family of oncogenes) in CRC primary and metastases, yet reveal that latency and interval systemic therapy affect the course of evolutionary events within metastatic lesions. Specifically, our analysis of patient-matched primary and multiple metastatic lesions, developed over time, showed a similar genetic composition for liver metastatic tumors, which were 21-months apart. This genetic makeup was different from those identified in lung metastases developed before manifestation of the second liver metastasis. These results underscore the role of latency in the evolutionary path of metastatic CRC and may have implications for future treatment options.

Integration of Genomic and Transcriptional Features in Pancreatic Cancer Reveals Increased Cell Cycle Progression in Metastases.

We integrated clinical, genomic, and transcriptomic data from 224 primaries and 95 metastases from 289 patients to characterize progression of pancreatic ductal adenocarcinoma (PDAC). Driver gene alterations and mutational and expression-based signatures were preserved, with truncations, inversions, and translocations most conserved. Cell cycle progression (CCP) increased with sequential inactivation of tumor suppressors, yet remained higher in metastases, perhaps driven by cell cycle regulatory gene variants. Half of the cases were hypoxic by expression markers, overlapping with molecular subtypes. Paired tumor heterogeneity showed cancer cell migration by Halstedian progression. Multiple PDACs arising synchronously and metachronously in the same pancreas were actually intra-parenchymal metastases, not independent primary tumors. Established clinical co-variates dominated survival analyses, although CCP and hypoxia may inform clinical practice.

Somatic HNF1A mutations in the malignant transformation of hepatocellular adenomas: a retrospective analysis of data from MSK-IMPACT and TCGA.

Mutations of Hepatocyte-Nuclear-Factor-1-Homeobox-A (HNF1A) gene and loss of Liver-Fatty-Acid-Binding-Protein (LFABP) are well documented in hepatocellular adenoma. However, the role of HNF1A mutations in hepatocellular carcinoma remains to be determined. In this study, all hepatocellular neoplasms evaluated by our institutional Memorial Sloan Kettering-Integrated Mutational Profiling of Actionable Clinical Targets assay or the Cancer Genome Atlas sequencing, and cases reported in the literature, were queried for HNF1A mutations. Together, 11 of 672 (1.6%) hepatocellular carcinomas harbored HNF1A mutations. The single case from our institution (n = 153) was extremely well differentiated, arising in a background of adenomatosis. Both the adenoma and carcinoma component contained the same 2 somatic HNF1A mutations (p. E32* and L214Q), with loss of LFABP. From the literature, 2 of 146 (1.4%) hepatocellular carcinomas had HNF1A mutations, and both arose in a background of adenomatosis. Information on pre-existing adenoma for the remaining cases (8/373, from The Cancer Genome Atlas) was not available. HNF1A mutations in carcinomas were associated with negative viral hepatitis status (p = .004), mutually exclusive with catenin beta-1 (CTNNB1) hotspot mutations, and trended to occur more in females (p = .06) and without cirrhosis (p = .03). Grade was not associated with HNF1A status (p = .28). Somatic HNF1A mutations occur in approximately 1% to 2% of hepatocellular carcinoma, often in a background of adenomatosis. Our findings suggest that malignant transformation of HNF1A-mutated hepatocellular adenoma occurs, albeit infrequently. Hepatocellular adenomas with HNF1A mutation or adenomatosis with loss of LFABP warrant thorough sampling and examination.

Sensitive tumour detection and classification using plasma cell-free DNA methylomes.

The use of liquid biopsies for cancer detection and management is rapidly gaining prominence1. Current methods for the detection of circulating tumour DNA involve sequencing somatic mutations using cell-free DNA, but the sensitivity of these methods may be low among patients with early-stage cancer given the limited number of recurrent mutations2-5. By contrast, large-scale epigenetic alterations-which are tissue- and cancer-type specific-are not similarly constrained6 and therefore potentially have greater ability to detect and classify cancers in patients with early-stage disease. Here we develop a sensitive, immunoprecipitation-based protocol to analyse the methylome of small quantities of circulating cell-free DNA, and demonstrate the ability to detect large-scale DNA methylation changes that are enriched for tumour-specific patterns. We also demonstrate robust performance in cancer detection and classification across an extensive collection of plasma samples from several tumour types. This work sets the stage to establish biomarkers for the minimally invasive detection, interception and classification of early-stage cancers based on plasma cell-free DNA methylation patterns.