Organized proteomic heterogeneity in colorectal cancer liver metastases and implications for therapies

Somatic Mutations in Surgically Treated Colorectal Liver Metastases: An Overview

Colorectal cancer is the second most common cause of cancer death in the United States, and up to half of patients develop colorectal liver metastases (CRLMs). Notably, somatic genetic mutations, such as mutations in RAS, BRAF, mismatch repair (MMR) genes, TP53, and SMAD4, have been shown to play a prognostic role in patients with CRLM. This review summarizes and appraises the current literature regarding the most relevant somatic mutations in surgically treated CRLM by not only reviewing representative studies, but also providing recommendations for areas of future research. In addition, advancements in genetic testing and an increasing emphasis on precision medicine have led to a more nuanced understanding of these mutations; thus, more granular data for each mutation are reviewed when available. Importantly, such knowledge can pave the way for precision medicine with the ultimate goal of improving patient outcomes.

Use of tryptic peptide MALDI mass spectrometry imaging to identify the spatial proteomic landscape of colorectal cancer liver metastases

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide. CRC liver metastases (CRLM) are often resistant to conventional treatments, with high rates of recurrence. Therefore, it is crucial to identify biomarkers for CRLM patients that predict cancer progression. This study utilised matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially map the CRLM tumour proteome. CRLM tissue microarrays (TMAs) of 84 patients were analysed using tryptic peptide MALDI-MSI to spatially monitor peptide abundances across CRLM tissues. Abundance of peptides was compared between tumour vs stroma, male vs female and across three groups of patients based on overall survival (0-3 years, 4-6 years, and 7+ years). Peptides were then characterised and matched using LC-MS/MS. A total of 471 potential peptides were identified by MALDI-MSI. Our results show that two unidentified m/z values (1589.876 and 1092.727) had significantly higher intensities in tumours compared to stroma. Ten m/z values were identified to have correlation with biological sex. Survival analysis identified three peptides (Histone H4, Haemoglobin subunit alpha, and Inosine-5'-monophosphate dehydrogenase 2) and two unidentified m/z values (1305.840 and 1661.060) that were significantly higher in patients with shorter survival (0-3 years relative to 4-6 years and 7+ years). This is the first study using MALDI-MSI, combined with LC-MS/MS, on a large cohort of CRLM patients to identify the spatial proteome in this malignancy. Further, we identify several protein candidates that may be suitable for drug targeting or for future prognostic biomarker development.

Lipid Nanoparticles-Based Therapy in Liver Metastasis Management: From Tumor Cell-Directed Strategy to Liver Microenvironment-Directed Strategy

Metastasis to the liver, as one of the most frequent metastatic patterns, was associated with poor prognosis. Major drawbacks of conventional therapies in liver metastasis were the lack of metastatic-targeting ability, predominant systemic toxicities and incapability of tumor microenvironment modulations. Lipid nanoparticles-based strategies like galactosylated, lyso-thermosensitive or active-targeting chemotherapeutics liposomes have been explored in liver metastasis management. This review aimed to summarize the state-of-art lipid nanoparticles-based therapies in liver metastasis management. Clinical and translational studies on the lipid nanoparticles in treating liver metastasis were searched up to April, 2023 from online databases. This review focused not only on the updates in drug-encapsulated lipid nanoparticles directly targeting metastatic cancer cells in treating liver metastasis, but more importantly on research frontiers in drug-loading lipid nanoparticles targeting nonparenchymal liver tumor microenvironment components in treating liver metastasis, which showed promise for future clinical oncological practice.

High-throughput proteomics profiling-derived signature associated with chemotherapy response and survival for stage II/III colorectal cancer

Adjuvant chemotherapy (ACT) is usually used to reduce the risk of disease relapse and improve survival for stage II/III colorectal cancer (CRC). However, only a subset of patients could benefit from ACT. Thus, there is an urgent need to identify improved biomarkers to predict survival and stratify patients to refine the selection of ACT. We used high-throughput proteomics to analyze tumor and adjacent normal tissues of stage II/III CRC patients with /without relapse to identify potential markers for predicting prognosis and benefit from ACT. The machine learning approach was applied to identify relapse-specific markers. Then the artificial intelligence (AI)-assisted multiplex IHC was performed to validate the prognostic value of the relapse-specific markers and construct a proteomic-derived classifier for stage II/III CRC using 3 markers, including FHL3, GGA1, TGFBI. The proteomics profiling-derived signature for stage II/III CRC (PS) not only shows good accuracy to classify patients into high and low risk of relapse and mortality in all three cohorts, but also works independently of clinicopathologic features. ACT was associated with improved disease-free survival (DFS) and overall survival (OS) in stage II (pN0) patients with high PS and pN2 patients with high PS. This study demonstrated the clinical significance of proteomic features, which serve as a valuable source for potential biomarkers. The PS classifier provides prognostic value for identifying patients at high risk of relapse and mortality and optimizes individualized treatment strategy by detecting patients who may benefit from ACT for survival.

TGFβ and the Tumor Microenvironment in Colorectal Cancer

Growing evidence supports an important role of the tumor microenvironment (TME) in the pathogenesis of colorectal cancer (CRC). Resident cells such as fibroblasts or immune cells infiltrating into the TME maintain continuous crosstalk with cancer cells and thereby regulate CRC progression. One of the most important molecules involved is the immunoregulatory cytokine transforming growth factor-β (TGFβ). TGFβ is released by various cells in the TME, including macrophages and fibroblasts, and it modulates cancer cell growth, differentiation, and cell death. Mutations in components of the TGF pathway, including TGFβ receptor type 2 or SMAD4, are among the most frequently detected mutations in CRC and have been associated with the clinical course of disease. Within this review, we will discuss our current understanding about the role of TGFβ in the pathogenesis of CRC. This includes novel data on the molecular mechanisms of TGFβ signaling in TME, as well as possible strategies for CRC therapy targeting the TGFβ pathway, including potential combinations with immune checkpoint inhibitors.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Characterization of Genomic Alterations in Colorectal Liver Metastasis and Their Prognostic Value

Colorectal liver metastases (CRLMs) are clinically heterogeneous lesions with poor prognosis. Genetic alterations play a crucial role in their progression. The traditional Fong clinical risk score (Fong-CRS) is commonly used for risk stratification and prognosis prediction. By identifying the genomic alterations of CRLMs, we aimed to develop a mutation-based gene-signature-based clinical score (mut-CS) system to improve clinical prognostication. Tumour tissues from 144 patients with CRLMs were analysed with next-generation sequencing (NGS). A mut-CS scoring system considering the unique mutation-based gene signature, primary site, and Fong-CRS was developed and could identify CRLM patients with poor prognosis. The mean time-dependent receiver operating characteristic curve AUC value of the mut-CS system was greater than that of previously established scoring measures (the Fong-CRS, the e-clinical score, the presence of concomitant RAS and TP53 mutations, and other clinical traits). Taking together, we identified a mutant signature that exhibits a strong prognostic effect for CRLMs. Traditional clinical scoring system characteristics were incorporated into the new mut-CS scoring system to help determine the appropriate treatment for CRLMs.

Proteomic Profiling and Biomarker Discovery in Colorectal Liver Metastases

Colorectal liver metastases (CRLM) are the leading cause of death among patients with metastatic colorectal cancer (CRC). As part of multimodal therapy, liver resection is the mainstay of curative-intent treatment for select patients with CRLM. However, effective treatment of CRLM remains challenging as recurrence occurs in most patients after liver resection. Proposed clinicopathologic factors for predicting recurrence are inconsistent and lose prognostic significance over time. The rapid development of next-generation sequencing technologies and decreasing DNA sequencing costs have accelerated the genomic profiling of various cancers. The characterisation of genomic alterations in CRC has significantly improved our understanding of its carcinogenesis. However, the functional context at the protein level has not been established for most of this genomic information. Furthermore, genomic alterations do not always result in predicted changes in the corresponding proteins and cancer phenotype, while post-transcriptional and post-translational regulation may alter synthesised protein levels, affecting phenotypes. More recent advancements in mass spectrometry-based technology enable accurate protein quantitation and comprehensive proteomic profiling of cancers. Several studies have explored proteomic biomarkers for predicting CRLM after oncologic resection of primary CRC and recurrence after curative-intent resection of CRLM. The current review aims to rationalise the proteomic complexity of CRC and explore the potential applications of proteomic biomarkers in CRLM.

Radiation-Induced Overexpression of TGFβ and PODXL Contributes to Colorectal Cancer Cell Radioresistance through Enhanced Motility

The primary cause of colorectal cancer (CRC) recurrence is increased distant metastasis after radiotherapy, so there is a need for targeted therapeutic approaches to reduce the metastatic-relapse risk. Dysregulation of the cell-surface glycoprotein podocalyxin-like protein (PODXL) plays an important role in promoting cancer-cell motility and is associated with poor prognoses for many malignancy types. We found that CRC cells exposed to radiation demonstrated increased TGFβ and PODXL expressions, resulting in increased migration and invasiveness due to increased extracellular matrix deposition. In addition, both TGFβ and PODXL were highly expressed in tissue samples from radiotherapy-treated CRC patients compared to those from patients without this treatment. However, it is unclear whether TGFβ and PODXL interactions are involved in cancer-progression resistance after radiation exposure in CRC. Here, using CRC cells, we showed that silencing PODXL blocked radiation-induced cell migration and invasiveness. Cell treatment with galunisertib (a TGFβ-pathway inhibitor) also led to reduced viability and migration, suggesting that its clinical use may enhance the cytotoxic effects of radiation and lead to the effective inhibition of CRC progression. Overall, the results demonstrate that downregulation of TGFβ and its-mediated PODXL may provide potential therapeutic targets for patients with radiotherapy-resistant CRC.

The role of the extracellular matrix protein TGFBI in cancer

The secreted extracellular protein, transforming growth factor beta induced (TGFBI or βIGH3), has roles in regulating numerous biological functions, including cell adhesion and bone formation, both during embryonic development and during the pathogenesis of human disease. TGFBI has been most studied in the context of hereditary corneal dystrophies, where mutations in TGFBI result in accumulation of TGFBI in the cornea. In cancer, early studies focused on TGFBI as a tumor suppressor, in part by promoting chemotherapy sensitivity. However, in established tumors, TGFBI largely has a role in promoting tumor progression, with elevated levels correlating to poorer clinical outcomes. As an important regulator of cancer progression, TGFBI expression and function is tightly regulated by numerous mechanisms including epigenetic silencing through promoter methylation and microRNAs. Mechanisms to target TGFBI have potential clinical utility in treating advanced cancers, while assessing TGFBI levels could be a biomarker for chemotherapy resistance and tumor progression.

Metastatic colorectal cancer cells maintain the TGFβ program and use TGFBI to fuel angiogenesis

Colorectal cancer (CRC) cells are traditionally considered unresponsive to TGFβ due to mutations in the receptors and/or downstream signaling molecules. TGFβ influences CRC cells only indirectly via stromal cells, such as cancer-associated fibroblasts. However, CRC cell ability to directly respond to TGFβ currently remains unexplored. This represents a missed opportunity for diagnostic and therapeutic interventions. Methods: We examined whether cancer cells from primary CRC and liver metastases respond to TGFβ by inducing TGFβ-induced protein ig-h3 (TGFBI) expression, and the contribution of canonical and non-canonical TGFβ signaling pathways to this effect. We then investigated in vitro and in vivo TGFBI impact on metastasis formation and angiogenesis. Using patient serum samples and an orthotopic mouse model of CRC liver metastases we assessed the diagnostic/tumor targeting value of novel antibodies against TGFBI. Results: Metastatic CRC cells, such as circulating tumor cells, directly respond to TGFβ. These cells were characterized by the absence of TGFβ receptor mutations and the frequent presence of p53 mutations. The pro-tumorigenic program orchestrated by TGFβ in CRC cells was mediated through TGFBI, the expression of which was positively regulated by non-canonical TGFβ signaling cascades. TGFBI inhibition was sufficient to significantly reduce liver metastasis formation in vivo. Moreover, TGFBI pro-tumorigenic function was linked to its ability to stimulate angiogenesis. TGFBI levels were higher in serum samples from untreated patients with CRC than in patients who were receiving chemotherapy. A radiolabeled anti-TGFBI antibody selectively targeted metastatic lesions in vivo, underscoring its diagnostic and therapeutic potential. Conclusions: TGFβ signaling in CRC cells directly contributes to their metastatic potential and stromal cell-independence. Proteins downstream of activated TGFβ, such as TGFBI, represent novel diagnostic and therapeutic targets for more specific anti-metastatic therapies.

Role of TGF-Beta and Smad7 in Gut Inflammation, Fibrosis and Cancer

The human gastrointestinal tract contains the largest population of immune cells in the body and this is a reflection of the fact that it is continuously exposed to a myriad of dietary and bacterial antigens. Although these cells produce a variety of inflammatory cytokines that could potentially promote tissue damage, in normal conditions the mucosal immune response is tightly controlled by counter-regulatory factors, which help induce and maintain gut homeostasis and tolerance. One such factor is transforming growth factor (TGF)-β1, a cytokine produced by multiple lineages of leukocytes, stromal cells and epithelial cells, and virtually targets all the gut mucosal cell types. Indeed, studies in animals and humans have shown that defects in TGF-β1 production and/or signaling can lead to the development of immune-inflammatory pathologies, fibrosis and cancer in the gut. Here, we review and discuss the available evidence about the role of TGF-β1 and Smad7, an inhibitor of TGF-β1 activity, in gut inflammation, fibrosis and cancer with particular regard to the contribution of these two molecules in the pathogenesis of inflammatory bowel diseases and colon cancer.

High Stromal TGFBI in Lung Cancer and Intratumoral CD8-Positive T Cells were Associated with Poor Prognosis and Therapeutic Resistance to Immune Checkpoint Inhibitors

BACKGROUND

We investigated whether the expression of transforming growth factor-beta-induced protein (TGFBI) and intratumoral immune cells including CD8- and Forkhead box protein P3 (Foxp3)-positive T cells in clinical lung cancer patients could predict the therapeutic response to nivolumab.

METHODS

Thirty-three patients who were treated with nivolumab were enrolled in this study. Immunohistochemical analyses of TGFBI, PD-L1, CD8, Foxp3, and vimentin expression were conducted. Serum concentrations of TGFBI and transforming growth factor-beta1 (TGF-β1) were determined by enzyme-linked immunosorbent assay (ELISA).

RESULTS

Cancer TGFBI was not associated with prognosis and therapeutic response to nivolumab, but cancer stromal TGFBI and intratumoral CD8-positive T cells were associated with them. Therefore, we evaluated cancer stromal TGFBI and intratumoral CD8-positive T cells. The high-TGFBI-expression group had poorer clinical responses than did the low-TGFBI-expression group (p < 0.0001). The number of times nivolumab was administered in the high-CD8-expression group was significantly higher than that in the low-CD8-expression group (p = 0.0046). The high-CD8-expression group had better clinical responses than did the low-CD8-expression group (p = 0.0013). Interestingly, all patients in the high-TGFBI/low-CD8-expression group had progressive disease (PD). In contrast, all patients in the low-TGFBI/high-CD8-expression group had PR + SD (partial response + stable disease) by the Response Evaluation Criteria in Solid Tumors (RECIST 1.1).

CONCLUSIONS

The dual evaluation of stromal TGFBI and intratumoral CD8-positive T cells could be a useful predictive marker for nivolumab.

Genotyping of Circulating Tumor DNA Reveals the Clinically Actionable Mutation Landscape of Advanced Colorectal Cancer

Circulating tumor DNA (ctDNA) enables genomic profiling of colorectal cancer. We investigated therapeutic targets by performing ctDNA panel-captured sequencing of 152 blood samples from advanced stage patients, from which somatic mutations and potentially actionable targets were evaluated. An additional 11 matched tissue samples were retrospectively obtained to verify target validity. The mutation frequencies of 1,127 collective genetic variants identified in our study strongly correlated with those of multiple public databases (Pearson R ² = 0.92, P < 0.0001). The clonal fraction of driver genes was 90.3%, which was significantly higher than that of potential passenger genes (58.12%). Totally, 90 drug-sensitive genes from 56 patients (36.84%) were identified, including recurring targets PIK3CA, FBXW7, EGFR, BRAF, and NRAS Various resistance mechanisms of anti-EGFR antibodies were revealed via ctDNA profiling, with 29 patients individually exhibiting multiple mechanisms, suggesting considerable resistance heterogeneity in our study population. Of the matched tissue/blood pairs, 88.14% of tissue-derived mutations were detected in ctDNA, and 88.9% of actionable targets were validated. The mutational landscape of ctDNA was highly consistent with tissue databases, and ctDNA profiling showed favorable concordance with tumor tissues in our matched analysis. Thus, comprehensive ctDNA genotyping is a promising noninvasive alternative to biopsy-derived analysis for determining targeted therapy in advanced colorectal cancer.

The Role of TGF-β and Its Receptors in Gastrointestinal Cancers

Early detection of gastrointestinal tumors improves patient survival. However, patients with these tumors are typically diagnosed at an advanced stage and have poor prognosis. The incidence and mortality of gastrointestinal cancers, including esophageal, gastric, liver, colorectal, and pancreatic cancers, are increasing worldwide. Novel diagnostic and therapeutic agents are required to improve patient survival and quality of life. The tumor microenvironment, which contains nontumor cells, signaling molecules such as growth factors and cytokines, and extracellular matrix proteins, plays a critical role in cancer cell proliferation, invasion, and metastasis. Transforming growth factor beta (TGF-β) signaling has dual roles in gastrointestinal tumor development and progression as both a tumor suppressor and tumor promoter. Here, we review the dynamic roles of TGF-β and its receptors in gastrointestinal tumors and provide evidence that targeting TGF-β signaling may be an effective therapeutic strategy.

Molecular and Immunohistochemical Markers with Prognostic and Predictive Significance in Liver Metastases from Colorectal Carcinoma

Despite the significant recent achievements in the diagnosis and treatment of colorectal cancer (CRC), the prognosis of these patients has currently plateaued. During the past few years, the opportunity to consider multiple treatment modalities (including surgery and other locoregional treatments, systemic therapy, and targeted therapy) led to the research of novel prognostic and predictive biomarkers in CRC liver metastases (CRCLM) patients. In this review, we seek to describe the current state of knowledge of CRCLM biomarkers and to outline impending clinical perspectives, in particular focusing on the cutting-edge tools available for their characterization.

Identification and characterization of transforming growth factor beta-induced in circulating tumor cell subline from pancreatic cancer cell line

Distant metastasis to liver, lung, brain, or bone occurs by circulating tumor cells (CTC). We hypothesized that a subset of CTC had features that are more malignant than tumor cells at the primary site. We established a highly malignant cell line, Panc-1-CTC, derived from the human pancreatic cancer cell line Panc-1 using an in vivo selection method. Panc-1-CTC cells showed greater migratory and invasive abilities than its parent cell line in vitro. In addition, Panc-1-CTC cells had a higher tumor-forming ability than parent cells in vivo. To examine whether a difference in malignant phenotypes exists between Panc-1-CTC cells and parent cells, we carried out comprehensive gene expression array analysis. As a result, Panc-1-CTC significantly expressed transforming growth factor beta-induced (TGFBI), an extracellular matrix protein, more abundantly than did parent cells. TGFBI is considered to regulate cell adhesion, but its functions remain unclear. In the present study, knockdown of TGFBI reduced cell migration and invasion abilities, whereas overexpression of TGFBI increased both abilities. Moreover, elevated expression of TGFBI was associated with poor prognosis in patients with pancreatic cancer.

LTBP2 promotes the migration and invasion of gastric cancer cells and predicts poor outcome of patients with gastric cancer

Latent transforming growth factor-β-binding protein (LTBP)2 is a member of the fibrillin/LTBP superfamily of extracellular matrix proteins, and has been demonstrated to exhibit tumor-promoting and tumor-suppressive functions in different types of cancer. However, the function of LTBP2 in gastric cancer (GC) remains unknown. The aim of the present study was to investigate the expression and molecular function of LTBP2 in GC, and to evaluate its prognostic value for patients with GC. The results revealed that the expression of LTBP2 was upregulated in GC tissues and cell lines. Increased LTBP2 expression was associated with poor overall survival in patients with early-stage [tumor-node-metastasis (TNM) I/II] and late-stage (TNM III/IV) GC. Furthermore, silencing of LTBP2 effectively suppressed the proliferation, migration, invasion and epithelial-mesenchymal transition in GC cells. These results suggested that LTBP2 may be considered as a potential therapeutic target and a promising prognostic biomarker for human GC.

Metabolic Reprogramming and the Recovery of Physiological Functionality in 3D Cultures in Micro-Bioreactors

The recovery of physiological functionality, which is commonly seen in tissue mimetic three-dimensional (3D) cellular aggregates (organoids, spheroids, acini, etc.), has been observed in cells of many origins (primary tissues, embryonic stem cells (ESCs), induced pluripotent stem cells (iPSCs), and immortal cell lines). This plurality and plasticity suggest that probably several basic principles promote this recovery process. The aim of this study was to identify these basic principles and describe how they are regulated so that they can be taken in consideration when micro-bioreactors are designed. Here, we provide evidence that one of these basic principles is hypoxia, which is a natural consequence of multicellular structures grown in microgravity cultures. Hypoxia drives a partial metabolic reprogramming to aerobic glycolysis and an increased anabolic synthesis. A second principle is the activation of cytoplasmic glutaminolysis for lipogenesis. Glutaminolysis is activated in the presence of hypo- or normo-glycaemic conditions and in turn is geared to the hexosamine pathway. The reducing power needed is produced in the pentose phosphate pathway, a prime function of glucose metabolism. Cytoskeletal reconstruction, histone modification, and the recovery of the physiological phenotype can all be traced to adaptive changes in the underlying cellular metabolism. These changes are coordinated by mTOR/Akt, p53 and non-canonical Wnt signaling pathways, while myc and NF-kB appear to be relatively inactive. Partial metabolic reprogramming to aerobic glycolysis, originally described by Warburg, is independent of the cell’s rate of proliferation, but is interwoven with the cells abilities to execute advanced functionality needed for replicating the tissues physiological performance.

Proteome Heterogeneity in Colorectal Cancer

Tumor heterogeneity is an important feature of colorectal cancer (CRC) manifested by dynamic changes in gene expression, protein expression, and availability of different tumor subtypes. Recent publications in the past 10 years have revealed proteome heterogeneity between different colorectal tumors and within the same tumor site. This paper reviews recent research works on the proteome heterogeneity in CRC, which includes the heterogeneity within a single tumor (intratumor heterogeneity), between different anatomical sites at the same organ, and between primary and metastatic sites (intertumor heterogeneity). The potential use of proteome heterogeneity in precision medicine and its implications in biomarker discovery and therapeutic outcomes will be discussed. Identification of the unique proteome landscape between and within individual tumors is imperative for understanding cancer biology and the management of CRC patients.

Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes

Tumor heterogeneity has been identified at various -omic levels. The tumor genome, transcriptome, proteome, and phenome can vary widely across cells in patient tumors and are influenced by tumor cell interactions with heterogeneous physical conditions and cellular components of the tumor microenvironment. Here, we explore the concept that while variation exists at multiple -omic levels, changes at each of these levels converge on the same pathways and lead to convergent phenotypes in tumors that can provide common drug targets. These phenotypes include cellular growth and proliferation, sustained oncogenic signaling, and immune avoidance, among others. Tumor heterogeneity complicates treatment of patient cancers as it leads to varied response to therapies. Identification of convergent cellular phenotypes arising in patient cancers and targeted therapies that reverse them has the potential to transform the way clinicians treat these cancers and to improve patient outcome.

Rearrangement of mitochondrial pyruvate dehydrogenase subunit dihydrolipoamide dehydrogenase protein-protein interactions by the MDM2 ligand nutlin-3

Drugs targeting MDM2's hydrophobic pocket activate p53. However, these agents act allosterically and have agonist effects on MDM2's protein interaction landscape. Dominant p53‐independent MDM2‐drug responsive‐binding proteins have not been stratified. We used as a variable the differential expression of MDM2 protein as a function of cell density to identify Nutlin‐3 responsive MDM2‐binding proteins that are perturbed independent of cell density using SWATH‐MS. Dihydrolipoamide dehydrogenase, the E3 subunit of the mitochondrial pyruvate dehydrogenase complex, was one of two Nutlin‐3 perturbed proteins identified fours hour posttreatment at two cell densities. Immunoblotting confirmed that dihydrolipoamide dehydrogenase was induced by Nutlin‐3. Depletion of MDM2 using siRNA also elevated dihydrolipoamide dehydrogenase in Nutlin‐3 treated cells. Mitotracker confirmed that Nutlin‐3 inhibits mitochondrial activity. Enrichment of mitochondria using TOM22+ immunobeads and TMT labeling defined key changes in the mitochondrial proteome after Nutlin‐3 treatment. Proximity ligation identified rearrangements of cellular protein–protein complexes in situ. In response to Nutlin‐3, a reduction of dihydrolipoamide dehydrogenase/dihydrolipoamide acetyltransferase protein complexes highlighted a disruption of the pyruvate dehydrogenase complex. This coincides with an increase in MDM2/dihydrolipoamide dehydrogenase complexes in the nucleus that was further enhanced by the nuclear export inhibitor Leptomycin B. The data suggest one therapeutic impact of MDM2 drugs might be on the early perturbation of specific protein–protein interactions within the mitochondria. This methodology forms a blueprint for biomarker discovery that can identify rearrangements of MDM2 protein–protein complexes in drug‐treated cells.

Risk analysis of colorectal cancer incidence by gene expression analysis

Background

Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction.

Objective

Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples.

Methods

We collected microarray data from the GEO database to establish colorectal cancer microarray gene expression datasets for a combined analysis. Using the Prediction Analysis for Microarrays (PAM) method and the GSEA MSigDB resource, we analyzed the 14,698 genes that were identified through an examination of their expression values between normal and tumor tissues.

Results

Ten genes (ABCG2, AQP8, SPIB, CA7, CLDN8, SCNN1B, SLC30A10, CD177, PADI2, and TGFBI) were found to be good indicators of the candidate genes that correlate with CRC. From these selected genes, an average of six significant genes were obtained using the PAM method, with an accuracy rate of 95%. The results demonstrate the potential of utilizing a model with the PAM method for data mining. After a detailed review of the published reports, the results confirmed that the screened candidate genes are good indicators for cancer risk analysis using the PAM method.

Conclusions

Six genes were selected with 95% accuracy to effectively classify normal and colorectal cancer tissues. We hope that these results will provide the basis for new research projects in clinical practice that aim to rapidly assess colorectal cancer risk using microarray gene expression analysis.

TGF-β Signaling in Gastrointestinal Cancers: Progress in Basic and Clinical Research

Transforming growth factor (TGF)-β superfamily proteins have many important biological functions, including regulation of tissue differentiation, cell proliferation, and migration in both normal and cancer cells. Many studies have reported that TGF-β signaling is associated with disease progression and therapeutic resistance in several cancers. Similarly, TGF-β-induced protein (TGFBI)—a downstream component of the TGF-β signaling pathway—has been shown to promote and/or inhibit cancer. Here, we review the state of basic and clinical research on the roles of TGF-β and TGFBI in gastrointestinal cancers.

Prognostic prediction by liver tissue proteomic profiling in patients with colorectal liver metastases

AIM

To obtain proteomic profiles in patients with colorectal liver metastases (CRLM) and identify the relationship between profiles and the prognosis of CRLM patients.

MATERIALS & METHODS

Prognosis prediction (favorable or unfavorable according to Fong's score) by a classification and regression tree algorithm of surface-enhanced laser desorption/ionization TOF-MS proteomic profiles from cryopreserved CRLM (patients) and normal liver tissue (controls).

RESULTS

The protein peak 7371 m/z showed the clearest differences between CRLM and control groups (94.1% sensitivity, 100% specificity, p < 0.001). The algorithm that best differentiated favorable and unfavorable groups combined 2970 and 2871 m/z protein peaks (100% sensitivity, 90% specificity).

CONCLUSION

Proteomic profiling in liver samples using classification and regression tree algorithms is a promising technique to differentiate healthy subjects from CRLM patients and to classify the severity of CRLM patients.

Cancer heterogeneity is not compatible with one unique cancer cell metabolic map

The Warburg effect and its accompanying metabolic features (anaplerosis, cataplerosis) are presented in textbooks and reviews as a hallmark (general characteristic): the metabolic map of cancer. On the other hand, research articles on specific tumors since a few years emphasize various biological features of different cancers, different cells in a cancer and the dynamic heterogeneity of these cells. We have analysed the research literature of the subject and show the generality of a dynamic, evolving biological and metabolic, spatial and temporal heterogeneity of individual cancers. We conclude that there is no one metabolic map of cancer but several and describe the two extremes of a panel from the hypoxic to the normoxic state. The implications for the significance of general ‘omic' studies, and on therapeutic conclusions drawn from them and for the diagnostic use of fractional biopsies is discussed.

Colorectal Cancer Classification and Cell Heterogeneity: A Systems Oncology Approach

Colorectal cancer is a heterogeneous disease that manifests through diverse clinical scenarios. During many years, our knowledge about the variability of colorectal tumors was limited to the histopathological analysis from which generic classifications associated with different clinical expectations are derived. However, currently we are beginning to understand that under the intense pathological and clinical variability of these tumors there underlies strong genetic and biological heterogeneity. Thus, with the increasing available information of inter-tumor and intra-tumor heterogeneity, the classical pathological approach is being displaced in favor of novel molecular classifications. In the present article, we summarize the most relevant proposals of molecular classifications obtained from the analysis of colorectal tumors using powerful high throughput techniques and devices. We also discuss the role that cancer systems biology may play in the integration and interpretation of the high amount of data generated and the challenges to be addressed in the future development of precision oncology. In addition, we review the current state of implementation of these novel tools in the pathological laboratory and in clinical practice.

Positive regulatory effects of perioperative probiotic treatment on postoperative liver complications after colorectal liver metastases surgery: a double-center and double-blind randomized clinical trial

BACKGROUND

Colorectal liver metastases (CLM) occur frequently and postoperative intestinal infection is a common complication. Our previous study showed that probiotics could decrease the rate of infectious complications after colectomy for colorectal cancer. To determine the effects of the perioperative administration of probiotics on serum zonulin levels which is a marker of intestinal permeability and the subsequent impact on postoperative infectious complications in patients with CLM.

METHODS

150 patients with CLM were randomly divided into control group (n = 68) and probiotics group (n = 66). Probiotics and placebo were given orally for 6 days preoperatively and 10 days postoperatively to control group and probiotics group respectively. We used the local resection for metastatic tumor ,while for large tumor, the segmental hepatectomy. Postoperative outcome were recorded. Furthermore, complications in patients with normal intestinal barrier function and the relation with serum zonulin were analyzed to evaluate the impact on the liver barrier dysfunction.

RESULTS

The incidence of infectious complications in the probiotics group was lower than control group. Analysis of CLM patients with normal postoperative intestinal barrier function paralleled with the serum zonulin level. And probiotics could also reduce the concentration of serum zonulin (P = 0.004) and plasma endotoxin (P < 0.001).

CONCLUSION

Perioperative probiotics treatment could reduce the serum zonulin level, the rate of postoperative septicemia and maintain the liver barrier in patients undergoing CLM surgery. we propose a new model about the regulation of probiotics to liver barrier via clinical regulatory pathway. We recommend the preoperative oral intake of probiotics combined with postoperative continued probiotics treatment in patients who undergo CLM surgery.

TRIAL REGISTRATION

ChiCTR-TRC- 12002841 . 2012/12/21.

Intratumoral heterogeneity and consequences for targeted therapies

According to the clonal model and Darwinian evolution, cancer cell evolves through new mutations helping it to proliferate, migrate, invade and metastasize. Recent genetic studies have clearly shown that tumors, when diagnosed, consist of a large number of mutations distributed in different cells. This heterogeneity translates in substantial genetic plasticity enabling cancer cells to adapt to any hostile environment. As targeted therapy focuses only on one pathway or protein, there will always be a cell with the "right" genetic background to survive the treatment and cause tumor relapse. Because today's targeted therapies never took tumor heterogeneity into account, nearly all novel drugs fail to provide patients with a considerable improvement of the survival. However, emerging proteomic studies guided by the idea that Darwinian selection is governed by the phenotype and not genotype, show that heterogeneity at the protein level is much less complex, then it could be expected from genetic studies. This information together with the recent trend to switch from functional to cytotoxic targeting may offer an entirely new strategy to efficiently combat cancer.

De novo discovery of phenotypic intratumour heterogeneity using imaging mass spectrometry

An essential and so far unresolved factor influencing the evolution of cancer and the clinical management of patients is intratumour clonal and phenotypic heterogeneity. However, the de novo identification of tumour subpopulations is so far both a challenging and an unresolved task. Here we present the first systematic approach for the de novo discovery of clinically detrimental molecular tumour subpopulations. In this proof-of-principle study, spatially resolved, tumour-specific mass spectra were acquired, using matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry, from tissues of 63 gastric carcinoma and 32 breast carcinoma patients. The mass spectra, representing the proteomic heterogeneity within tumour areas, were grouped by a corroborated statistical clustering algorithm in order to obtain segmentation maps of molecularly distinct regions. These regions were presumed to represent different phenotypic tumour subpopulations. This was confirmed by linking the presence of these tumour subpopulations to the patients' clinical data. This revealed several of the detected tumour subpopulations to be associated with a different overall survival of the gastric cancer patients (p = 0.025) and the presence of locoregional metastases in patients with breast cancer (p = 0.036). The procedure presented is generic and opens novel options in cancer research, as it reveals microscopically indistinct tumour subpopulations that have an adverse impact on clinical outcome. This enables their further molecular characterization for deeper insights into the biological processes of cancer, which may finally lead to new targeted therapies.