Targeted multiplex proteomics for molecular prescreening and biomarker discovery in metastatic colorectal cancer

MYC targeting by OMO-103 in solid tumors: a phase 1 trial

Among the 'most wanted' targets in cancer therapy is the oncogene MYC, which coordinates key transcriptional programs in tumor development and maintenance. It has, however, long been considered undruggable. OMO-103 is a MYC inhibitor consisting of a 91-amino acid miniprotein. Here we present results from a phase 1 study of OMO-103 in advanced solid tumors, established to examine safety and tolerability as primary outcomes and pharmacokinetics, recommended phase 2 dose and preliminary signs of activity as secondary ones. A classical 3 + 3 design was used for dose escalation of weekly intravenous, single-agent OMO-103 administration in 21-day cycles, encompassing six dose levels (DLs). A total of 22 patients were enrolled, with treatment maintained until disease progression. The most common adverse events were grade 1 infusion-related reactions, occurring in ten patients. One dose-limiting toxicity occurred at DL5. Pharmacokinetics showed nonlinearity, with tissue saturation signs at DL5 and a terminal half-life in serum of 40 h. Of the 19 patients evaluable for response, 12 reached the predefined 9-week time point for assessment of drug antitumor activity, eight of those showing stable disease by computed tomography. One patient defined as stable disease by response evaluation criteria in solid tumors showed a 49% reduction in total tumor volume at best response. Transcriptomic analysis supported target engagement in tumor biopsies. In addition, we identified soluble factors that are potential pharmacodynamic and predictive response markers. Based on all these data, the recommended phase 2 dose was determined as DL5 (6.48 mg kg-1).ClinicalTrials.gov identifier: NCT04808362 .

An Updated Review on Molecular Biomarkers in Diagnosis and Therapy of Colorectal Cancer

Colorectal cancer is one of the most common cancer types worldwide. Since colorectal cancer takes time to develop, its incidence and mortality can be treated effectively if it is detected in its early stages. As a result, non-invasive or invasive biomarkers play an essential role in the early diagnosis of colorectal cancer. Many experimental studies have been carried out to assess genetic, epigenetic, or protein markers in feces, serum, and tissue. It may be possible to find biomarkers that will help with the diagnosis of colorectal cancer by identifying the genes, RNAs, and/or proteins indicative of cancer growth. Recent advancements in the molecular subtypes of colorectal cancer, DNA methylation, microRNAs, long noncoding RNAs, exosomes, and their involvement in colorectal cancer have led to the discovery of novel biomarkers. In small-scale investigations, most biomarkers appear promising. However, large-scale clinical trials are required to validate their effectiveness before routine clinical implementation. Hence, this review focuses on small-scale investigations and results of big data analysis that may provide an overview of the biomarkers for the diagnosis, therapy, and prognosis of colorectal cancer.

A single protein to multiple peptides: Investigation of protein-peptide correlations using targeted alpha-2-macroglobulin analysis

Recent advances in proteomics technologies have enabled the analysis of thousands of proteins in a high-throughput manner. Mass spectrometry (MS) based proteomics uses a peptide-centric approach where biological samples undergo specific proteolytic digestion and then only unique peptides are used for protein identification and quantification. Considering the fact that a single protein may have multiple unique peptides and a number of different forms, it becomes essential to understand dynamic protein-peptide relationships to ensure robust and reliable peptide-centric protein analysis. In this study, we investigated the correlation between protein concentration and corresponding unique peptide responses under a conventional proteolytic digestion condition. Protein-peptide correlation, digestion efficiency, matrix-effect, and concentration-effect were evaluated. Twelve unique peptides of alpha-2-macroglobulin (A2MG) were monitored using a targeted MS approach to acquire insights into protein-peptide dynamics. Although the peptide responses were reproducible between replicates, protein-peptide correlation was moderate in protein standards and low in complex matrices. The results suggest that reproducible peptide signal could be misleading in clinical studies and a peptide selection could dramatically change the outcome at protein level. This is the first study investigating quantitative protein-peptide correlations in biological samples using all unique peptides representing the same protein and opens a discussion on peptide-based proteomics.

An Introduction to Advanced Targeted Acquisition Methods

Targeted proteomics via selected reaction monitoring (SRM) or parallel reaction monitoring (PRM) enables fast and sensitive detection of a preselected set of target peptides. However, the number of peptides that can be monitored in conventional targeting methods is usually rather small. Recently, a series of methods has been described that employ intelligent acquisition strategies to increase the efficiency of mass spectrometers to detect target peptides. These methods are based on one of two strategies. First, retention time adjustment-based methods enable intelligent scheduling of target peptide retention times. These include Picky, iRT, as well as spike-in free real-time adjustment methods such as MaxQuant.Live. Second, in spike-in triggered acquisition methods such as SureQuant, Pseudo-PRM, TOMAHAQ, and Scout-MRM, targeted scans are initiated by abundant labeled synthetic peptides added to samples before the run. Both strategies enable the mass spectrometer to better focus data acquisition time on target peptides. This either enables more sensitive detection or a higher number of targets per run. Here, we provide an overview of available advanced targeting methods and highlight their intrinsic strengths and weaknesses and compatibility with specific experimental setups. Our goal is to provide a basic introduction to advanced targeting methods for people starting to work in this field.

Integrated approaches for precision oncology in colorectal cancer: The more you know, the better

Colorectal cancer (CRC) is one of the most common human malignancies accounting for approximately 10 % of worldwide cancer incidence and mortality. While early-stage CRC is mainly a preventable and curable disease, metastatic colorectal cancer (mCRC) remains an unmet clinical need. Moreover, about 25 % of CRC cases are diagnosed only at the metastatic stage. Despite the extensive molecular and functional knowledge on this disease, systemic therapy for mCRC still relies on traditional 5-fluorouracil (5-FU)-based chemotherapy regimens. On the other hand, targeted therapies and immunotherapy have shown effectiveness only in a limited subset of patients. For these reasons, there is a growing need to define the molecular and biological landscape of individual patients to implement novel, rationally driven, tailored therapies. In this review, we explore current and emerging approaches for CRC management such as genomic, transcriptomic and metabolomic analysis, the use of liquid biopsies and the implementation of patients' preclinical avatars. In particular, we discuss the contribution of each of these tools in elucidating patient specific features, with the aim of improving our ability in advancing the diagnosis and treatment of colorectal tumors.

TOP2A expression predicts responsiveness to carfilzomib in myeloma and informs novel combinatorial strategies for enhanced proteasome inhibitor cell killing

Microarray was utilized to determine if a genetic signature associated with resistance to carfilzomib (CFZ) could be identified. Twelve human myeloma (MM) cell lines (HMCLs) were treated with CFZ and a cell-viability profile was assessed categorizing HMCLs as sensitive or resistant to CFZ. The gene expression profiles (GEP) of untreated resistant versus sensitive HMCLs revealed 29 differentially expressed genes. TOP2A, an enzyme involved in cell cycle and proliferation, was overexpressed in carfilzomib-resistant HMCLs. TOP2A protein expression levels, evaluated utilizing trephine biopsy specimens acquired prior to treatment with proteasome inhibitors, were higher in patients failing to achieve a response when compared to responding patients. Logistic-regression analysis confirmed that TOP2A protein expression was a highly significant predictor of response to PIs (AUC 0.738). Further, the combination of CFZ with TOP2A inhibitors, demonstrated synergistic cytotoxic effects in vitro, providing a rationale for combining topoisomerase inhibitors with CFZ to overcome resistance in MM.

Lineage Reversion Drives WNT Independence in Intestinal Cancer

The WNT pathway is a fundamental regulator of intestinal homeostasis, and hyperactivation of WNT signaling is the major oncogenic driver in colorectal cancer. To date, there are no described mechanisms that bypass WNT dependence in intestinal tumors. Here, we show that although WNT suppression blocks tumor growth in most organoid and in vivo colorectal cancer models, the accumulation of colorectal cancer-associated genetic alterations enables drug resistance and WNT-independent growth. In intestinal epithelial cells harboring mutations in KRAS or BRAF, together with disruption of TP53 and SMAD4, transient TGFβ exposure drives YAP/TAZ-dependent transcriptional reprogramming and lineage reversion. Acquisition of embryonic intestinal identity is accompanied by a permanent loss of adult intestinal lineages, and long-term WNT-independent growth. This work identifies genetic and microenvironmental factors that drive WNT inhibitor resistance, defines a new mechanism for WNT-independent colorectal cancer growth, and reveals how integration of associated genetic alterations and extracellular signals can overcome lineage-dependent oncogenic programs. SIGNIFICANCE: Colorectal and intestinal cancers are driven by mutations in the WNT pathway, and drugs aimed at suppressing WNT signaling are in active clinical development. Our study identifies a mechanism of acquired resistance to WNT inhibition and highlights a potential strategy to target those drug-resistant cells.This article is highlighted in the In This Issue feature, p. 1426.

EGFR Blockade Reverts Resistance to KRASG12C Inhibition in Colorectal Cancer

Most patients with KRAS G12C-mutant non-small cell lung cancer (NSCLC) experience clinical benefit from selective KRASG12C inhibition, whereas patients with colorectal cancer bearing the same mutation rarely respond. To investigate the cause of the limited efficacy of KRASG12C inhibitors in colorectal cancer, we examined the effects of AMG510 in KRAS G12C colorectal cancer cell lines. Unlike NSCLC cell lines, KRAS G12C colorectal cancer models have high basal receptor tyrosine kinase (RTK) activation and are responsive to growth factor stimulation. In colorectal cancer lines, KRASG12C inhibition induces higher phospho-ERK rebound than in NSCLC cells. Although upstream activation of several RTKs interferes with KRASG12C blockade, we identify EGFR signaling as the dominant mechanism of colorectal cancer resistance to KRASG12C inhibitors. The combinatorial targeting of EGFR and KRASG12C is highly effective in colorectal cancer cells and patient-derived organoids and xenografts, suggesting a novel therapeutic strategy to treat patients with KRAS G12C colorectal cancer. SIGNIFICANCE: The efficacy of KRASG12C inhibitors in NSCLC and colorectal cancer is lineage-specific. RTK dependency and signaling rebound kinetics are responsible for sensitivity or resistance to KRASG12C inhibition in colorectal cancer. EGFR and KRASG12C should be concomitantly inhibited to overcome resistance to KRASG12C blockade in colorectal tumors.See related commentary by Koleilat and Kwong, p. 1094.This article is highlighted in the In This Issue feature, p. 1079.

Patient-specific multi-omics models and the application in personalized combination therapy

The rapid advancement of high-throughput technologies and sharp decrease in cost have opened up the possibility to generate large amount of multi-omics data on an individual basis. The development of high-throughput -omics, including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics, enables the application of multi-omics technologies in the clinical settings. Combination therapy, defined as disease treatment with two or more drugs to achieve efficacy with lower doses or lower drug toxicity, is the basis for the care of diseases like cancer. Patient-specific multi-omics data integration can help the identification and development of combination therapies. In this review, we provide an overview of different -omics platforms, and discuss the methods for multi-omics, high-throughput, data integration, personalized combination therapy.

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Effect of polysaccharide extract SPSS1 from Apostichopus japonicas spermary on HepG2 cells via iTRAQ-based proteome analysis

In this study, polysaccharide extract was prepared from Apostichopus japonicus spermary and purified by ion-exchange chromatography and gel filtration chromatography. Two main fractions named SPSS1 and SPSS2 were obtained and analyzed by ultraviolet spectroscopy and mixed with KBr, respectively. Chemical components analysis proved that SPSS1 and SPSS2 were rich in sulfate. Monosaccharide analysis indicated that in addition to the high content of lactose in both kinds of polysaccharides, the highest content of monosaccharide in SPSS1 was galactose, while in SPSS2 it was fucose. Further, the antitumor study of SPSS1 was carried and the results showed that SPSS1 treatment inhibited the proliferation of HepG2 cells. Through the iTRAQ-based proteome analysis, there were 208 differential proteins between control tumor cells and SPSS1 treatment of tumor cells. Compared to control tumor cells, 135 proteins were upregulated and 73 proteins were downregulated in treatment tumor cells. PRACTICAL APPLICATIONS: Our study suggested that polysaccharide from sea cucumbers had the potential to be further developed as antitumor drugs.